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Original Research – Definition, Examples, Guide

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Original Research

Definition:

Original research refers to a type of research that involves the collection and analysis of new and original data to answer a specific research question or to test a hypothesis. This type of research is conducted by researchers who aim to generate new knowledge or add to the existing body of knowledge in a particular field or discipline.

Types of Original Research

There are several types of original research that researchers can conduct depending on their research question and the nature of the data they are collecting. Some of the most common types of original research include:

Basic Research

This type of research is conducted to expand scientific knowledge and to create new theories, models, or frameworks. Basic research often involves testing hypotheses and conducting experiments or observational studies.

Applied Research

This type of research is conducted to solve practical problems or to develop new products or technologies. Applied research often involves the application of basic research findings to real-world problems.

Exploratory Research

This type of research is conducted to gather preliminary data or to identify research questions that need further investigation. Exploratory research often involves collecting qualitative data through interviews, focus groups, or observations.

Descriptive Research

This type of research is conducted to describe the characteristics or behaviors of a population or a phenomenon. Descriptive research often involves collecting quantitative data through surveys, questionnaires, or other standardized instruments.

Correlational Research

This type of research is conducted to determine the relationship between two or more variables. Correlational research often involves collecting quantitative data and using statistical analyses to identify correlations between variables.

Experimental Research

This type of research is conducted to test cause-and-effect relationships between variables. Experimental research often involves manipulating one or more variables and observing the effect on an outcome variable.

Longitudinal Research

This type of research is conducted over an extended period of time to study changes in behavior or outcomes over time. Longitudinal research often involves collecting data at multiple time points.

Original Research Methods

Original research can involve various methods depending on the research question, the nature of the data, and the discipline or field of study. However, some common methods used in original research include:

This involves the manipulation of one or more variables to test a hypothesis. Experimental research is commonly used in the natural sciences, such as physics, chemistry, and biology, but can also be used in social sciences, such as psychology.

Observational Research

This involves the collection of data by observing and recording behaviors or events without manipulation. Observational research can be conducted in the natural setting of the behavior or in a laboratory setting.

Survey Research

This involves the collection of data from a sample of participants using questionnaires or interviews. Survey research is commonly used in social sciences, such as sociology, political science, and economics.

Case Study Research

This involves the in-depth analysis of a single case, such as an individual, organization, or event. Case study research is commonly used in social sciences and business studies.

Qualitative research

This involves the collection and analysis of non-numerical data, such as interviews, focus groups, and observation notes. Qualitative research is commonly used in social sciences, such as anthropology, sociology, and psychology.

Quantitative research

This involves the collection and analysis of numerical data using statistical methods. Quantitative research is commonly used in natural sciences, such as physics, chemistry, and biology, as well as in social sciences, such as psychology and economics.

Researchers may also use a combination of these methods in their original research depending on their research question and the nature of their data.

Data Collection Methods

There are several data collection methods that researchers can use in original research, depending on the nature of the research question and the type of data that needs to be collected. Some of the most common data collection methods include:

• Surveys : Surveys involve asking participants to respond to a series of questions about their attitudes, behaviors, beliefs, or experiences. Surveys can be conducted in person, over the phone, through email, or online.
• Interviews : Interviews involve asking participants open-ended questions about their experiences, beliefs, or behaviors. Interviews can be conducted in person, over the phone, or through video conferencing.
• Observations : Observations involve observing and recording participants’ behaviors or interactions in a natural or laboratory setting. Observations can be conducted using structured or unstructured methods.
• Experiments : Experiments involve manipulating one or more variables and observing the effect on an outcome variable. Experiments can be conducted in a laboratory or in the natural environment.
• Case studies: Case studies involve conducting an in-depth analysis of a single case, such as an individual, organization, or event. Case studies can involve the collection of qualitative or quantitative data.
• Focus groups: Focus groups involve bringing together a small group of participants to discuss a specific topic or issue. Focus groups can be conducted in person or online.
• Document analysis: Document analysis involves collecting and analyzing written or visual materials, such as reports, memos, or videos, to answer research questions.

Data Analysis Methods

Once data has been collected in original research, it needs to be analyzed to answer research questions and draw conclusions. There are various data analysis methods that researchers can use, depending on the type of data collected and the research question. Some common data analysis methods used in original research include:

• Descriptive statistics: This involves using statistical measures such as mean, median, mode, and standard deviation to describe the characteristics of the data.
• Inferential statistics: This involves using statistical methods to infer conclusions about a population based on a sample of data.
• Regression analysis: This involves examining the relationship between two or more variables by using statistical models that predict the value of one variable based on the value of one or more other variables.
• Content analysis: This involves analyzing written or visual materials, such as documents, videos, or social media posts, to identify patterns, themes, or trends.
• Qualitative analysis: This involves analyzing non-numerical data, such as interview transcripts or observation notes, to identify themes, patterns, or categories.
• Grounded theory: This involves developing a theory or model based on the data collected in the study.
• Mixed methods analysis: This involves combining quantitative and qualitative data analysis methods to provide a more comprehensive understanding of the research question.

How to Conduct Original Research

Conducting original research involves several steps that researchers need to follow to ensure that their research is valid, reliable, and produces meaningful results. Here are some general steps that researchers can follow to conduct original research:

• Identify the research question: The first step in conducting original research is to identify a research question that is relevant, significant, and feasible. The research question should be specific and focused to guide the research process.
• Conduct a literature review: Once the research question is identified, researchers should conduct a thorough literature review to identify existing research on the topic. This will help them identify gaps in the existing knowledge and develop a research plan that builds on previous research.
• Develop a research plan: Researchers should develop a research plan that outlines the methods they will use to collect and analyze data. The research plan should be detailed and include information on the population and sample, data collection methods, data analysis methods, and ethical considerations.
• Collect data: Once the research plan is developed, researchers can begin collecting data using the methods identified in the plan. It is important to ensure that the data collection process is consistent and accurate to ensure the validity and reliability of the data.
• Analyze data: Once the data is collected, researchers should analyze it using appropriate data analysis methods. This will help them answer the research question and draw conclusions from the data.
• Interpret results: After analyzing the data, researchers should interpret the results and draw conclusions based on the findings. This will help them answer the research question and make recommendations for future research or practical applications.
• Communicate findings: Finally, researchers should communicate their findings to the appropriate audience using a format that is appropriate for the research question and audience. This may include writing a research paper, presenting at a conference, or creating a report for a client or stakeholder.

Purpose of Original Research

The purpose of original research is to generate new knowledge and understanding in a particular field of study. Original research is conducted to address a research question, hypothesis, or problem and to produce empirical evidence that can be used to inform theory, policy, and practice. By conducting original research, researchers can:

• Expand the existing knowledge base: Original research helps to expand the existing knowledge base by providing new information and insights into a particular phenomenon. This information can be used to develop new theories, models, or frameworks that explain the phenomenon in greater depth.
• Test existing theories and hypotheses: Original research can be used to test existing theories and hypotheses by collecting empirical evidence and analyzing the data. This can help to refine or modify existing theories, or to develop new ones that better explain the phenomenon.
• Identify gaps in the existing knowledge: Original research can help to identify gaps in the existing knowledge base by highlighting areas where further research is needed. This can help to guide future research and identify new research questions that need to be addressed.
• Inform policy and practice: Original research can be used to inform policy and practice by providing empirical evidence that can be used to make decisions and develop interventions. This can help to improve the quality of life for individuals and communities, and to address social, economic, and environmental challenges.

How to publish Original Research

Publishing original research involves several steps that researchers need to follow to ensure that their research is accepted and published in reputable academic journals. Here are some general steps that researchers can follow to publish their original research:

• Select a suitable journal: Researchers should identify a suitable academic journal that publishes research in their field of study. The journal should have a good reputation and a high impact factor, and should be a good fit for the research topic and methods used.
• Review the submission guidelines: Once a suitable journal is identified, researchers should review the submission guidelines to ensure that their manuscript meets the journal’s requirements. The guidelines may include requirements for formatting, length, and content.
• Write the manuscript : Researchers should write the manuscript in accordance with the submission guidelines and academic standards. The manuscript should include a clear research question or hypothesis, a description of the research methods used, an analysis of the data collected, and a discussion of the results and their implications.
• Submit the manuscript: Once the manuscript is written, researchers should submit it to the selected journal. The submission process may require the submission of a cover letter, abstract, and other supporting documents.
• Respond to reviewer feedback: After the manuscript is submitted, it will be reviewed by experts in the field who will provide feedback on the quality and suitability of the research. Researchers should carefully review the feedback and revise the manuscript accordingly.
• Respond to editorial feedback: Once the manuscript is revised, it will be reviewed by the journal’s editorial team who will provide feedback on the formatting, style, and content of the manuscript. Researchers should respond to this feedback and make any necessary revisions.
• Acceptance and publication: If the manuscript is accepted, the journal will inform the researchers and the manuscript will be published in the journal. If the manuscript is not accepted, researchers can submit it to another journal or revise it further based on the feedback received.

How to Identify Original Research

To identify original research, there are several factors to consider:

• The research question: Original research typically starts with a novel research question or hypothesis that has not been previously explored or answered in the existing literature.
• The research design: Original research should have a clear and well-designed research methodology that follows appropriate scientific standards. The methodology should be described in detail in the research article.
• The data: Original research should include new data that has not been previously published or analyzed. The data should be collected using appropriate research methods and analyzed using valid statistical methods.
• The results: Original research should present new findings or insights that have not been previously reported in the existing literature. The results should be presented clearly and objectively, and should be supported by the data collected.
• The discussion and conclusions: Original research should provide a clear and objective interpretation of the results, and should discuss the implications of the research findings. The discussion and conclusions should be based on the data collected and the research question or hypothesis.
• The references: Original research should be supported by references to existing literature, which should be cited appropriately in the research article.

Advantages of Original Research

Original research has several advantages, including:

• Generates new knowledge: Original research is conducted to answer novel research questions or hypotheses, which can generate new knowledge and insights into various fields of study.
• Supports evidence-based decision making: Original research provides empirical evidence that can inform decision-making in various fields, such as medicine, public policy, and business.
• Enhances academic and professional reputation: Conducting original research and publishing in reputable academic journals can enhance a researcher’s academic and professional reputation.
• Provides opportunities for collaboration: Original research can provide opportunities for collaboration between researchers, institutions, and organizations, which can lead to new partnerships and research projects.
• Advances scientific and technological progress: Original research can contribute to scientific and technological progress by providing new knowledge and insights into various fields of study, which can inform further research and development.
• Can lead to practical applications: Original research can have practical applications in various fields, such as medicine, engineering, and social sciences, which can lead to new products, services, and policies that benefit society.

Limitations of Original Research

Original research also has some limitations, which include:

• Time and resource constraints: Original research can be time-consuming and expensive, requiring significant resources to design, execute, and analyze the research data.
• Ethical considerations: Conducting original research may raise ethical considerations, such as ensuring the privacy and confidentiality of research participants, obtaining informed consent, and avoiding conflicts of interest.
• Risk of bias: Original research may be subject to biases, such as selection bias, measurement bias, and publication bias, which can affect the validity and reliability of the research findings.
• Generalizability: Original research findings may not be generalizable to larger populations or different contexts, which can limit the applicability of the research findings.
• Replicability: Original research may be difficult to replicate, which can limit the ability of other researchers to verify the research findings.
• Limited scope: Original research may have a limited scope, focusing on a specific research question or hypothesis, which can limit the breadth of the research findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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What is an original research article?

An original research article is a report of research activity that is written by the researchers who conducted the research or experiment. Original research articles may also be referred to as: “primary research articles” or “primary scientific literature.” In science courses, instructors may also refer to these as “peer-reviewed articles” or “refereed articles.”

Original research articles in the sciences have a specific purpose, follow a scientific article format, are peer reviewed, and published in academic journals.

Identifying Original Research: What to Look For

An "original research article" is an article that is reporting original research about new data or theories that have not been previously published. That might be the results of new experiments, or newly derived models or simulations. The article will include a detailed description of the methods used to produce them, so that other researchers can verify them. This description is often found in a section called "methods" or "materials and methods" or similar. Similarly, the results will generally be described in great detail, often in a section called "results."

Since the original research article is reporting the results of new research, the authors should be the scientists who conducted that research. They will have expertise in the field, and will usually be employed by a university or research lab.

In comparison, a newspaper or magazine article (such as in  The New York Times  or  National Geographic ) will usually be written by a journalist reporting on the actions of someone else.

An original research article will be written by and for scientists who study related topics. As such, the article should use precise, technical language to ensure that other researchers have an exact understanding of what was done, how to do it, and why it matters. There will be plentiful citations to previous work, helping place the research article in a broader context. The article will be published in an academic journal, follow a scientific format, and undergo peer-review.

Original research articles in the sciences follow the scientific format. ( This tutorial from North Carolina State University illustrates some of the key features of this format.)

Look for signs of this format in the subject headings or subsections of the article. You should see the following:

Scientific research that is published in academic journals undergoes a process called "peer review."

The peer review process goes like this:

• A researcher writes a paper and sends it in to an academic journal, where it is read by an editor
• The editor then sends the article to other scientists who study similar topics, who can best evaluate the article
• The scientists/reviewers examine the article's research methodology, reasoning, originality, and sginificance
• The scientists/reviewers then make suggestions and comments to impove the paper
• The original author is then given these suggestions and comments, and makes changes as needed
• This process repeats until everyone is satisfied and the article can be published within the academic journal

For more details about this process see the Peer Reviewed Publications guide.

This journal article  is an example. It was published in the journal  Royal Society Open Science  in 2015. Clicking on the button that says "Review History" will show the comments by the editors, reviewers and the author as it went through the peer review process. The "About Us" menu provides details about this journal; "About the journal" under that tab includes the statement that the journal is peer reviewed.

Review articles

There are a variety of article types published in academic, peer-reviewed journals, but the two most common are original research articles and review articles . They can look very similar, but have different purposes and structures.

Like original research articles, review articles are aimed at scientists and undergo peer-review. Review articles often even have “abstract,” “introduction,” and “reference” sections. However, they will not (generally) have a “methods” or “results” section because they are not reporting new data or theories. Instead, they review the current state of knowledge on a topic.

Press releases, newspaper or magazine articles

These won't be in a formal scientific format or be peer reviewed. The author will usually be a journalist, and the audience will be the general public. Since most readers are not interested in the precise details of the research, the language will usually be nontechnical and broad. Citations will be rare or nonexistent.

Tips for Finding Original research Articles

Search for articles in one of the library databases recommend for your subject area . If you are using Google, try searching in Google Scholar instead and you will get results that are more likely to be original research articles than what will come up in a regular Google search!

For tips on using library databases to find articles, see our Library DIY guides .

Tips for Finding the Source of a News Report about Science

If you've seen or heard a report about a new scientific finding or claim, these tips can help you find the original source:

• Often, the report will mention where the original research was published; look for sentences like "In an article published yesterday in the journal  Nature ..." You can use this to find the issue of the journal where the research was published, and look at the table of contents to find the original article.
• The report will often name the researchers involved. You can search relevant databases for their name and the topic of the report to find the original research that way.
• Sometimes you may have to go through multiple articles to find the original source. For example, a video or blog post may be based on a newspaper article, which in turn is reporting on a scientific discovery published in another journal; be sure to find the original research article.
• Don't be afraid to ask a librarian for help!

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Original Research

An original research paper should present a unique argument of your own. In other words, the claim of the paper should be debatable and should be your (the researcher’s) own original idea. Typically an original research paper builds on the existing research on a topic, addresses a specific question, presents the findings according to a standard structure (described below), and suggests questions for further research and investigation. Though writers in any discipline may conduct original research, scientists and social scientists in particular are interested in controlled investigation and inquiry. Their research often consists of direct and indirect observation in the laboratory or in the field. Many scientists write papers to investigate a hypothesis (a statement to be tested).

Although the precise order of research elements may vary somewhat according to the specific task, most include the following elements:

• Table of contents
• List of illustrations
• Body of the report
• References cited

Check your assignment for guidance on which formatting style is required. The Complete Discipline Listing Guide (Purdue OWL)  provides information on the most common style guide for each discipline, but be sure to check with your instructor.

The title of your work is important. It draws the reader to your text. A common practice for titles is to use a two-phrase title where the first phrase is a broad reference to the topic to catch the reader’s attention. This phrase is followed by a more direct and specific explanation of your project. For example:

“Lions, Tigers, and Bears, Oh My!: The Effects of Large Predators on Livestock Yields.”

The first phrase draws the reader in – it is creative and interesting. The second part of the title tells the reader the specific focus of the research.

In addition, data base retrieval systems often work with  keywords  extracted from the title or from a list the author supplies. When possible, incorporate them into the title. Select these words with consideration of how prospective readers might attempt to access your document. For more information on creating keywords, refer to this  Springer research publication guide.

See the KU Writing Center Writing Guide on Abstracts for detailed information about creating an abstract.

Table of Contents

The table of contents provides the reader with the outline and location of specific aspects of your document. Listings in the table of contents typically match the headings in the paper. Normally, authors number any pages before the table of contents as well as the lists of illustrations/tables/figures using lower-case roman numerals. As such, the table of contents will use lower-case roman numbers to identify the elements of the paper prior to the body of the report, appendix, and reference page. Additionally, because authors will normally use Arabic numerals (e.g., 1, 2, 3) to number the pages of the body of the research paper (starting with the introduction), the table of contents will use Arabic numerals to identify the main sections of the body of the paper (the introduction, literature review, methods, results, discussion, conclusion, references, and appendices).

Here is an example of a table of contents:

ABSTRACT..................................................iii

TABLE OF CONTENTS...............................iv

LIST OF ILLUSTRATIONS...........................v

LIST OF TABLES.........................................vii

INTRODUCTION..........................................1

LITERATURE REVIEW.................................6

METHODS....................................................9

RESULTS....................................................10

DISCUSSION..............................................16

CONCLUSION............................................18

REFERENCES............................................20

APPENDIX................................................. 23

More information on creating a table of contents can be found in the Table of Contents Guide (SHSU)  from the Newton Gresham Library at Sam Houston State University.

List of Illustrations

Authors typically include a list of the illustrations in the paper with longer documents. List the number (e.g., Illustration 4), title, and page number of each illustration under headings such as "List of Illustrations" or "List of Tables.”

Body of the Report

The tone of a report based on original research will be objective and formal, and the writing should be concise and direct. The structure will likely consist of these standard sections:  introduction, methods, results, discussion, and conclusion . Typically, authors identify these sections with headings and may use subheadings to identify specific themes within these sections (such as themes within the literature under the literature review section).

Introduction

Given what the field says about this topic, here is my contribution to this line of inquiry.

The introduction often consists of the rational for the project. What is the phenomenon or event that inspired you to write about this topic? What is the relevance of the topic and why is it important to study it now? Your introduction should also give some general background on the topic – but this should not be a literature review. This is the place to give your readers and necessary background information on the history, current circumstances, or other qualities of your topic generally. In other words, what information will a layperson need to know in order to get a decent understanding of the purpose and results of your paper? Finally, offer a “road map” to your reader where you explain the general order of the remainder of your paper. In the road map, do not just list the sections of the paper that will follow. You should refer to the main points of each section, including the main arguments in the literature review, a few details about your methods, several main points from your results/analysis, the most important takeaways from your discussion section, and the most significant conclusion or topic for further research.   

Literature Review

This is what other researchers have published about this topic.

In the literature review, you will define and clarify the state of the topic by citing key literature that has laid the groundwork for this investigation. This review of the literature will identify relations, contradictions, gaps, and inconsistencies between previous investigations and this one, and suggest the next step in the investigation chain, which will be your hypothesis. You should write the literature review in the  present tense  because it is ongoing information.

Methods (Procedures)

This is how I collected and analyzed the information.

This section recounts the procedures of the study. You will write this in  past tense  because you have already completed the study. It must include what is necessary to replicate and validate the hypothesis. What details must the reader know in order to replicate this study? What were your purposes in this study? The challenge in this section is to understand the possible readers well enough to include what is necessary without going into detail on “common-knowledge” procedures. Be sure that you are specific enough about your research procedure that someone in your field could easily replicate your study. Finally, make sure not to report any findings in this section.

This is what I found out from my research.

This section reports the findings from your research. Because this section is about research that is completed, you should write it primarily in the  past tense . The form and level of detail of the results depends on the hypothesis and goals of this report, and the needs of your audience. Authors of research papers often use visuals in the results section, but the visuals should enhance, rather than serve as a substitute, for the narrative of your results. Develop a narrative based on the thesis of the paper and the themes in your results and use visuals to communicate key findings that address your hypothesis or help to answer your research question. Include any unusual findings that will clarify the data. It is a good idea to use subheadings to group the results section into themes to help the reader understand the main points or findings of the research. 

This is what the findings mean in this situation and in terms of the literature more broadly.

This section is your opportunity to explain the importance and implications of your research. What is the significance of this research in terms of the hypothesis? In terms of other studies? What are possible implications for any academic theories you utilized in the study? Are there any policy implications or suggestions that result from the study? Incorporate key studies introduced in the review of literature into your discussion along with your own data from the results section. The discussion section should put your research in conversation with previous research – now you are showing directly how your data complements or contradicts other researchers’ data and what the wider implications of your findings are for academia and society in general. What questions for future research do these findings suggest? Because it is ongoing information, you should write the discussion in the  present tense . Sometimes the results and discussion are combined; if so, be certain to give fair weight to both.

These are the key findings gained from this research.

Summarize the key findings of your research effort in this brief final section. This section should not introduce new information. You can also address any limitations from your research design and suggest further areas of research or possible projects you would complete with a new and improved research design.

References/Works Cited

See KU Writing Center  writing guides  to learn more about different citation styles like APA, MLA, and Chicago.  Make an appointment  at the KU Writing Center for more help. Be sure to format the paper and references based on the citation style that your professor requires or based on the requirements of the academic journal or conference where you hope to submit the paper.

The appendix includes attachments that are pertinent to the main document but are too detailed to be included in the main text. These materials should be titled and labeled (for example Appendix A: Questionnaire). You should refer to the appendix in the text with in-text references so the reader understands additional useful information is available elsewhere in the document. Examples of documents to include in the appendix include regression tables, tables of text analysis data, and interview questions.

Updated June 2022  

Academic Integrity at MIT

A handbook for students, search form, writing original work.

One of the challenges of good scholarship is to take what has already been done, said, or argued, and incorporating it into your work in an original way. To some students, this task may seem unnecessarily redundant: a student writing a paper on the benefits of stem cell research may ask, “If the positive aspects of this research have already been argued, why do I need to do it again?” The answer is that:

by doing research on your subject, you become more familiar with existing scholarly work, which in turn can provide models for your own writing

your way of presenting the information and arguing it will be different from that of others and is therefore valuable; and

as more recent information on your subject becomes available, you have the opportunity to bring this information into your report or argument, adding new dimensions to the discussion.

Sometimes the goals of academic writing may seem contradictory.

Academic writing is a challenge. It demands that you build on work done by others but create something original from it. By acknowledging where you have used the ideas, work, or words of others, you maintain your academic integrity and uphold the standards of the Institute and of the discipline in which you work.

(Adapted from: Overview and Contradictions , Purdue University OWL Online Writing Lab. Retrieved July 2019.

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• Writing and Communication Center

How to Do Original Research

How to do original research? Although you’ll probably conduct most of your research online or in the library, remember that there’s a great deal of material you can find in laboratories, in courthouses, and in private archives. Consider the possibility of conducting some original research for your research paper. You can do this by  interviewing  knowledgeable people and devising and distributing questionnaires or  surveys . This may be required in class, so always check with your professor.

Original research is research you conduct rather than find in books or articles. It is also called primary research because it starts with you. If you plan to conduct primary research, like an experiment, personal interviews, or a survey of people, you will need to devise a basic methodology for your inquiry. A methodology is simply a statement of the procedure you will follow in conducting the research. Depending upon the type of research you are conducting, the methodology could include:

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• A step-by-step sequence of procedures performed for an experiment.
• Questions to be asked in personal interviews.
• The names of people you plan to interview or a profile of the people you plan to interview.
• The questionnaire you will use in the interview.
• A demographic profile that segments people you will survey by such things as age range, gender, educational levels, income bracket, geographic location, or common interests.

A good methodology lends credibility to your research paper. If you are conducting an experiment, for instance, it is important to record the process so that others can later repeat the experiment and get the same results. It also provides important background for your readers and ensures consistency across your results. Whenever you conduct interviews, your readers will be interested in what questions you asked and what the person answered. If you are conducting a survey, it is important to ask everyone in the survey the same questions so that you can compare responses. It is also essential to note whom you surveyed so that you can say something about the attitudes of the particular group.

How to Conduct Interviews

Interviews allow you to conduct primary research and acquire valuable information unavailable in print and online sources. By including quotations from people who have direct knowledge of a particular subject, you add considerable authority and immediacy to your research paper. You can conduct interviews by telephone, by e-mail, or in person.

Often, you can find subjects to interview via the Web sites you visit in your research. Use the contact form at the Web site to extend your invitation. Allow plenty of time. If you want to interview the person who runs the site, he or she may get back to you immediately.However, most often your request will have to be forwarded to an appropriate individual or routed through “channels,” usually the public relations office of the sponsoring organization.

7 Steps in Arranging Interviews

• Identify whom you will interview.
• Locate and contact the person.
• Invite his or her participation.
• Determine how you will interview the person—by phone, in person, or by e-mail.
• Assemble the questions you will ask.
• Forward the questions to your interviewee.
• Request the right to ask follow-up questions.

Who should you interview? Include only respected people in the field. Don’t waste your time with cranks and people with private agendas to further.

Guidelines for Requesting Interviews

• Identify yourself by full name and title.
• Explain your assignment/project.
• Explain your topic.
• State your time frame.
• Offer an idea of how much time the person should allow for the interview.
• Ask for the interview, requesting either someone who is able to speak to your topic or a specific interviewee by name.
• Provide your contact information.
• Finish with a cordial closing as you would in a letter.
• A day or two before the interview, send an e-mail reminder or telephone the interviewee to confirm the time and date.

Interviews can be conducted via  e-mail , by  telephone , or  in person . There are advantages and disadvantages to each method.

E-mail interviews  are convenient; interviewees can respond at their convenience. They also provide you and the interviewee with a written record of what was asked and answered. However, they also place a burden on the interviewee by requiring the person to write out responses that you normally would record in a telephone or face-to-face interview. Be prepared to give considerable thought to questions you prepare in advance. Follow-up questions are difficult in e-mail and you do not want to waste the time of people who have graciously agreed to be interviewed. Be specific and complete in your questions to avoid getting answers that require followup because they do not deliver the information you need. Avoid questions like,”What do you think of social networking?” Instead, be specific with questions that seek detailed information, such as, “What is the most significant trend in social networking that you see emerging among teenagers, and why do you believe it’s the most significant?”

Telephone interviews  are more open-ended and offer you the opportunity to follow up with questions that might occur to you in the course of the conversation. They are not good options, however, if you are excessively shy or if the interviewee is uncomfortable with them. They can also be difficult to arrange if the person maintains a busy schedule. Never insist on a telephone interview; choose the format that is most convenient for the interviewee. Finally, it is useful to record telephone interviews so that you can later review what was said and ensure accuracy on any quotes you use;however,always ask the permission of the interviewee before recording an interview.

Face-to-face interviews , like telephone interviews, are not for the shy and can be difficult to arrange. However, they offer you the opportunity to meet the interviewee. This can be particularly valuable if you are meeting in a setting that is pertinent to your course of inquiry, such as the person’s laboratory or a social setting that pertains to the topic, such as an Internet café if you are discussing social networking, or a troubled housing project if you are discussing the influence of neighborhood environments on high school completion rates, crime rates, or family support networks.Ask the person’s permission to record the interview at the time you make the appointment.

If you are doing a telephone or face-to-face interview, be sure you allow the interviewee to do the talking. Do not interrupt or rush the person through the interview. Many times, interviewees will use the opportunity to promote recent books, writings, or product/service introductions. If they do, let them and then proceed to the questions that are of interest to you. Cutting off an interviewee can set a bad tone for the interview and produce disappointing results.

As you incorporate interviews in your paper, you must accurately and fairly present their views and opinions—even when they do not conform to your own. Be sure to do your research in advance. Read at least one thing your interviewee has written on the topic. Have a good sense in advance of what the person will say about it.

How to Conduct Surveys

Surveys are useful when you want to measure the behavior or attitudes of a fairly large group. On the basis of the responses, you can draw some conclusions. Such generalizations are usually made in quantitative terms: “Fewer than one-third of the respondents said that they favored further governmental funding for schools,” for example.

Fortunately,Web sites and software programs abound to help you design surveys by offering a structure for organizing the survey, prompting you to enter questions, and tabulating the results. Online free polling services include  Zoomerang , and  Polldaddy . The New York Times offers a lesson on poll creation, called “To Free or Not Too Free,” for middle school and high school teachers in its Learning Network at http://learning.blogs.nytimes.com/ .

Surveys should be carefully focused and ask specific questions to minimize ambiguities or bias in the findings. Questions should be crafted and presented to ensure that the data you collect will allow you to make the kinds of determinations you seek. Surveys should follow a structure that informs respondents of the purpose.

Structuring Your Survey

• Give your survey a title.
• State the purpose of the survey.
• Tell respondents where the information will be published
• Include a privacy statement explaining with whom you will share the information and how it will be used.
• Get the respondents’ permission to use the data they provide.
• Describe how the survey will be conducted.
• Set a deadline for when you need the results.
• Tell the respondents how to complete the survey. Be very clear about how they should answer the questions (i.e., whether they should check, circle, or underline the answer or write a response in the blank provided).
• Thank respondents for their time.

You want the respondents to complete the surveys. For that reason, the surveys should not be too long. Aim for 25 to 30 questions. The choices presented to respondents should be straightforward and easy to respond to. Questions can be presented in the following ways:

• Yes or no/true or false
• Multiple choice
• Ratings on a scale, usually 1 to 10
• Ranking in order of importance or preference

Yes-no and true-false questions are the most straightforward. Multiple choice questions can be problematic if the respondent does not identify with the choices given; these should always include options such as “don’t know” or “none of the above” that leave room for exceptions. Rankings allow respondents to express qualitative preferences by assigning a number that reflects their attitudes according to a scale.

Rankings, on the other hand, ask the respondent to place a series of items in order. Comments can be the most revealing as they ask the respondent to state their opinions or describe something; however, they are difficult to tabulate as the results cannot be easily fitted into categories. As you begin designing questions, ask yourself: What, exactly, do I want to determine? Surveys are typically conducted for one of two different reasons. Attitude surveys can be short and simple, focused around a single issue and pose a single question or a short set of questions. For example:

Do you believe that the quality of education would improve if the school year was lengthened to offer more hours for instruction?

Surveys designed to identify trends tend to be much longer than other kinds of surveys. This is to provide a qualitative view of related issues rather than one that is simply based on a yes or no answer. For example:

How would you rate the quality of education in your local school district?

• a. Excellent
• d. Below average

Adding questions that gather demographic data allows you to make distinctions about the individuals being polled and interpret their answers according to group affiliations. Questions asking the person’s age range or income can also be relevant for your research, but such questions should always be respectful of peoples’ privacy. Rather than ask survey respondents to divulge their sex or annual income, for instance, present the respondents with a range and give them the option of not answering, such as:

c. I prefer not to answer

What is your annual income?

a. under $25,000

b. $25,001–$50,000

c. $50,001–$75,000

d. $75,001–$100,000

e. Over $100,000

f. I prefer not to answer

Tabulating Your Survey Results

A great deal of care should be taken to correctly tabulate results.This can be a challenging task if you have not collected data through an online site or from a form that provides automatic analysis. Researchers who expect to review and tabulate the data themselves would be well advised to work with a small group of respondents (no more than 20) to keep the task manageable. The American Statistical Association (ASA) and the American Psychological Association (APA) publish excellent guidelines on how to conduct surveys and tabulate the results. The ASA’s publication What Is a Survey? can be downloaded from  https://www.whatisasurvey.info/download.htm . The APA offers numerous articles on conducting surveys at its Web site  http://www.apa.org/ .

In addition, many topics have been extensively discussed by experts on respected television news programs and documentaries. It is often possible to write to the television station and obtain printed transcripts of the programs. You might also be able to videotape the programs or borrow copies of the programs that have already been recorded.

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Research Process

• Introduction
• Topic Selection

Originality

• Information Needs
• Evaluating Sources
• Getting Sources
• Getting Organized
• Understanding Your Sources
• Putting it into Words
• Bringing it Together

One way to think about originality in research is to think about how many times someone else has analyzed information. These can be described as primary, secondary, and tertiary information, and often instructors want you to use primary sources so they can see what you have to say about the information you find. The gallery provides information about and examples of primary, secondary, and tertiary resources:

First-hand accounts or documents related to the topic from people who had a direct connection with it, such as speeches, diaries, letters, interviews, photographs, original research, and dataset. They can be found in archives, historic newspaper databases, scholarly journal articles, image databases, and data resources.

Example: An original handwritten poem by Frederick Douglass, held in the Xavier archives.

Resources that add some interpretation, analysis, or provide context for primary sources. Books, articles, and documentaries that are about a topic are most likely secondary sources. They can be found in print or electronic books, database articles that are not based on original research, and documentaries.

Example: The "About this Collection" description and contextualization of the poem "Liberty" by Frederick Douglass

Resources used to find primary or secondary sources or give general information rather than analysis. It can be found in reference materials such as encyclopedias, dictionaries, background databases and some websites.

Example: Frederick Douglass page on allpoetry.com, which shares basic facts of his life and the text of the poem.

More about Original Research

As you participate in the scholarly conversation, it is important to understand what kinds of original research are being done by academics and how that fits with the research you are doing. Most original research is done as either qualitative or quantitative:

From Research to Publication: The Life of a Journal Article

1. Conduct Original Research

Original research is done when the researchers are responsible for the entire process of coming up with a hypothesis, a means for testing the hypothesis, defending their hypothesis based on prior research, and gathering and analyzing the data, and explaining their findings. This is often done by scientists, doctors, college professors, or people working within a field of study.

Researchers must present their findings in a very thorough manner so that other researchers could replicate their work and reach the same conclusions. Their writing must follow specific style rules and writing conventions that match the preference of the publication, or journal , where they will submit their work.

3. Submit to Editor

The journal editor's initial job it is it make sure that the submission matches the subject matter of the journal and is written according to the style rules for their publication. The editor then identifies other people who are experts on the same content the article is about, or  peers , and sends the article for them to read.

4. Peer Review

The peer group of experts receives the article and reviews the content to ensure that the science being used to do the research is reasonable, the data was conducted accurately, analyzed in a way that is free of errors, and the authors have reached a conclusion that is supported by their research. They then respond to the editor letting them know whether they feel the article is ready for publication.

5. Editor Decisions

The editor reviews the feedback of the peer group and decides if the research article should be accepted for publication, rejected, or sent back to the authors for revisions based on peer feedback. 

6. Published

If the editor accepts the article for publication, it is now available to be published in that journal. Depending on the frequency, method, and business model of the publication, it can take a year or more for the article to become available for others to read.

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• J Med Libr Assoc
• v.103(2); 2015 Apr

How to write an original research paper (and get it published)

The purpose of the Journal of the Medical Library Association (JMLA) is more than just archiving data from librarian research. Our goal is to present research findings to end users in the most useful way. The “Knowledge Transfer” model, in its simplest form, has three components: creating the knowledge (doing the research), translating and transferring it to the user, and incorporating the knowledge into use. The JMLA is in the middle part, transferring and translating to the user. We, the JMLA, must obtain the information and knowledge from researchers and then work with them to present it in the most useable form. That means the information must be in a standard acceptable format and be easily readable.

There is a standard, preferred way to write an original research paper. For format, we follow the IMRAD structure. The acronym, IMRAD, stands for I ntroduction, M ethods, R esults A nd D iscussion. IMRAD has dominated academic, scientific, and public health journals since the second half of the twentieth century. It is recommended in the “Uniform Requirements for Manuscripts Submitted to Biomedical Journals” [ 1 ]. The IMRAD structure helps to eliminate unnecessary detail and allows relevant information to be presented clearly in a logical sequence [ 2 , 3 ].

Here are descriptions of the IMRAD sections, along with our comments and suggestions. If you use this guide for submission to another journal, be sure to check the publisher's prescribed formats.

The Introduction sets the stage for your presentation. It has three parts: what is known, what is unknown, and what your burning question, hypothesis, or aim is. Keep this section short, and write for a general audience (clear, concise, and as nontechnical as you can be). How would you explain to a distant colleague why and how you did the study? Take your readers through the three steps ending with your specific question. Emphasize how your study fills in the gaps (the unknown), and explicitly state your research question. Do not answer the research question. Remember to leave details, descriptions, speculations, and criticisms of other studies for the Discussion .

The Methods section gives a clear overview of what you did. Give enough information that your readers can evaluate the persuasiveness of your study. Describe the steps you took, as in a recipe, but be wary of too much detail. If you are doing qualitative research, explain how you picked your subjects to be representative.

You may want to break it into smaller sections with subheadings, for example, context: when, where, authority or approval, sample selection, data collection (how), follow-up, method of analysis. Cite a reference for commonly used methods or previously used methods rather than explaining all the details. Flow diagrams and tables can simplify explanations of methods.

You may use first person voice when describing your methods.

The Results section summarizes what the data show. Point out relationships, and describe trends. Avoid simply repeating the numbers that are already available in the tables and figures. Data should be restricted to tables as much as possible. Be the friendly narrator, and summarize the tables; do not write the data again in the text. For example, if you had a demographic table with a row of ages, and age was not significantly different among groups, your text could say, “The median age of all subjects was 47 years. There was no significant difference between groups (Table).” This is preferable to, “The mean age of group 1 was 48.6 (7.5) years and group 2 was 46.3 (5.8) years, a nonsignificant difference.”

Break the Results section into subsections, with headings if needed. Complement the information that is already in the tables and figures. And remember to repeat and highlight in the text only the most important numbers. Use the active voice in the Results section, and make it lively. Information about what you did belongs in the Methods section, not here. And reserve comments on the meaning of your results for the Discussion section.

Other tips to help you with the Results section:

• ▪ If you need to cite the number in the text (not just in the table), and the total in the group is less than 50, do not include percentage. Write “7 of 34,” not “7 (21%).”
• ▪ Do not forget, if you have multiple comparisons, you probably need adjustment. Ask your statistician if you are not sure.

The Discussion section gives you the most freedom. Most authors begin with a brief reiteration of what they did. Every author should restate the key findings and answer the question noted in the Introduction . Focus on what your data prove, not what you hoped they would prove. Start with “We found that…” (or something similar), and explain what the data mean. Anticipate your readers' questions, and explain why your results are of interest.

Then compare your results with other people's results. This is where that literature review you did comes in handy. Discuss how your findings support or challenge other studies.

You do not need every article from your literature review listed in your paper or reference list, unless you are writing a narrative review or systematic review. Your manuscript is not intended to be an exhaustive review of the topic. Do not provide a long review of the literature—discuss only previous work that is directly pertinent to your findings. Contrary to some beliefs, having a long list in the References section does not mean the paper is more scholarly; it does suggest the author is trying to look scholarly. (If your article is a systematic review, the citation list might be long.)

Do not overreach your results. Finding a perceived knowledge need, for example, does not necessarily mean that library colleges must immediately overhaul their curricula and that it will improve health care and save lives and money (unless your data show that, in which case give us a chance to publish it!). You can say “has the potential to,” though.

Always note limitations that matter, not generic limitations.

Point out unanswered questions and future directions. Give the big-picture implications of your findings, and tell your readers why they should care. End with the main findings of your study, and do not travel too far from your data. Remember to give a final take-home message along with implications.

Notice that this format does not include a separate Conclusion section. The conclusion is built into the Discussion . For example, here is the last paragraph of the Discussion section in a recent NEJM article:

In conclusion, our trial did not show the hypothesized benefit [of the intervention] in patients…who were at high risk for complications.

However, a separate Conclusion section is usually appropriate for abstracts. Systematic reviews should have an Interpretation section.

Other parts of your research paper independent of IMRAD include:

Tables and figures are the foundation for your story. They are the story. Editors, reviewers, and readers usually look at titles, abstracts, and tables and figures first. Figures and tables should stand alone and tell a complete story. Your readers should not need to refer back to the main text.

Abstracts can be free-form or structured with subheadings. Always follow the format indicated by the publisher; the JMLA uses structured abstracts for research articles. The main parts of an abstract may include introduction (background, question or hypothesis), methods, results, conclusions, and implications. So begin your abstract with the background of your study, followed by the question asked. Next, give a quick summary of the methods used in your study. Key results come next with limited raw data if any, followed by the conclusion, which answers the questions asked (the take-home message).

• ▪ Recommended order for writing a manuscript is first to start with your tables and figures. They tell your story. You can write your sections in any order. Many recommend writing your Result s, followed by Methods, Introduction, Discussion , and Abstract.
• ▪ We suggest authors read their manuscripts out loud to a group of librarians. Look for evidence of MEGO, “My Eyes Glaze Over” (attributed to Washington Post publisher Ben Bradlee and others). Modify as necessary.
• ▪ Every single paragraph should be lucid.
• ▪ Every paragraph should answer your readers' question, “Why are you telling me this?”

The JMLA welcomes all sizes of research manuscripts: definitive studies, preliminary studies, critical descriptive studies, and test-of-concept studies. We welcome brief reports and research letters. But the JMLA is more than a research journal. We also welcome case studies, commentaries, letters to the editor about articles, and subject reviews.

Originality and critical analysis

A classic postgraduate research project presents aims/hypotheses of a particular study, and then demonstrates arguments that clearly addresses these aims/hypotheses. Postgraduate research projects must demonstrate a degree of originality and analysis. This can cause anxiety as it is difficult to determine what constitutes original work. For this reason, it is best to address the concept of originality when you are choosing your research topic.

Originality in an academic context.

Originality does not mean re-inventing the wheel. New inventions or discoveries come very rarely in reality. The idea is to ensure you are not simply repeating what another researcher has done before. Producing an original piece of work simply means moving an idea forward by an incremental amount for the next generation to continue developing.

Critical analysis

At postgraduate level it is important to demonstrate an ability to critically analyse your data/evidence. You need to look beyond the raw data and ask yourself ‘what does this mean?’

So, analysis can mean:

You should be able to demonstrate critical thinking and analysis. Do not take anything you see or hear for granted, put it all into context, and ask yourself whether the whole picture makes sense. If there are things that don’t seem to fit, ask yourself why.

Your finished dissertation, thesis or presentation should be predominantly your own work. While it is important to put your work into the context of previous studies, examiners are interested in what you have done and what you are thinking, and therefore the bulk of your work should be demonstrably identifiable as your contribution to the subject.

See our webpage for further information on Critical thinking 

The next section describes the strategies and models used in research.

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A publication of the harvard college writing program.

Harvard Guide to Using Sources 

• The Honor Code

Writing "Original" Papers

Some of your writing assignments at Harvard will explicitly ask you to present an "original" thesis, claim, or idea. But even when the word "original" isn't mentioned, you should assume that your professor expects you to develop a thesis that is the product of your own thinking and not something drawn directly from a source. Occasionally an assignment will require only a summary of your reading, particularly if the instructor wants to make sure you have understood a particularly complex concept; however, some assignments may be worded in a way that leaves expectations ambiguous (you may be asked, for example, to "discuss" or "consider" a source), and you may think you are only expected to summarize when, in fact, you are expected to make an argument. When in doubt about whether you are supposed to make an argument in your paper, always check with your instructor to make sure you understand what you're expected to do.

The expectation that you will say something original in every college paper may seem daunting. After all, how can you, an undergraduate who has been studying a particular subject for as little as one semester, know enough to make an original contribution to a field that your professor may have spent a career studying? Indeed, it would be impossible for you to come up with an idea for every paper you write that no one has ever thought of before, and your instructors realize this. When they ask you to come up with an original idea, they may be signaling different expectations, depending on the context of the assignment. Below, you'll find a general framework for thinking about originality in different situations you will encounter in college.

Writing Situation #1: Short Non-Research Papers

In the context of certain assignments, it's enough to come up with a thesis that's original to you—a thesis that you arrived at after thinking about the material you read, rather than an idea you encountered in one of the assigned sources. This will be true for the papers you write in Expos, as well as for many of the short papers you write in your Gen Ed and concentration courses. For these papers, your instructor does not expect you to come up with an idea that no one else has ever written about. Instead, your instructor is most interested in your thought process, your analytical skills, and the way you explain why you think what you think. But why, you may be wondering, would anyone bother writing a paper that presents an idea that other scholars have written about already?

Here's the short answer to that question: There is real value in discovering an idea for yourself, selecting the best evidence to support it, and taking the necessary steps to argue for it. Taking these steps helps you learn both what you think about a topic or issue and how to think through a problem or set of problems. This kind of thinking is necessary preparation for the longer projects you'll do later in your college career when you will be expected to say something truly original. It's impossible to tackle those projects—from a senior thesis to original lab research—if you haven't had the experience of arriving at an idea, fleshing out an argument, and presenting it to an audience. This preparation will serve you well as your college coursework becomes more specialized, and it will also benefit you when you leave college. Whatever field you go into, you'll find yourself in situations where your analysis of a particular problem—and your use of sources to solve that problem—will be crucial to your success.

While the specifics of the assignments for short papers will vary, remember that whenever you're asked to make a claim, you're expected to do your own thinking. In other words, writing a paper about a claim that has been worked over in class, in section, or in your readings will not leave you room to do much thinking of your own. Nor will writing a paper about a claim that will strike your readers as obvious, simple, and unarguable. If you are interested in an idea that has come up in class, or one that seems obvious, you should work on extending or complicating this idea, or coming up with a counterargument that changes the way the idea should be considered. Also, keep in mind that when your instructors tell you not to consult outside sources, they are often doing so precisely to encourage your original thinking, and you should follow their instructions. When an assignment specifies that you avoid outside sources, you should generally take this to mean that you should not do any outside reading in preparation for the assignment.

Writing Situation #2: Short Research Papers and Term Papers

When you are assigned a research paper or term paper for a course, you will often be asked to write 10-20 pages in which you respond to sources you identify and locate yourself . As with the shorter papers you write for your courses, you will generally not be expected to come up with an idea that has never been considered before (although your instructors will certainly be pleased if you do). So how will you know if your idea is original enough?

The key to answering this question is to think carefully about the context of the course and to decide what's reasonable for you to do given the scope of the assignment. For example, if you've been asked to find five sources of your own, your paper will not be original enough if your argument simply echoes one of these sources, or if it echoes a source that was assigned in class. On the other hand, if you locate three sources, each of which offers different answers to the same question, your paper will be original if you can make your own argument for which answer makes the most sense and why.

Your argument will not, however, be original enough if you make the same argument as one of the sources without acknowledging why that source makes the strongest argument. For example, if you were writing about climate change and you were asked to read and consider an argument for investing in nuclear energy and an argument against investing in nuclear energy, you might agree with one of those arguments and present your argument for why it is the stronger idea. Or you might decide that both arguments fall short. You might decide that you support or oppose investing in nuclear energy for reasons other than those offered in the source’s argument. Or you might decide that the argument opposing nuclear energy misses a key factor. The result of doing your own thinking about the topic would be a paper that does not simply restate the position of one of your sources but, rather, uses those sources to inform your own thinking. And the process of writing that paper would have gotten you closer to figuring out what you think about the topic. When you are doing research, it's always a good idea to check in with your instructor to make sure that you are not overlooking important work in that field and that the sources you are choosing are significant and appropriate for your project.

Writing Situation #3: The Junior Tutorial and the Senior Thesis

When you write a substantial piece of work that takes a semester or more (like a junior tutorial paper or a senior thesis), the expectations for originality are different because of the length of the essay you'll write and because of your level of expertise in the field. As you gain experience in your concentration, your knowledge of the major ideas in your chosen field will expand, you will develop your ability to ask more rigorous questions in that field, and you will be able to answer those questions in ways that are original not just to you but to your readers. At this point in your college career, you'll have had the opportunity to learn who the major thinkers are in your field and how to identify the important literature on what research has taken place on your topic. You'll be able to find the most important current scholarship on a topic or the most recent findings related to your research question. Your expertise, along with the time you'll have to devote to the project, means that you will be well-equipped to say something original about your topic.

Even when you write these longer papers, it's still important to understand what it means to say something original. Academic work is very specialized, and scholars build theories and ideas based on the knowledge and ideas that they have studied. In practical terms, this means that ideas evolve slowly, and every original idea doesn't have to be E=mc2 or Kierkegaard's "leap of faith." While there's nothing wrong with hoping to discover a new element to add to the periodic table or trying to figure out the true identity of Shakespeare, it's more likely that your ideas will be original in any of the following ways.

You might discover, in your study of a particular topic, that no one has considered a question or problem that interests you. Or you might bring new information or a new perspective to a question that others have asked. For example, you might look at newly released government documents to consider a question about how the Reagan administration shaped economic policies. While the question may have been asked before, the newly available data will allow you to provide a fresh, original perspective. Similarly, while many people have written about Shakespeare’s plays, you might find that comparing a new production to a more traditional version would bring you a fresh perspective on the play.

Sometimes collecting and analyzing your own data will provide an original take on a topic. For example, if you were writing a senior thesis in a lab science or social science concentration, you might collect and analyze your own data in pursuit of an answer to a question that other scholars have attempted to answer before with different types of data. In psychology, for example, you might conduct an experiment under the supervision of a professor and then analyze your data. In a sociology or anthropology course, you might conduct a series of interviews and analyze them in order to answer a question in a new way.

As appealing as it might seem to discover an entirely new idea, it's just as valuable to add a new step or a new way of thinking to an idea that someone else has already presented. It's also valuable—and original—to consider ideas in relation to each other that have not been considered or connected to each other in this way before.

Whether you're working on a short assignment or a semester-long project, remember that even in the context of all the thinking that has come before yours, you are always capable of bringing your own unique point of view to a paper. In fact, you're doing your own thinking all the time, long before you start writing—in class discussion, in the dining hall, and in your instructor's office hours. When you bring sources into the equation, you're able to go beyond your gut reactions and feelings ("capitalism is good" or “capitalism is bad”) to develop more nuanced ideas ("capitalism does a better job of creating incentives for innovation than other systems" or "a capitalist society cannot protect the most vulnerable"). Sources also introduce you to competing arguments and interpretations and help to lay the groundwork for your own thinking. When you read what has already been written on a particular topic, or when you analyze data that has already been produced in addition to new data, you become more qualified to contribute to the conversation.

Many students tackling college-level writing for the first time find the expectations of college writing new and difficult. There are resources to help you as you embark on your writing assignments at Harvard, and you should feel free to make use of them. Writing Center tutors , Departmental Writing Fellows , and House tutors are all excellent resources. The Harvard Writing Project publishes a number of guides to writing in different fields, and the Writing Center offers general writing resources in addition to individual conferences.

Before you can use sources effectively, you need to know how to locate them, how to know if they are reliable, and how to distinguish clearly between the ideas in a source and your own ideas. The information on this site provides an introduction to the research process, including how and where to find sources , how to decide if a source is reliable and useful , how to use sources accurately and effectively in your papers both to strengthen your own thinking and writing and to avoid plagiarism, and finally, how to integrate source material into your writing and how to cite sources responsibly .

What Does It Mean to Be Controversial?

Most of your college writing assignments will instruct you to take a position or to make an argument. While it's important to learn how to weigh the evidence and draw conclusions that may be different from those of other scholars, it's also important to remember that in academic writing, the most controversial position isn't necessarily the strongest one to take. It might be tempting to manufacture a controversial argument by over-generalizing or caricaturing the ideas you oppose, but ultimately this kind of argument will be neither convincing nor interesting. Any argument you make should be the result of careful thought, and it should follow from a fair reading of the evidence available to you.

Consider, for example, an essay that Aishani Aatresh wrote for her ESPP class, Technology, Environment, and Society. In the paper, Aatresh tries to answer the question of why hydrogen-powered vehicles have not been as successful as electric vehicles in the United States. While it would have sounded most controversial to argue something like “hydrogen-powered vehicles will always be too dangerous because hydrogen is so flammable,” or “hydrogen-powered vehicles are inferior to electric vehicles in every way,” Aatresh’s research suggested that this type of statement would oversimplify a complex situation. She ended up with a thesis that is still controversial in the sense that readers may disagree with it, but one that does not depend on over-simplifying the issues at stake.

Here is the thesis statement she drafted:

Instead of being a contest of modes of sustainability or “superior” technology, FCEVs largely fit into familiar modes of movement while EVs represent elite, material, and innovative “progress” and thus are differentially situated in American society based on how these visions relate to the idea of independence.

With this thesis statement, Aatresh was able to use the evidence that she uncovered to take a position on a controversial topic (alternative fuels) that was both nuanced and arguable.

• What Are You Supposed to Do with Sources?
• Writing "Original" Papers
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What does originality in research mean? A student's perspective

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• 1 University of South Wales Cardiff, UK.
• PMID: 25059081
• DOI: 10.7748/nr.21.6.8.e1254

Aim: To provide a student's perspective of what it means to be original when undertaking a PhD.

Background: A review of the literature related to the concept of originality in doctoral research highlights the subjective nature of the concept in academia. Although there is much literature that explores the issues concerning examiners' views of originality, there is little on students' perspectives.

Review methods: A snowballing technique was used, where a recent article was read, and the references cited were then explored. Given the time constraints, the author recognises that the literature review was not as extensive as a systematic literature review.

Discussion: It is important for students to be clear about what is required to achieve a PhD. However, the vagaries associated with the formal assessment of the doctoral thesis and subsequent performance at viva can cause considerable uncertainty and anxiety for students.

Conclusion: Originality in the PhD is a subjective concept and is not the only consideration for examiners. Of comparable importance is the assessment of the student's ability to demonstrate independence of thought and increasing maturity so they can become independent researchers.

Implications for research/practice: This article expresses a different perspective on what is meant when undertaking a PhD in terms of originality in the doctoral thesis. It is intended to help guide and reassure current and potential PhD students.

Keywords: PhD; Student perspectives; doctoral research; originality.

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Original Research Articles

Definition : An original research article communicates the research question, methods, results, and conclusions of a research study or experiment conducted by the author(s). These articles present original research data or findings generated through the course of the authors' study and an analysis of that data or information.

Published in Journals : Origingal research articles are published in scientific journals, also called scholarly or academic journals. These can be published in print and/or online. Journals are serial publications, meaning they publish volumes and issues on a schedule continually over time, similar to a magazine but for a scholarly audience. You can access journals through many of the library's databases. A list of recommended databases to use to search for original articles on biology subjects can be found through this link , accessible from the database "subject" dropdown on the library homepage.

Peer Reviewed : Prior to being published, original research articles undergo a process called peer review in an effort to ensure that published articles are based on sound research that adheres to established standards in the discipline. This means that after an article is first submitted to a journal, it is reviewed by other scientists who are experts in the article's subject area. These individuals review the article and provide unbiased feedback about the soundness of the background information, research methods, analysis, conclusions, logic, and reasoning of any conclusions; the author needs to incorporate and/or respond to recommended edits before an article will be published. Though it isn't perfect, peer review is the best quality control mechanism that scholars currently have in place to validate the quality of published research.

Peer reviewed articles will often be published with "Received", "Accepted", and "Published" dates, which indicates the timeline of the peer review process.

Structure : Traditionally, an original research article follows a standardized structure known by the acronym IMRD, which stands for Introduction, Methods, Results, & Discussion. Further information about the IMRD structure is available on the  Reading Original Research Articles  tab of this guide.

Other types of journal articles

Review Articles (usually peer reviewed) : Summarize and synthesize the current published literature on a certain topic. They do not involve original experiments or report new findings. The scope of a review article may be broad or narrow, depending on the publication record. Original research articles do incorporate literature review components, but a review article covers  only  review content.

Non Peer Reviewed Articles in Journals : Many journals publish the types of articles where peer review is not required. These differ by publication but may include research notes (brief reports of new research findings); responses to other articles; letters, commentaries, or opinion pieces; book reviews; and news. These articles are often more concise and will typically have a shorter reference list or no reference list at all. Many journals will indicate what genre these articles fall into on the article itself by using a label.

Why is Published Original Research Important?

Current information : Typical publication turnaround varies, but can be as quick as ~3 months.

Replicable : The studies published in original research articles contain enough methodological detail to be replicated so research can be verified (though this is a topic of recent debate ).

Contains Raw Data : The raw original research data, along with information about experimental conditions, allows for reuse of results for your own research or analysis.

Shows Logic : Using the provided data and methods, you can evaluate the logic of the authors' conclusions.

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Many original research articles are not labeled as original research articles.  Original research articles include a research question or hypothesis.  They usually contain most of the following sections: methods, results, discussion, conclusion and references.  An original research article is written by the person or people that conducted the experiment or observations.  Original research articles are considered empirical or primary sources and present an original study.

Articles that look at multiple studies are not considered original research articles.  Search library databases using keywords like “study or “case study” to increase your chances of locating original research articles. 

For information on how to find an original research article that is not meta-analysis, not meta-synthesis and not mixed method, go to  https://westcoastuniversitylibrary.libanswers.com/research/faq/291851 .

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Novelty in Research: What It Is and How to Know Your Work is Original

One of the key prerequisites for researcher success, irrespective of their field of study, is identifying the novelty in research. They hope to make new discoveries that build on the work of others and produce fresh perspectives on existing knowledge in their field. To achieve this, researchers invest considerable time and effort in reading relevant literature, conducting experiments, and staying up to date on the latest developments in their own and related fields. Most journals seek to publish research that is novel, significant, and interesting to its readers. Establishing novelty in research is also critical when applying for funding, which makes it essential to prove this early in the research process. But what is meant by novelty in research and how can one judge the novelty of their research study? This article will help you answer these questions in the simplest manner.

Table of Contents

What is meant by novelty in research?

The word ‘novelty’ comes from the Latin word ‘novus,’ which simply means new. Apart from new, the term is also associated with things, ideas or products for instance, that are original or unusual. Novelty in research refers to the introduction of a new idea or a unique perspective that adds to the existing knowledge in a particular field of study. It involves bringing something fresh and original to the table that has not been done before or exploring an existing topic in a new and innovative way. Novelty in research expands the boundaries of a particular research discipline and provides new insights into previously unexplored areas. It is also one of the first things academic journals look for when evaluating a manuscript submitted for publishing. This makes it essential for researchers to ensure novelty in research in order to create new knowledge and make a significant contribution to their field of study.

How can you ensure novelty in research?

Academics are often immersed in their research and so focused on excellence that it can be difficult to examine your work as an author and judge its novelty in research objectively. But this challenge can be overcome with time and practice by adding research reading to your daily schedule. Assessing novelty in research means evaluating how new and original the ideas or findings presented in a study are, in comparison to existing knowledge in the field. Here are some ways to judge the novelty of research:

• Conduct a literature review: A literature review is an essential component of any research project, and it helps to establish the context for the study by identifying what is already known about the topic. By reviewing the existing literature, researchers can identify gaps in the knowledge and formulate new questions or hypotheses to investigate, ensuring novelty in research.
• Compare with previous studies: Researchers can assess the novelty of their work by comparing their findings to those of previous studies in the same or related fields. If the results differ significantly from what has been previously reported, it can be an indication that the study is novel and potentially significant.
• Read target journal publications: Subscribe to your target journal and other reputed journals in your field of study and keep up with the articles it publishes. Since most high-impact journals typically ensure novelty in research when publishing papers, this will help you keep track of the developments and progress being made in your subject area.
• Assess contribution to the field: One way to assess novelty in research is to evaluate how much it contributes to your specific field. Research that makes a significant contribution to advancing knowledge or addressing important questions is often considered more valuable than those that simply replicate elements from previously published research.
• Consider an alternative methodology: Even if the topic or area of study has been studied, one can bring in novelty in research by exploring various methodologies or by tweaking the research question to provide new insights and perspectives. Researchers can highlight aspects of the study that have not been done before, introduce these in the proposed research design, and illuminate how this will ensure novelty in research.
• Get support from your peers: Engage with your mentors/supervisors, professors, peers, and other experts in the field to get their feedback on introducing novelties in their research. It’s a good idea to join and actively participate in scientific research and scholarly groups or networks where users provide updates on new technological innovations and development.
• Make research reading a habit: An overwhelming number of research papers are published every day, making it difficult for researchers to keep up with new, relevant developments in the world of research. This is where online tools for researchers can help you simplify this process while saving on time and effort. Smart AI-driven apps like R Discovery can understand your areas of interest and curate a reading feed with personalized article recommendation, alerts on newly published articles, summaries to help you quickly evaluate articles, and many other useful features for researchers. By taking the search out of research, it gives you back time that you can then spend to stay updated and ensure novelty in research.

In an ideal world, all research done would be completely original. Yet with rapid advances in technology and research, there are bound to be overlaps with previously published papers. The key here is to find a new way of looking at old problems, trying new methodologies and angles, and coming up with interesting insights that can add to or alter current knowledge in your field of research. Smart online tools have made it easier to read and keep up with the latest in research and we’re sure the tips above will help you better assess your project and judge the novelty of your research study.

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

Try R Discovery Prime FREE for 1 week or upgrade at just US$72 a year to access premium features that let you listen to research on the go, read in your language, collaborate with peers, auto sync with reference managers, and much more. Choose a simpler, smarter way to find and read research – Download the app and start your free 7-day trial today !  

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When life mirrors research: What a fall on the ice taught me about being Black and in pain

By Staja “Star” Booker Aug. 7, 2024

A s I hurried to an important meeting about my Ph.D. dissertation one day in 2015, I slipped and fell on Iowa’s formidable winter ice. I quickly jumped up to prevent anyone from seeing me on the ground and got into my car. The immediate, excruciating pain told me that something really bad had happened.

As I drove to my meeting in tears, I called my sister. “I just busted my butt,” I told her, not knowing then I had actually fractured my sacrum. I thought that maybe over the next few days the pain would get better.

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It didn’t. A few days later I asked a friend to drive me to an urgent care clinic. The clinicians there sent me to the local emergency department.

Part of me wanted to find out why I was in such pain and get treated to relieve it. Another part of me — my research centers on deconstructing the experience of chronic pain in Black older adults and trying to understand and interpret the intersections of structural racism, ageism, sexism , ableism, and economic classism — wanted to see what would transpire if I, as a young Black woman, didn’t disclose that I was a registered nurse or a Ph.D. student studying disparities in chronic pain experiences. I chose the latter.

Related: Treating chronic pain requires much more than medications

Long story short: None of the clinicians who saw me in the emergency department asked me to rate my pain. None offered me any treatment — not even a Tylenol or a pillow for positioning — during my nearly four hours in the emergency department observation room. And no one checked on me to determine if my pain was better or worse.

In some disbelief, I asked myself, “Is this what Black people endure in clinical settings?” I sat there realizing how much this experience reflected what my research had been telling me. Like so many adults I had interviewed, I was now left to determine how I would move forward from — or with — this chronic pain.

The U.S. health care system has not been effective in acknowledging and treating pain, especially among Black and other minoritized people. Chronic pain and its unequal treatment need to be acknowledged as a public health problem, a health disparities priority, a moral imperative, a civil rights infringement, and a human rights violation.

What many experts fail to understand — including myself for many years — is that using a disparities-only lens focusing on the deficits, defeats, and demoralization of people living with pain isn’t the most effective way forward. As a Black nurse researcher, I believe that pain management of the future must center justice as its core operating principle and adopt two synchronized actions: creating systems of equity and delivering pain-affirming care.

Driving forces of the future of equitable pain care

Black adults, in particular, have had to contend with identity-based bias when seeking pain care, including implicit bias from providers primarily based on their race, gender, age, and cultural and behavioral expression.

Related: High physician empathy could offer patients with lower back pain lasting benefits, study shows

The Advil Pain Equity Project’s first campaign, Believe My Pain , launched in partnership with Morehouse School of Medicine and BLKHLTH , focuses on illuminating the issues of pain disparities, inequities, and injustices in Black communities and championing equitable and accessible pain relief solutions. An equitable system of pain management affirms the individual’s experiences of living with pain regardless of identity, confirms the cause of pain (when possible), and uses unbiased, evidence-based treatments in a timely manner.

Pain-affirming care is an empathy-driven and personalized approach that integrates evidence-based care, principles of equity and intersectionality (which means recognizing that an individual’s overlapping identities affect life and social experiences as a result of either oppression or privilege), and population-health measures to ensure that every person living with pain is taken seriously, is treated without judgment, and receives the best and most just care consistently. This must include empowering adults with pain with the skills, confidence, and resources to access all appropriate treatments.

Early in my journey with chronic pain, even I as a pain management expert had to advocate for a prescription for a muscle relaxant and later for physical therapy to try transcutaneous electrical nerve stimulation.

Top recommendations to get us there

Health care providers, researchers, and the public must shift their belief away from drug seeking to comfort seeking, knowing that people seek medications because they need and desperately want relief from pain. I am grateful that over time my pain has decreased significantly, and I am able to identify the triggers and manage those well. But what about people who look like me and continue to struggle with chronic pain? What should the future be for them?

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It will take a collective effort from health care systems, research experts, funding agencies, insurance payers, policy makers, and community organizations to transform the future of pain of management. Avenues for creating equity and pain-affirming care include:

Community engagement equity: Expand opportunities for underrepresented communities to contribute to pain care reform, create chronic pain support groups in under-resourced and underserved communities, and offer education and free screenings for conditions known to cause chronic pain.

Resource equity: Develop community-based pain resources centers (not to be confused with pain management clinics) to help with navigation to health care resources, pain medication affordability, pain self-management education, and the like.

Pharmacoequity: Expand access to pharmacogenetic testing to determine the safest and most effective analgesic medications, ensure fair opioid prescription, establish monitoring and regulatory compliance policies that do not criminally target communities of color, and reduce prescription cost gouging and pharmacy deserts.

Tech equity: Widen responsible use of artificial intelligence by clinicians and researchers to predict patients at high risk for pain, undertreatment, or poor pain control, along with expanded access to smart technologies and devices for pain treatment and self-management.

As I learned the hard way, everyone is just an injury or medical emergency away from chronic pain. Pain management of the future is not five or 10 years away. It should start today by upholding the civil rights of racialized populations, thus creating healthier lives and communities with less pain. Failure to do so will serve as the dominant modus operandi keeping a nation riddled with chronic pain and adverse economic and social impacts for generations to come. In the words of Malcolm X, “We want justice by any means necessary. We want equality by any means necessary.”

Staja “Star” Booker, Ph.D., R.N., is an assistant professor of nursing at the University of Florida College of Nursing .

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White men who have been mistreated at work are more likely to notice and report harassment − new research

Associate Professor of Sociology, University of Michigan

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Erin A. Cech receives funding from the National Science Foundation.

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White men who have personally experienced mistreatment at work, such as bullying, are more likely to realize that their organization does not always operate fairly. And that makes them more likely to recognize and report race and gender bias against their co-workers, I found in a recent study.

As a sociologist who researches workplace inequality , I wondered whether the way white men in the U.S. are treated at work might be related to whether they recognize sexist and racist incidents that harm their colleagues.

To find out, I analyzed data from over 11,000 federal employees , including 5,011 white men employed by 28 government agencies, collected for a survey that measures the government’s progress toward eliminating personnel policy violations.

I found that although white men are mistreated less often than women and people of color, about 1 in 3 of them experienced some instance of bullying, intimidation or other form of harassment in the two years prior to the study. In comparison, 44% of white women, 49% of women of color and 35% of men of color experienced some form of harassment.

It turned out that white men who were targets of harassment were 70% more likely than other white men in their workplaces to recognize gender bias among their colleagues. They were 58% more likely to recognize bias against their racial or ethnic minority colleagues. They were also nearly twice as likely to have reported race and gender bias to their supervisors and colleagues when they witnessed it.

Why were white men who had been harassed more sensitive to bias in their workplace?

I found that they tended to be more skeptical that their organization worked fairly. For example, only one-third of white men who experienced harassment agreed with this statement: “Recognition and rewards are based on performance in my organization.” In contrast, two-thirds of white men who had not experienced harassment agreed with it. The skepticism among those who had experienced mistreatment increased their tendency to recognize and report bias against their colleagues.

Importantly, these patterns existed whether white men thought they were the target of harassment because of a social characteristic – such as their age, religion or sexual identity – or because of more idiosyncratic personality conflicts.

Why it matters

Many white men believe that their workplace operates according to merit : that people who are better at their jobs get promoted, while those who aren’t get demoted or fired. Yet race and gender bias are startlingly common in U.S. workplaces: More than 4 in 10 women have experienced gender discrimination, and 41% of Black workers have experienced racial discrimination at some point in their careers.

Rooting out gender and racial bias from the workplace requires the support of white men . Yet white men tend to stand up or speak out only to the extent they recognize the existence of bias in their workplaces and are willing to do something about it.

In recent years, there have been many efforts to identify the best strategies for reducing prejudice in the workplace. My findings suggest that encouraging white men to reflect on their own negative experiences at work may make them more open to acknowledging the mistreatment of colleagues.

What still isn’t known

I believe that it’s important for scholars to look into why white men who experience harassment become better allies when their colleagues who are women or people of color are mistreated on the job. It’s also worthwhile for researchers to explore whether patterns like the one I identified exist for other groups and in other contexts – including in other countries.

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Dow plunges more than 1,000 points amid fears of U.S. economic slowdown

By Aimee Picchi

Edited By Anne Marie Lee

Updated on: August 5, 2024 / 9:22 PM EDT / CBS News

Stocks in the U.S. plunged for a third consecutive trading day, with the Dow Jones Industrial Average tumbling more than 1,000 points amid growing fears of an economic downturn sparked by a slowdown in hiring and consumer spending. 

The S&P 500 slid 160 points, or 3%, to 5,186 on Monday, the index's biggest one-day drop in nearly two years, according to FactSet. The tech-heavy Nasdaq Composite sank 3.4% as investors fled some of the Big Tech players that until recently had powered the U.S. market higher — Apple shed 4.8%, while Meta and Nvidia, fell 2.5% and 6.4%, respectively. 

The Dow Jones Industrial Average tumbled 1,034 points, shedding 2.6% of its value. Earlier in the day, it had lost as more than 1,200 points, but the markets regained some of their early losses as Wall Street digested Monday data from the Institute for Supply Management (ISM) Services index, which showed that service employment picked up in July. 

"The details of the ISM report were encouraging, with business activity, new orders and employment all rebounding markedly in July," Oxford Economics said in a Monday research note. The report "aligns with our view of an economy in transition rather than one on the brink of collapse."

Even with Monday's rout, U.S. stocks still remain in positive territory this year. The S&P 500 has gained 9.4% in 2024, even after including its recent slide, while the Dow remains up by 2.6%.

What's driving down stocks

Stocks  lost ground on Thursday after weak reports on manufacturing and construction, which stoked fears the U.S. economy may finally be buckling under the pressure of high interest rates. 

Then on Friday, government data showed that hiring last month was far weaker than expected , adding to Wall Street's fears that a "soft landing," in which the U.S. economy could avoid a recession despite the highest interest rates in 23 years, could instead become a hard landing. 

"The main factor that has staying power is the economy's slowdown," wrote Wells Fargo head of global investment strategy Paul Christopher in a report. "Investors have been watching household financial stress build for the past two years, but during that time, job growth remained above its December 2009-December 2019 average of 180,000 new jobs per month."

But Friday's jobs report showed that employers added only 114,000 new jobs last month, far fewer than the 175,000 jobs expected by economists, he noted. 

Tech stocks have been hit particularly hard in recent weeks as investors pull back from artificial intelligence companies amid questions about when the emerging sector will deliver profits. 

"It has been a tough few weeks for the AI group as earnings were reported," analysts with Melius Research wrote. 'Microsoft, Meta, Google and Amazon were all asked about payoffs from AI investments. While pretty clear that they all need to keep spending, the market remains skeptical of the pace."

The market rout extended to Asian and European markets, with Japan's benchmark stock index plunging 12.4% on Monday. The Nikkei had dropped 5.8% on Friday, making this its worst two-day decline ever. 

Stocks in Korea and Taiwan also fell sharply, with all three Asian markets damaged as investors pull back from companies focused on artificial intelligence out of concern the sector has been overhyped.

When will the Fed cut rates?

With the disappointing economic data, Wall Street is worried the Federal Reserve may have kept its benchmark interest rate too high for too long, heightening the risk of a recession. The central bank kept the federal funds rate unchanged when it met  on July 31 to discuss economic conditions and whether and when it should begin cutting rates.

A rate cut would make it less expensive for U.S. households and companies to borrow money, but it could take time for the effects to boost the economy. On Monday, some investors called for the Fed to start cutting rates sooner rather than later to stave off an economic downturn.

"The Federal Reserve needs to start easing monetary policy more aggressively than had been anticipated, in order to head off a looming recession in the world's largest economy," said Nigel Green, CEO of deVere Group, an independent financial advisory and asset management firm, in an email. "The Fed was behind the curve at the beginning of the cycle, it cannot afford to be behind the curve this time too."

Economists still don't expect a recession

Although worries over weakness in the U.S. economy and volatile markets have rippled around the world, domestic economic activity remains solid, with many analysts saying that a recession remains unlikely. Stephen Brown, deputy chief North America economist with Capital Economics, still expects a soft landing, while acknowledging that the risk of a sharper downturn is rising. 

The economy has accelerated this year, with the nation's gross domestic product jumping to 2.8% in the second quarter, blowing past forecasts. A recession is typically marked by two consecutive quarters of negative GDP. And although July's jobs report was disappointing, analysts point out that it reflects just one month of data, while also noting that the depressed hiring figures in July could have also been impacted by Hurricane Beryl . 

"It can be a mistake to read too much into a single data release," noted Solita Marcelli, chief investment officer Americas at UBS Global Wealth Management, told investors in a research note. "The number of people who reported being unable to work [in July] due to the weather was 436,000; this compares to an average of 33,000 for July since 2000."

The Associated Press contributed to this report.

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Aimee Picchi is the associate managing editor for CBS MoneyWatch, where she covers business and personal finance. She previously worked at Bloomberg News and has written for national news outlets including USA Today and Consumer Reports.

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COVID-19 vaccines: Get the facts

Looking to get the facts about COVID-19 vaccines? Here's what you need to know about the different vaccines and the benefits of getting vaccinated.

As the coronavirus disease 2019 (COVID-19) continues to cause illness, you might have questions about COVID-19 vaccines. Find out about the different types of COVID-19 vaccines, how they work, the possible side effects, and the benefits for you and your family.

COVID-19 vaccine benefits

What are the benefits of getting a covid-19 vaccine.

Staying up to date with a COVID-19 vaccine can:

• Help prevent serious illness and death due to COVID-19 for both children and adults.
• Help prevent you from needing to go to the hospital due to COVID-19 .
• Be a less risky way to protect yourself compared to getting sick with the virus that causes COVID-19.
• Lower long-term risk for cardiovascular complications after COVID-19.

Factors that can affect how well you're protected after a vaccine can include your age, if you've had COVID-19 before or if you have medical conditions such as cancer.

How well a COVID-19 vaccine protects you also depends on timing, such as when you got the shot. And your level of protection depends on how the virus that causes COVID-19 changes and what variants the vaccine protects against.

Talk to your healthcare team about how you can stay up to date with COVID-19 vaccines.

Should I get the COVID-19 vaccine even if I've already had COVID-19?

Yes. Catching the virus that causes COVID-19 or getting a COVID-19 vaccination gives you protection, also called immunity, from the virus. But over time, that protection seems to fade. The COVID-19 vaccine can boost your body's protection.

Also, the virus that causes COVID-19 can change, also called mutate. Vaccination with the most up-to-date variant that is spreading or expected to spread helps keep you from getting sick again.

Researchers continue to study what happens when someone has COVID-19 a second time. Later infections are generally milder than the first infection. But severe illness can still happen. Serious illness is more likely among people older than age 65, people with more than four medical conditions and people with weakened immune systems.

Safety and side effects of COVID-19 vaccines

What covid-19 vaccines have been authorized or approved.

The COVID-19 vaccines available in the United States are:

• 2023-2024 Pfizer-BioNTech COVID-19 vaccine, available for people age 6 months and older.
• 2023-2024 Moderna COVID-19 vaccine, available for people age 6 months and older.
• 2023-2024 Novavax COVID-19 vaccine, available for people age 12 years and older.

These vaccines have U.S. Food and Drug Administration (FDA) emergency use authorization or approval.

In December 2020, the Pfizer-BioNTech COVID-19 vaccine two-dose series was found to be both safe and effective in preventing COVID-19 infection in people age 18 and older. This data helped predict how well the vaccines would work for younger people. The effectiveness varied by age.

The Pfizer-BioNTech vaccine is approved under the name Comirnaty for people age 12 and older. The FDA authorized the vaccine for people age 6 months to 11 years. The number of shots in this vaccination series varies based on a person's age and COVID-19 vaccination history.

In December 2020, the Moderna COVID-19 vaccine was found to be both safe and effective in preventing infection and serious illness among people age 18 or older. The vaccine's ability to protect younger people was predicted based on that clinical trial data.

The FDA approved the vaccine under the name Spikevax for people age 12 and older. The FDA authorized use of the vaccine in people age 6 months to 11 years. The number of shots needed varies based on a person's age and COVID-19 vaccination history.

In July 2022, this vaccine was found to be safe and effective and became available under an emergency use authorization for people age 18 and older.

In August 2022, the FDA authorized the vaccine for people age 12 and older. The number of shots in this vaccination series varies based on a person's age and COVID-19 vaccination history.

In August 2022, the FDA authorized an update to the Moderna and the Pfizer-BioNTech COVID-19 vaccines. Both included the original and omicron variants of the virus that causes COVID-19. In June 2023, the FDA directed vaccine makers to update COVID-19 vaccines. The vaccines were changed to target a strain of the virus that causes COVID-19 called XBB.1.5. In September and October 2023, the FDA authorized the use of the updated 2023-2024 COVID-19 vaccines made by Novavax, Moderna and Pfizer-BioNTech.

How do the COVID-19 vaccines work?

COVID-19 vaccines help the body get ready to clear out infection with the virus that causes COVID-19.

Both the Pfizer-BioNTech and the Moderna COVID-19 vaccines use genetically engineered messenger RNA (mRNA). The mRNA in the vaccine tells your cells how to make a harmless piece of virus that causes COVID-19.

After you get an mRNA COVID-19 vaccine, your muscle cells begin making the protein pieces and displaying them on cell surfaces. The immune system recognizes the protein and begins building an immune response and making antibodies. After delivering instructions, the mRNA is immediately broken down. It never enters the nucleus of your cells, where your DNA is kept.

The Novavax COVID-19 adjuvanted vaccine is a protein subunit vaccine. These vaccines include only protein pieces of a virus that cause your immune system to react the most. The Novavax COVID-19 vaccine also has an ingredient called an adjuvant that helps raise your immune system response.

With a protein subunit vaccine, the body reacts to the proteins and creates antibodies and defensive white blood cells. If you later become infected with the COVID-19 virus, the antibodies will fight the virus. Protein subunit COVID-19 vaccines don't use any live virus and can't cause you to become infected with the COVID-19 virus. The protein pieces also don't enter the nucleus of your cells, where your DNA is kept.

Can a COVID-19 vaccine give you COVID-19?

No. The COVID-19 vaccines available in the U.S. don't use the live virus that causes COVID-19. Because of this, the COVID-19 vaccines can't cause you to become sick with COVID-19.

It can take a few weeks for your body to build immunity after getting a COVID-19 vaccination. As a result, it's possible that you could become infected with the virus that causes COVID-19 just before or after being vaccinated.

What are the possible general side effects of a COVID-19 vaccine?

Some people have no side effects from the COVID-19 vaccine. For those who get them, most side effects go away in a few days.

A COVID-19 vaccine can cause mild side effects after the first or second dose. Pain and swelling where people got the shot is a common side effect. That area also may look reddish on white skin. Other side effects include:

• Fever or chills.
• Muscle pain or joint pain.
• Tiredness, called fatigue.
• Upset stomach or vomiting.
• Swollen lymph nodes.

For younger children up to age 4, symptoms may include crying or fussiness, sleepiness, loss of appetite, or, less often, a fever.

In rare cases, getting a COVID-19 vaccine can cause an allergic reaction. Symptoms of a life-threatening allergic reaction can include:

• Breathing problems.
• Fast heartbeat, dizziness or weakness.
• Swelling in the throat.

If you or a person you're caring for has any life-threatening symptoms, get emergency care.

Less serious allergic reactions include a general rash other than where you got the vaccine, or swelling of the lips, face or skin other than where you got the shot. Contact your healthcare professional if you have any of these symptoms.

You may be asked to stay where you got the vaccine for about 15 minutes after the shot. This allows the healthcare team to help you if you have an allergic reaction. The healthcare team may ask you to wait for longer if you had an allergic reaction from a previous shot that wasn't serious.

Contact a healthcare professional if the area where you got the shot gets worse after 24 hours. And if you're worried about any side effects, contact your healthcare team.

Are there any long-term side effects of the COVID-19 vaccines?

The vaccines that help protect against COVID-19 are safe and effective. Clinical trials tested the vaccines to make sure of those facts. Healthcare professionals, researchers and health agencies continue to watch for rare side effects, even after hundreds of millions of doses have been given in the United States.

Side effects that don't go away after a few days are thought of as long term. Vaccines rarely cause any long-term side effects.

If you're concerned about side effects, safety data on COVID-19 vaccines is reported to a national program called the Vaccine Adverse Event Reporting System in the U.S. This data is available to the public. The U.S. Centers for Disease Control and Protection (CDC) also has created v-safe, a smartphone-based tool that allows users to report COVID-19 vaccine side effects.

If you have other questions or concerns about your symptoms, talk to your healthcare professional.

Can COVID-19 vaccines affect the heart?

In some people, COVID-19 vaccines can lead to heart complications called myocarditis and pericarditis. Myocarditis is the swelling, also called inflammation, of the heart muscle. Pericarditis is the swelling, also called inflammation, of the lining outside the heart.

Symptoms to watch for include:

• Chest pain.
• Shortness of breath.
• Feelings of having a fast-beating, fluttering or pounding heart.

If you or your child has any of these symptoms within a week of getting a COVID-19 vaccine, seek medical care.

The risk of myocarditis or pericarditis after a COVID-19 vaccine is rare. These conditions have been reported after COVID-19 vaccination with any of the vaccines offered in the United States. Most cases have been reported in males ages 12 to 39.

These conditions happened more often after the second dose of the COVID-19 vaccine and typically within one week of COVID-19 vaccination. Most of the people who got care felt better after receiving medicine and resting.

These complications are rare and also may happen after getting sick with the virus that causes COVID-19. In general, research on the effects of the most used COVID-19 vaccines in the United States suggests the vaccines lower the risk of complications such as blood clots or other types of damage to the heart.

If you have concerns, your healthcare professional can help you review the risks and benefits based on your health condition.

Things to know before a COVID-19 vaccine

Are covid-19 vaccines free.

In the U.S., COVID-19 vaccines may be offered at no cost through insurance coverage. For people whose vaccines aren't covered or for those who don't have health insurance, options are available. Anyone younger than 18 years old can get no-cost vaccines through the Vaccines for Children program. Adults can get no-cost COVID-19 vaccines through the temporary Bridges to Access program, which is scheduled to end in December 2024.

Can I get a COVID-19 vaccine if I have an existing health condition?

Yes, COVID-19 vaccines are safe for people who have existing health conditions, including conditions that have a higher risk of getting serious illness with COVID-19.

The COVID-19 vaccine can lower the risk of death or serious illness caused by COVID-19. Your healthcare team may suggest that you get added doses of a COVID-19 vaccine if you have a moderately or severely weakened immune system.

Cancer treatments and other therapies that affect some immune cells also may affect your COVID-19 vaccine. Talk to your healthcare professional about timing additional shots and getting vaccinated after immunosuppressive treatment.

Talk to your healthcare team if you have any questions about when to get a COVID-19 vaccine.

Is it OK to take an over-the-counter pain medicine before or after getting a COVID-19 vaccine?

Don't take medicine before getting a COVID-19 vaccine to prevent possible discomfort. It's not clear how these medicines might impact the effectiveness of the vaccines. It is OK to take this kind of medicine after getting a COVID-19 vaccine, as long as you have no other medical reason that would prevent you from taking it.

Allergic reactions and COVID-19 vaccines

What are the signs of an allergic reaction to a covid-19 vaccine.

Symptoms of a life-threatening allergic reaction can include:

If you or a person you're caring for has any life-threatening symptoms, get emergency care right away.

Less serious allergic reactions include a general rash other than where you got the vaccine, or swelling of the lips, face or skin other than where the shot was given. Contact your healthcare professional if you have any of these symptoms.

Tell your healthcare professional about your reaction, even if it went away on its own or you didn't get emergency care. This reaction might mean that you are allergic to the vaccine. You might not be able to get a second dose of the same vaccine. But you might be able to get a different vaccine for your second dose.

Can I get a COVID-19 vaccine if I have a history of allergic reactions?

If you have a history of severe allergic reactions not related to vaccines or injectable medicines, you may still get a COVID-19 vaccine. You're typically monitored for 30 minutes after getting the vaccine.

If you've had an immediate allergic reaction to other vaccines or injectable medicines, ask your healthcare professional about getting a COVID-19 vaccine. If you've ever had an immediate or severe allergic reaction to any ingredient in a COVID-19 vaccine, the CDC recommends not getting that specific vaccine.

If you have an immediate or severe allergic reaction after getting the first dose of a COVID-19 vaccine, don't get the second dose. But you might be able to get a different vaccine for your second dose.

Pregnancy, breastfeeding and fertility with COVID-19 vaccines

Can pregnant or breastfeeding women get the covid-19 vaccine.

The CDC recommends getting a COVID-19 vaccine if:

• You are planning to or trying to get pregnant.
• You are pregnant now.
• You are breastfeeding.

Staying up to date on your COVID-19 vaccine helps prevent severe COVID-19 illness. It also may help a newborn avoid getting COVID-19 if you are vaccinated during pregnancy.

People at higher risk of serious illness can talk to a healthcare professional about additional COVID-19 vaccines or other precautions. It also can help to ask about what to do if you get sick so that you can quickly start treatment.

Children and COVID-19 vaccines

If children don't often experience severe illness with covid-19, why do they need a covid-19 vaccine.

While rare, some children can become seriously ill with COVID-19 after getting the virus that causes COVID-19 .

A COVID-19 vaccine might prevent your child from getting the virus that causes COVID-19 . It also may prevent your child from becoming seriously ill or having to stay in the hospital due to the COVID-19 virus.

After a COVID-19 vaccine

Can i stop taking safety precautions after getting a covid-19 vaccine.

You can more safely return to activities that you might have avoided before your vaccine was up to date. You also may be able to spend time in closer contact with people who are at high risk for serious COVID-19 illness.

But vaccines are not 100% effective. So taking other action to lower your risk of getting COVID-19 still helps protect you and others from the virus. These steps are even more important when you're in an area with a high number of people with COVID-19 in the hospital. Protection also is important as time passes since your last vaccination.

If you are at higher risk for serious COVID-19 illness, basic actions to prevent COVID-19 are even more important. Some examples are:

• Avoid close contact with anyone who is sick or has symptoms, if possible.
• Use fans, open windows or doors, and use filters to move the air and keep any germs from lingering.
• Wash your hands well and often with soap and water for at least 20 seconds. Or use an alcohol-based hand sanitizer with at least 60% alcohol.
• Cough or sneeze into a tissue or your elbow. Then wash your hands.
• Clean and disinfect high-touch surfaces. For example, clean doorknobs, light switches, electronics and counters regularly.
• Spread out in crowded public areas, especially in places with poor airflow. This is important if you have a higher risk of serious illness.
• The CDC recommends that people wear a mask in indoor public spaces if COVID-19 is spreading. This means that if you're in an area with a high number of people with COVID-19 in the hospital a mask can help protect you. The CDC suggests wearing the most protective mask possible that you'll wear regularly, that fits well and is comfortable.

Can I still get COVID-19 after I'm vaccinated?

COVID-19 vaccination will protect most people from getting sick with COVID-19. But some people who are up to date with their vaccines may still get COVID-19. These are called vaccine breakthrough infections.

People with vaccine breakthrough infections can spread COVID-19 to others. However, people who are up to date with their vaccines but who have a breakthrough infection are less likely to have serious illness with COVID-19 than those who are not vaccinated. Even when people who are vaccinated get symptoms, they tend to be less severe than those felt by unvaccinated people.

Researchers continue to study what happens when someone has COVID-19 a second time. Reinfections and breakthrough infections are generally milder than the first infection. But severe illness can still happen. Serious illness is more likely among people older than age 65, people with more than four medical conditions and people with weakened immune systems.

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Raygun becomes viral sensation during breaking performance at 2024 Paris Olympics: Social media reacts

Breaking , more commonly known as breakdancing, made its debut as an Olympic sport this week at the 2024 Paris Games , with 17 B-girls and 16 B-boys making their way to France with the hopes of securing a gold medal.

On the first day of competition, viewers from across the world were treated to a different kind of introduction — not to the sport itself, but one of its athletes.

Though she was a long way from winning a gold medal, likely no breaker Friday captured the imagination of the international audience more than Rachael Gunn, an Australian breaker who competes under the name “Raygun.”

REQUIRED READING: Follow USA TODAY's coverage of the 2024 Paris Olympics

Raygun went 0-3 in her head-to-head competitions Friday — falling to Logistx of the United States, Syssy of France and eventual silver medalist Nicka of Lithuania by a combined score of 54-0 — and failed to record a point across those three matches, but for what she lacked in smoothly executed moves, she made up for in the hearts she won over with her demeanor.

Raygun’s short-lived Olympic experience made her a celebrity, one who people became even more enamored with once they learned more about her.

The 36-year-old Gunn, who was one of the oldest qualifiers in the breaking competition, has a PhD in cultural studies and is a college professor at Macquarie University in Sydney. Her research focuses primarily on breaking, street dance and hip-hop culture while her work draws on “cultural theory, dance studies, popular music studies, media, and ethnography.”

“In 2023, many of my students didn’t believe me when I told them I was training to qualify for the Olympics, and were shocked when they checked Google and saw that I qualified,” Gunn said to CNBC earlier this month .

Unlike much of her competition in Paris, Gunn took up break dancing later in life. She didn’t enter her first battle until 2012.

On Friday, a person who began the day as a little-known academic ended it as a viral worldwide sensation.

Here’s a sampling of the reaction to Raygun and her performance:

2024 PARIS OLYMPICS: Meet the members of Team USA competing at the 2024 Paris Olympics

Social media reacts to Raygun’s breaking performance at 2024 Paris Olympics

I could live all my life and never come up with anything as funny as Raygun, the 36-year-old Australian Olympic breakdancer pic.twitter.com/1uPYBxIlh8 — mariah (@mariahkreutter) August 9, 2024

Give Raygun the gold right now #breakdancing pic.twitter.com/bMtAWEh3xo — n★ (@nichstarr) August 9, 2024

my five year old niece after she says “watch this!” : pic.twitter.com/KBAMSkgltj — alex (@alex_abads) August 9, 2024

I'd like to personally thank Raygun for making millions of people worldwide think "huh, maybe I can make the Olympics too" pic.twitter.com/p5QlUbkL2w — Bradford Pearson (@BradfordPearson) August 9, 2024

The Aussie B-Girl Raygun dressed as a school PE teach complete with cap while everyone else is dressed in funky breaking outfits has sent me. It looks like she’s giving her detention for inappropriate dress at school 🤣 #Olympics pic.twitter.com/lWVU3myu6C — Georgie Heath🎙️ (@GeorgieHeath27) August 9, 2024

There has not been an Olympic performance this dominant since Usain Bolt’s 100m sprint at Beijing in 2008. Honestly, the moment Raygun broke out her Kangaroo move this competition was over! Give her the #breakdancing gold 🥇 pic.twitter.com/6q8qAft1BX — Trapper Haskins (@TrapperHaskins) August 9, 2024

my dog on the lawn 30 seconds after i've finished bathing him pic.twitter.com/A5aqxIbV3H — David Mack (@davidmackau) August 9, 2024

My wife at 3AM: I think I heard one of the kids Me: No way, they are asleep *looks at baby monitor* pic.twitter.com/Ubhi6kY4w4 — Wes Blankenship (@Wes_nship) August 9, 2024

me tryna get the duvet off when i’m too hot at night #olympics pic.twitter.com/NM4Fb2MEmX — robyn (@robynjournalist) August 9, 2024

Raygun really hit them with the "Tyrannosaurus." pic.twitter.com/ZGCMjhzth9 — Mike Beauvais (@MikeBeauvais) August 9, 2024

Raygun (AUS) https://t.co/w2lxLRaW2x — Peter Nygaard (@RetepAdam) August 9, 2024

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• Published: 02 August 2024

Wireless ear EEG to monitor drowsiness

• Ryan Kaveh   ORCID: orcid.org/0000-0003-4146-7259 1   na1 ,
• Carolyn Schwendeman 1   na1 ,
• Leslie Pu 1 ,
• Ana C. Arias 1 &
• Rikky Muller   ORCID: orcid.org/0000-0003-3791-1847 1  

Nature Communications volume  15 , Article number:  6520 ( 2024 ) Cite this article

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• Biomedical engineering
• Electrical and electronic engineering
• Predictive markers

Neural wearables can enable life-saving drowsiness and health monitoring for pilots and drivers. While existing in-cabin sensors may provide alerts, wearables can enable monitoring across more environments. Current neural wearables are promising but most require wet-electrodes and bulky electronics. This work showcases in-ear, dry-electrode earpieces used to monitor drowsiness with compact hardware. The employed system integrates additive-manufacturing for dry, user-generic earpieces, existing wireless electronics, and offline classification algorithms. Thirty-five hours of electrophysiological data were recorded across nine subjects performing drowsiness-inducing tasks. Three classifier models were trained with user-specific, leave-one-trial-out, and leave-one-user-out splits. The support-vector-machine classifier achieved an accuracy of 93.2% while evaluating users it has seen before and 93.3% when evaluating a never-before-seen user. These results demonstrate wireless, dry, user-generic earpieces used to classify drowsiness with comparable accuracies to existing state-of-the-art, wet electrode in-ear and scalp systems. Further, this work illustrates the feasibility of population-trained classification in future electrophysiological applications.

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Introduction.

Drowsiness and fatigue while operating heavy machinery can be life-threatening. It is estimated that over 16.5% of fatal vehicle accidents in the United States include a drowsy driver resulting in over 8000 deaths and $109 billion in damages 1 , 2 , 3 . In addition to private and commercial (trucking) accidents, the National Safety Council has also cited drowsiness as the most critical hazard in construction and mining. While these deaths may be prevented with common risk assessments, fatigued individuals are often unable to recognize the full extent of their impairment before it is too late 4 . Drowsiness monitoring solutions use camera-based eye-tracking, steering trajectory sensors, or electrophysiological recording devices 5 , 6 , 7 . While they can be a good fit in automotive scenarios, eye tracking is obscured by sunglasses and other obstructions while steering sensors can be susceptible to false alarms on rough roads. User-centered recording modalities such as body-worn cameras, photoplethysmography (PPG), electrodermal activity, electrocardiography (ECG), electrooculography (EOG), and electroencephalography (EEG) are becoming increasingly popular because they are highly portable and adaptable to professional work environments 8 , 9 , 10 , 11 . These modalities have been incorporated into multiple form-factors such as eye-tracking glasses 12 , PPG/ExG tracking helmets 7 , and in-ear ExG sensors 13 , 14 . Of these methods, ExG generally achieves the highest drowsiness detection accuracies 15 .

Surface EEG is a safe, non-invasive method of monitoring the brain’s electrical activity from the scalp. Clinically, the most prevalent use of EEG is the monitoring and diagnosis of stereotyped neurological disorders related to sleep and epilepsy. These clinical systems generally use large, scalp-based, gold (Au) and silver/silver chloride (Ag/AgCl) electrode arrays 16 , 17 , 18 . Au forms a capacitive interface due to its inert nature, while Ag/AgCl forms a faradaic interface between Ag and skin. The AgCl is a slightly soluble salt that quickly saturates the skin and forms a stable electrode-skin interface. To maintain a low-impedance electrode-skin interface, contact is improved with skin preparation from an overseeing technician. While suitable for occasional, short-term monitoring, existing wet electrode arrays tend to be large and delicate for everyday use. Additionally, prolonged use of devices that require skin abrasion can result in skin irritation and lesions, further limiting their long-term use 19 , 20 . To promote use outside the lab and simplify clinical measurements, recent wearable EEG monitoring systems have focused on using smaller form-factor wet electrode arrays (e.g., cEEGgrid) 21 and dry electrodes that eliminate the use of hydrogels, integrating electronics and electrodes into a headset form factor, and software packages that allow for use in more everyday applications. The improved wet electrode systems (e.g., the cEEG grid) can provide unobtrusive EEG monitoring for 7+ h, but still requires hydrogel application (limiting day-to-day use). Dry electrode systems for research (e.g., CGX systems and Emotiv), commercial (e.g., Muse headband and Neurosity), and hobbyist (e.g., OpenBCI and Brainbit) have similarly demonstrated impressive EEG recordings of spontaneous and evoked neural signals and enabled disease monitoring, brain-computer interfaces (BCIs) and meditation guidance. As these commercial systems’ popularity increases, more and more wireless EEG systems are being developed and deployed across different environments 22 , 23 , 24 , 25 . The least cumbersome systems employ dry electrodes that minimize set-up time but generally still require skin cleaning and electrode surface treatments. Furthermore, the associated software packages require training to use 23 , 24 . Lastly, headset electronics are better suited for research and clinical environments as opposed to public, everyday use.

Discreet, multi-channel EEG recordings from inside the ear canal have been demonstrated 26 , 27 , 28 with recent advancements focusing on earpiece design, electrode materials, and multi-sensor arrays. The ear canal is an ideal sensor location due to its inherent mechanical stability and wealth of potential recording modalities. In-ear sensors and electrodes are well situated to record temporal lobe activity, blood oxygen saturation, head movement, and masseter muscle activity making it ideal for multi-modal sensing if high spatial coverage is not required 29 , 30 . While some applications may treat muscle activity or ear canal deformation as interference signals, these signals can be useful for other general ExG workloads. It is also important to note that in and around-the-ear EEG is inherently limited in gathering spatially encoded brain-activity relative to broader scalp arrays 27 , 28 , 29 , 30 , 31 . Many successful designs have leveraged hydrogel coated on flex-pcb arrays or user-customized earpieces to record ExG features such as EOG, low-frequency EEG (1–30 Hz), and evoked potentials (40–80 Hz) 26 , 27 , 28 , 32 , 33 . These wet-electrode based, custom earpiece systems established the feasibility of in-ear monitoring for attention monitoring, seizure monitoring, whole night sleep monitoring, and sleep stage classification 34 , 35 , 36 , 37 . Due to their user customized approach, earpieces require a case-by-case integration schemes to minimize earpiece volume resulting in variable electrode positioning. The required skin-preparation and hydrogel also can lead the conductive bridging between electrodes, limit-user-comfort, and reduced electrode lifetime 38 . The next step to more scalable deployment of in-ear ExG recordings would be the utilization of one-size-fits-most (user-generic) earpiece designs, dry electrodes, wireless electronics, and electrode materials that do not require maintenance.

Recent user-generic earpieces equipped with wet electrodes, dry electrodes 39 , 40 , 41 , 42 , PPG, and/or chemical sensors have achieved high degrees of accuracy for brain-state and activity classification 39 , 40 , 43 , 44 , 45 , 46 . Additionally, dry-electrode based in-ear ExG have recorded low frequency neural rhythms, evoked potentials, and EOG comparable to wet-electrode. While potentially more susceptible to noise due to higher electrode-skin impedance (ESI) interfaces 47 , dry electrodes eliminate the use of hydrogel, simplify the earpiece application process, and can improve user comfort. To achieve a middle ground between comfort and low ESI, state-of-the-art dry electrodes employ a wide range of solutions ranging from exotic materials, conductive composites, capacitive interfaces, solid-gels, and high-surface area 3D electrodes (microneedles, fingers, and nanowires) 20 , 40 , 41 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 . PEDOT:PSS and IrO 3 are commonly used in the small-scale production of rigid electrodes due to their superior conductivity and faradaic interfaces 57 , 58 , 59 . Both materials promote charge transfer by leveraging doped surfaces and high effective surface areas. Conductive, flexible composites, such as silvered-glass silicone and carbon-infused silicone, are not as conductive as PEDOT:PSS and IrO 3 but offer significantly greater comfort. Conductive composites are made from polymers or elastomers that can be molded into arbitrary shapes for anatomically fit electrodes and use added conductive particles to achieve a desirable ESI. The more conductive particles that are added will ultimately limit polymer cross-linking and may lead to cracking over time 60 . The clinical and industry standard materials are silver/silver chloride (Ag/AgCl) and gold due to their cost, biocompatibility, and electrical properties. Ag/AgCl can be painted on 3D electrodes to form consistent, faradaic, low-impedance interface through hair and grime. Furthermore, Ag/AgCl is also popular for consumable electrodes since the conductive particles deplete over time 61 . Gold electrodes are more inert, can be repeatedly reused, and form a capacitive interface that is not reliant on added conductive ions. While potentially more susceptible to motion artifacts and interference, gold’s lifetime and chemical properties make it ideal for long-lasting ExG recording systems. Most commercial wearables and existing in-ear ExG systems use Ag/AgCl, Au, or conductive composite electrodes 24 , 62 , 63 , 64 .

Electrodes are just one piece of signal acquisition. Neural recording hardware is required to digitize neural signals and transmit them to a processing unit/base-station for offline processing. Neural recording hardware for more consumer-facing products tend to be tailor-made with low bandwidth, noise, and power specifications 65 , 66 , 67 . These devices usually have bandwidths around 100 Hz and can achieve ultra-lower power operation (<100 μW 67 ). Research focused devices, however, utilizing high resolution and bandwidth hardware enables greater investigation outside the original project description. Such versatile systems generally support higher channel counts (16–64+), commercial wireless protocols (bluetooth or Wi-Fi), higher sampling rates (500–1000 Hz), and can take advantage of different signal modalities (e.g., EMG) at the cost of higher power (>50 mW) 42 , 46 , 68 . Low-noise and high-resolution systems allows for greater flexibility, repeated interpretable signal processing (frequency analysis, time-domain averaging, etc.) and algorithm development to illuminate different feature classes, mitigate interference, and discover new potential applications. Such systems have been used to build brain-machine interfaces with P300 responses and steady-state evoked potentials 27 , 29 , 34 , 69 , 70 . When adapting existing electronics for use with wearable dry electrodes, increased ESI, system noise, and interference susceptibility bear important considerations for power requirements and any downstream machine learning algorithm 71 , 72 . Employing versatile, higher power electronics with more interpretable, light weight classical algorithms (e.g., logistic regression, support vector machines, random forest) is an important first step for future sensor and power optimizations. To this effect, this work uses an existing, high channel count, high bandwidth system to enable studying the relationship between the employed ExG electrode technology and drowsiness detection.

In addition to system optimisation, the choice of machine learning algorithm determines system functionality from the perspective of training, data, and processing requirements. Every-day ExG systems would ideally work out of the box, improve over time, and continue to provide feedback when wireless connectivity is poor and there is unreliable access to large processing power (construction sites, planes, and trucks). Classical algorithms such as logistic regression, SVMs, and random forest have demonstrated impressive success in classifying neural signals with limited datasets 15 , 25 , 73 , 74 . Neural network-based algorithms have also achieved impressive results 75 , 76 , 77 , and are good candidates for further research. Neural network-based algorithms, on average, require more training data than SVMs, logistic regression, and random forest, making them difficult to work with on smaller data sets. Furthermore, interpretable algorithms such as logistic regression and SVMs enable greater visibility into which types of features have sufficient SNR for classification and could potentially be applied to different applications. Lastly, algorithms such as SVMs, logistic regression, and random forest generally require less processing power than similarly performing neural net or perceptron-based architectures, making them ideal for low-power, edge-based deployments on existing microcontrollers. Additionally, while existing in-ear ExG BCIs have achieved high classification accuracies with user-specific training and validation 35 , 43 , 76 , 78 , 79 , ideal in-ear ExG wearables would leverage pre-trained algorithms so never-before-seen users can use these devices without time-consuming training. This user-generic classification has been explored in scalp-based drowsiness monitoring with great success but not yet with in-ear ExG 15 .

This project is the first integration and demonstration of wireless, dry-electrode in-ear ExG sensors used for drowsiness classification. To this effect, a novel in-ear EEG sensor manufacturing method coupled to a pre-existing wireless data acquisition platform is presented and verified with open-source machine learning classification on 9-subjects. A fabrication process for dry, gold-plated electrodes suitable for repeated, comfortable, low-impedance earpieces is introduced and tested over the course of months of electrode use. This electrode technology provides a unique method for the rapid prototyping of reusable, Au electrodes that remain stable over 12 months of use. These electrodes can replace existing solutions that rely on shorter-lifespan Ag/AgCl electrodes or expensive materials such as platinum or IrO3. The earpieces are then coupled with wireless, discreet electronics capable of taking uninterrupted, low-noise neural measurements for over 40 h 46 to form a wearable, in-ear ExG system. The resulting Ear ExG BCI is then demonstrated with a nine-subject drowsiness monitoring study. Low-complexity temporal and spectral features are extracted from the recorded ExG data and used to train multiple, offline machine learning models for automated drowsiness detection. The best-performing model utilizing a support vector machine achieved an average drowsy-event detection accuracy of 93.2% when evaluating on users it has seen before and 93.3% when evaluating never-before-seen users. This system and its use of offline classifiers lay the groundwork for future, discreet, fully wireless, long term, longitudinal brain monitoring (Fig.  1 ).

Envisioned systems could be discreetly worn throughout the day to comfortably record neural signals from inside the ear canal, perform drowsiness detection, and provide feedback.

Results: ear ExG drowsiness monitoring platform

Modular electrode design, fabrication, and assembly, earpiece design.

Easy-to-use neural wearables require a user-generic earpiece and electrode scheme designed for recording across multiple demographics and for comfortable, long-term wear. To achieve these requirements, electrode and earpiece designs were derived from refs. 46 , 80 and resulted in a small, medium, and large size of a single design with modular electrodes. Electrodes are positioned near the ear canal such that they do not pass the isthmus of the ear canal, which tends to develop a corkscrew shape as individuals age. This earpiece is designed to account for these age-related changes. Previous studies 30 , 41 , have highlighted high value electrode locations that minimize channel-to-channel correlation while maximizing mechanical stability. To also maximize electrode surface area across different individuals, small, medium, and large sized earpieces were designed with slightly differing electrode sizes. The final “medium-sized” earpiece is comprised of four 60 mm 2 electrodes inside the ear canal and two 3 cm 2 electrodes on the ear’s concha cymba and concha cavity (Fig.  2a ). The in-ear electrodes are cantilevers that apply gentle outward pressure to achieve lower ESI over previous iterations (370 kΩ to 120 kΩ at 50 Hz 46 ) and improve mechanical stability. The out-ear electrodes act as fiducial guideposts to ensure the electrodes contact the same surface with each wear. Furthermore, electrodes outside the ear are good reference and ground candidates due to their increased distance from the brain or any muscle. To improve the earpiece assembly and further increase comfort over 46 , a soft earpiece body with a manifold in-ear design was 3D printed with a clear methacrylate photopolymer (Fig.  2a ). Each rigid electrode is attached to this soft, elastic substrate and moves independently from the other electrodes to fit in a subject’s ear (Fig.  2b ). This new, modular assembly properly demonstrates the capabilities of the manifold earpiece fabrication process.

a The final earpieces are composed of four in-ear electrodes and two out-ear electrodes. Manifold 3D-printed earpieces are assembled by plugging rigid, gold-plated earpieces into a soft, flexible skeleton. b The out-ear electrodes press against the ear’s concha cymba and concha bowl, while the in-ear electrodes contact the ear canal’s aperture. In-ear electrodes only enter the first 10 mm of the ear canal. c Diagram and photographs of electrode fabrication: i) Electrodes are 3D printed or molded. ii) The bare electrodes are sandblasted and cleaned. iii) The electrodes are electroless copper plated via exposure to surfactant, catalyst, and copper sulfate solutions in sequence. iv) A nickel layer is electroless plated. v) A final gold layer is electroless deposited.

Electrode fabrication

A low-cost, fully electroless plating process was developed to enable rapid prototyping of arbitrary shaped electrophysiological sensors. Electrodes were 3D printed with a clear methacrylate polymer (Fig.  2c ) and sandblasted to increase surface roughness. Samples were then submersed in different catalyst baths to develop copper, nickel, and gold metal layers. Lastly, tinned copper wires are soldered directly to the electrode surface for integration with the neural recording front end. This plating process is expanded on 45 , 81 , with the addition of a nickel layer that limits grain-boundary diffusion of copper and significantly extends electrode lifetime 81 , 82 , 83 . Furthermore, the nickel-plating step removes the need for repeated electroless palladium plating and the overall number of fabrication steps. While other in-ear electrodes use expensive materials like IrO 3 or hydrogels 39 , 40 , this improved layer stack-up (Cu, Ni, Au) is reminiscent of printed-circuit-board fabrication and enables similar levels of scale for electrode prototyping. The final surface contains at least 0.5 µm of copper, 0.5 µm of nickel, and 0.25 µm of gold and is suitable for dry electrode recording.

Plating process characterization

Material acid dip tests and tape tests.

The final electrode surfaces were physically and chemically robust. Kapton tape was applied around the entire electrode surface and then removed. No visible gold, nickel, or copper was removed with the tape indicating strong adhesion to the methacrylate substrate 81 , 84 . Electrode samples were also dipped in nitric acid baths to test the porosity and continuity of the gold surface. While concentrated and dilute nitric acid will readily dissolve copper and nickel, respectively, neither will etch gold. No noticeable differences were observed after dipping gold-plated electrodes into a 1M nitric acid bath. Control samples of copper and nickel, however, were quickly etched down to the bare methacrylate surface. The acid dip tests and subsequent microscope inspections (Fig.  3a ) found no micro or nano cracks that may affect the electrode’s surface or electrical properties.

a Representative light microscopy images of plated surfaces showcasing the roughness resulting from sandblasting. b Stylus Profilometer measurements of a flat sample after each plating step. c Absolute sheet resistance measurements, mean (red circle), and standard deviation (error bars) immediately after plating. d In-ear electrode-skin impedance magnitude, phase, and magnitude fit. Standard deviation of electrode magnitude shown in shaded green region. e Constant phase element electrode model used for fitting.

Surface roughness characterization

Light microscopy photographs and stylus profilometry measurements were used to assess surface roughness between each step of the plating process on a single flat sample. Figure  3b plots the normalized surface topography of the sample during each plating step. The reported Rp values are the standard deviation of the plotted lines. Though surface roughness decreases slightly with each subsequent plating step, the final gold surface is still much rougher than a simple, planar surface. This increases electrode surface area, promotes better film adhesion, and reduces ESI 50 , 81 , 84 , 85 .

Sheet resistance

Sheet resistance was characterized by a 4-point probe immediately after plating. 40 sheet resistance measurements were taken of each copper-, nickel-, and gold-plated samples. As prepared, copper-plated samples, nickel-plated samples, and gold-plated samples exhibited an average sheet resistance of 177.9 ± 109, 95.5 ± 13, and 30.3 ± 3.7 mΩ □ −1 , respectively (Fig.  3c ). With each subsequent metal layer, the sheet resistance stabilized, and the surfaces became more conductive.

Bioimpedance of In-ear electrodes across multiple users

Impedance spectroscopy was used to assess in-ear electrode-skin impedance. Four subjects took impedance measurements (20 total measurements) between the in-ear electrodes and the out-ear cymba electrode. To account for future, real-life conditions with cerumen and oil, no skin preparation was performed before each trial, and measurements were repeated until all four electrodes in the ear canal were measured. Since the ESI measurements include two dry electrodes, the plotted values were divided by two to demonstrate the average ESI of a single dry electrode. All measurements were performed with an LCR meter (E4980 A, Keysight) powered by a wall outlet and arranged as a two-point probe where a single electrode is considered a single probe. The LCR meter was configured with a current limit of 0.5 mA to prevent sensation or injury. While the LCR meter is designed to achieve high accuracy (within 3%) even in the presence of powerline interference, electrode cables were shielded by ground wires to further minimize interference. All impedance results were fitted to an equivalent circuit model (spectra shown in Fig.  3d , circuit model shown in Fig.  3e ) to better understand motion artifact settling times associated with the phase elements of the electrode skin interface and provide reference for future analog front-end designs. At 50 Hz, the interface has an average impedance of 120 kΩ and phase of −33°.

Lightweight ExG recording system

ExG was recorded using an existing compact, wireless recording platform affixed to a headband (Fig.  4a ). The platform, known as WANDmini, is a wireless neural recording frontend built for and already deployed in previous in-ear EEG studies 46 . It is adapted from a system originally designed for electrocorticography and comprises a custom neural recording circuit 68 , 86 , (NMIC 86 , Cortera Neurotechnologies, Inc.), a microcontroller, and a Bluetooth radio for wireless transmission. The NMIC digitizes up to 64, fully differential channels of electrophysiological activity with a sampling rate of 1 kSps. WANDmini arranges the NMIC’s channels in a monopolar montage with a single reference electrode. This arrangement is it suitable for EEG, EOG, and EMG recording and provides enough sampling and channel count headroom to remove any recording electronics related bottlenecks. An onboard microcontroller and radio packetizes and streams digitized neural data to a base station connected to a host machine over Bluetooth Low Energy (BLE) (Fig.  4a ). System power is dominated by the microcontroller and Bluetooth transmission (98.3%) thus making unused channels immaterial from a power perspective. With the NMIC and WANDmini power consumptions, 700 μW and 46 mW, respectively, a 3.7 V 550 mA battery can provide ~44 h of runtime. In summary, the NMIC’s significantly lower power than common commercial neural frontends (e.g., ADS1298/1299), high channel count, and sufficiently low noise floor makes it ideal for use in modular in-ear EEG prototypes. NMIC and WANDmini specifications are listed in Table  1 and further detailed in Supplement section  II.h . The host machine uses a custom graphical user interface (GUI) that plots and saves all incoming data and cues for the trail overseer. This custom GUI is unique to this work and provides the test subject with a reaction time game, auditory cues, and visual alerts during experiments. More information about the GUI is available in section 2h of the supplement.

a Subjects sit beside a laptop displaying a basic reaction time measuring game. A head-worn WANDmini, secured in a 3D-printed enclosure, records and transmits ExG from contralaterally worn earpieces to a base station via BLE while the subject plays the game. All captured ExG can be live plotted for the trial overseer while the game records subject’s reaction times and Likert survey responses. b Recorded ExG, reaction times, and Likert items are used to generate features and labels for a brain-state classifier. Drowsy events, shaded in green, are determined when a subject’s reaction time and Likert response cross a drowsiness threshold that is determined per subject. Using both the reaction time and Likert scores enables robust label creation that is agnostic to temporary user error.

EEG characterization and user-generic drowsiness detection

Drowsiness study.

To characterize the full system performance, 35 h of Ear ExG data was recorded during a nine subject drowsiness study. Subjects wore two earpieces with the electrodes organized in a contralateral monopolar montage. Previous works have demonstrated that electrodes on a single earpiece are sufficiently distant from each other to measure ExG 37 , 41 , but greater signal amplitude can be recorded with electrodes placed across both ears 39 , 45 . To induce drowsiness, subjects played a repetitive reaction time game. Every 60 s, a user was prompted to press a random number between 0 and 9 and their reaction time was recorded (Fig.  4a ). Every 5 min, the user was prompted to enter a Likert item according to the Karolinska Sleepiness Scale (KSS). This scale is frequently used to evaluate subjective sleepiness and ranges from 0 = “extremely alert”, to 10 = “extremely sleepy, fighting to stay awake” 87 . Queue intervals (60 s and 5 min) were selected based on initial experimentation and previous works that demonstrated a balance between minimizing disturbances and frequent datapoints 45 , 88 . All recorded ExG, cue timing, reaction times, and Likert items are saved by a custom GUI for post-processing and machine learning model training (Fig.  4b ). Immediately after each trial, reaction time and Likert items were thresholded per subject to automatically generate alert/drowsy labels for each trial since behavior and response time metrics are heavily correlated with drowsiness 6 , 87 , 88 . By taking both an objective and a subjective drowsiness measurement, high-confidence data labels could be generated in face of user-error and user-bias (memory of previous KSS scores affecting subsequent scores). Both objective and subjective measures must agree to classify an event as drowsy. Furthermore, as noted in previous works, reaction times and likert scores are variable on a subject-to-subject basis. As a result, each trial was thresholded on a per subject basis. Each trial contained at least one drowsy event, and 65 drowsiness events were recorded across 34 trials.

Drowsiness classification pipeline

The training pipeline for ExG data consisted of post-processing, feature extraction, and model training steps (Fig.  5a ). ExG recordings were referenced to maximize spatial covering, band pass filtered, and segmented into 50 s or 10 s windows. If a window of data exhibited an artifact greater than 10 mV (from motion) it would be discarded. This was happened very infrequently as most artifacts were less than 1 mV above the baseline rms voltage. Temporal and spectral features relevant for ExG-based drowsiness detection were implemented to target ocular artifacts and activity in standard EEG frequency bands relevant to drowsiness detection: delta ( δ , 0.05–4 Hz), theta ( θ , 4–8 Hz), alpha ( α , 8–13 Hz), beta ( β , 13–30 Hz), and gamma ( γ , 30–50 Hz). Binary (alert/drowsy) classification was performed with low-complexity logistic regression, support vector machine (SVM), and random forest classifier models.

a Ear ExG experimental recordings are re-referenced, filtered, cleaned of motion-contaminated epochs, and then undergo feature extraction and model training. b Cross-validation is performed similarly, featurized ear ExG epochs are fed to all three classification models. Model outputs are then fed to an event detector that performs a moving average and then thresholds the resulting classifications to estimate alert and drowsy states.

Three cross-validation techniques were used to estimate model performance across varying usage scenarios: user-specific, leave-one-trial-out, and leave-one-user-out. User-specific cross-validation trained models on n  − 1 trials for the subject, tested on their remaining trial, and averaged the results after n independent iterations to determine drowsiness detection accuracy for a single subject. Leave-one-trial-out cross-validation trained models on 33 of the recorded trails, tested on the remaining trial, and averaged results after all 34 independent iterations to determine the study’s overall drowsiness detection accuracy. Leave-one-user-out cross-validation trained on recordings from eight subjects, tested on the remaining subject’s recordings, and averaged results after all nine independent iterations. This evaluated detection accuracy when using population training and deploying on a never-before-seen subject. Due to the inherent imbalance between drowsy and alert classes, each classification model employed a balancing scheme where over-represented classes are given a smaller class weight than under-represented classes. In the case of drowsy vs. alert, alert epochs are given a class weight inversely proportional to the number of epochs. This allows classes to be treated more fairly across all training/cross-validation regimes (since they will all have different class balances). During validation, class probabilities returned from the classifier models were filtered with a 3-tap Hamming window FIR filter and thresholded to achieve final binary outputs (Fig.  5b ).

Drowsiness classification results

Alpha modulation ratio.

Alpha waves (8–12 Hz) are a spontaneous neural signal that can reflect a person’s state of relaxation, which makes them an important spectral feature in ExG-based drowsiness classification 15 . A sample recording from a single user demonstrating alpha wave modulation is presented in Fig.  6a . This modulation is clear in the time–frequency spectrogram (Fig.  6a ). To assess the modulation ratio more quantitatively, Fig.  6a also plots the average power across the entire alpha band while the subject opens and closes their eyes every 30 s. The presented sample data’s modulation ratio was 2.001.

a Spectrogram demonstrating alpha modulation when the subject closes their eyes. Alpha bandpower (8–12 Hz put through a 2 s rolling average filter for clarity) is modulated by 4× in amplitude when eyes are closed. b Logistic regression event detection with 10 s feature windows. c Support vector machine event detection with 10 s feature windows. d Random Forest event detection with 10 s feature windows. ( e , f , g ) Drowsiness event detection using 50 s feature windows. Standard Deviation (Std Dev) shown across results from all nine users.

Classifier comparison across validation schemes

The overall average of the user-specific classification results ranged from 77.9% to 92.2% across all models and feature window sizes. In the user-generic leave-one-trial-out case, average classification accuracy was higher and ranged from 91.4% to 93.2% when cross-validating across the 34 trials. This is most likely due to the increased amount of data available for training. Lastly, the leave-one-user-out validation scheme achieved average classification accuracies from 88.1% − 93.3% across all users, window sizes, and models. Figure  6b–g showcases average model accuracy and standard deviation where appropriate.

10 s vs 50 s windows

Two feature windowing schemes were investigated, 10 s (Figs.  6b–d ) and 50 s (Fig.  6e–g ) windows. All training steps, including feature selection, are performed independently. The 10 s feature windows result in significant performance loss in the user-specific validation scheme. For example, the average user-specific logistic regression-based classifier performance increased from 77.9% to 90.8% when increasing feature window sizes to 50 s. Minimal accuracy loss, however, was observed when using leave-one-trial-out and leave-one-user-out validation schemes with features from 10 s windows. This minimal accuracy loss is most likely due to the increased amount of training data available (~30 trials) to the models relative to the user-specific cases where individual models only train on a 1−4 of trials.

Classifier architecture comparison

Three low-complexity machine learning models were used to promote the scalability and usability of the drowsiness detection platform. All models were implemented in Python 3.8 using scikit-learn packages. Logistic regression models were implemented with a stochastic average gradient descent solver. L1 regularization was used to add a penalty equal to the absolute value of the magnitude of the feature coefficients. Support vector machines were implemented with a radial basis function (RBF) kernel to account for data that may not be lineally separable. The trained models utilized a maximum of 400 support vectors and a regularization parameter, C  = 1. Random forest models were implemented with 100 trees and a maximum depth of five to prevent overfitting. These implementations resulted in memory footprints that were estimated using python’s pympler package. The logistic regression, SVM, and RF models required 2.8 kB, 144.2 kB, and 63.8 kB respectively. These memory requirements are well within the capacity of modern microcontroller’s embedded memories (e.g., 32-bit ARM Cortex-M).

Since all three models achieve high accuracy, it is clear that drowsiness is classifiable with in-ear eeg recording. No model shows markedly greater performance or another. The logistic regression model is more computationally efficient, requires significantly less memory, and can be more easily trained/deployed with smaller datasets. It is important to verify that logistic regression continues to perform as well across larger demographics, a topic for future studies.

We have reported the design and fabrication of in-ear dry electrodes along with the assembly and evaluation of a wireless, wearable, in-ear ExG platform for offline drowsiness detection on never-before-seen users. All aspects of this platform can be adapted to different use-cases. The 3D printed and electroless Au-plated electrodes can be rapidly augmented for any anatomically optimized wearable and used/re-used for long periods of time, WANDmini can support multi-day electrophysiological monitoring, and the presented offline classifiers demonstrate the potential for future dry-electrode based brain-state classification. In contrast to other state-of-the-art in-ear recording platforms (Table  2 ), the electrodes, wireless electronics, and lightweight algorithms presented lay the groundwork for future large-scale deployment of user-generic, wireless ear ExG brain-computer interfaces that use multiple machine learning algorithms.

Our results are promising for the development of the next generation of standalone wearables that can monitor brain and muscle activity in work environments and in everyday, public scenarios. To realize these standalone, wireless systems, future work requires integrating these classifiers on-chip for real-time brain-state classification and miniaturizing all the hardware into a pair of earbuds. Furthermore, the hardware would need to support online classification to allow for full-day, itinerant use. Lastly, it would be important to take this miniaturized hardware and implement a user-study with a wider demographic. By monitoring in-ear EEG across individuals aged 18–65+, further age specific models can be investigated. If a monolithic model is unable to classify drowsiness stereotypes across such a large age range, it would be interesting to provide models with context such as age, gender, known sleep disorders, and previous night’s sleep quality. Furthermore, the feature selection performed in this work suggests that simpler calculations such as bandpower ratios are sufficient for drowsiness classification. If this remains the case across larger demographics, then feature extractors can ignore computationally expensive features such as standard deviation, different entropy measures, etc. to reduce power in embedded classification scenarios. With aforementioned integration, a pair of ear ExG buds would significantly enable long term, daily recording ExG without interrupting a user’s day or stigma. These measurements would enable an entirely new era of research for tracking long-term cognitive changes from disorders such as depression, Alzheimer’s, narcolepsy, or stress.

Study approval and ethical consent

The user study, subject recruitment, and all data analysis was approved by UC Berkeley’s Institutional Review Board (CPHS protocol ID: 2018-09-11395). Informed consent was received by all participants in the study for their results to be included in presented figures/data.

Both the electrodes and earpiece were printed with a stereolithography (SLA) 3D printer (Formlabs Form 3 printer) with a standard, clear methacrylate photopolymer (Fig.  2c ). An SLA printer was used due to its increased precision over standard filament deposition modeling (FDM) based printers. In SLA printers, thin layers of photosensitive polymer are cured by a laser. The resulting printed surfaces must be washed and cured in UV to achieve the final 3D part.

The original 3D printed surface is highly anisotropic due to the structure’s uniformly printed layers. To create a more heterogenous surface, electrode structures were sandblasted with 100 grit white fused aluminum oxide blasting media (Industrial Supply, Twin Falls, ID) to remove the regular surface pattern leftover from the printing process while also increasing the effective surface area. The sandblasted samples were then sonicated in a bath of Alconox cleaning solution for ~10 min and rinsed with DI water. Lastly, the electrode structures were treated in a bath of 1% benzalkonium chloride (Sigma Aldrich 12060-100G) surfactant solution for 10 min. These surface treatment steps ensure a clean plating surface with high surface energy and lead to improved catalyst/metal layer adhesion.

The samples are then submersed in catalyst and plating baths. First, the electrodes are submerged in a beaker of palladium-tin catalyst for 10 min followed by a copper plating solution for a minimum of six hours. This initial plating step results in a thick copper layer that will oxidize if left out in ambient atmosphere. As a result, samples would then be quickly rinsed, dried, and placed in a nickel-plating bath for ~10 min (Sigma Aldrich 901630). Afterwards, the electrodes are placed in an electroless gold plating solution for approximately 15 min. In between plating steps, the samples were rinsed with DI water and dried thoroughly.

WANDmini: ExG recording hardware

The WANDmini board contains a neural recording frontend (NMIC), a SoC FPGA with a 166 MHz Advanced RISC Machine (ARM) Cortex-M3 processor (SmartFusion2 M2S060T from Microsemi), and low-energy radio (nRF51822 from Nordic Semiconductor). The SoC FPGA forms a custom-designed 2Mb/s digital signal and clock interface with a single NMIC, aggregates all data and commands into packets, then streams all the packets to the 2Mb/s 2.4 GHz low-energy radio.

WANDmini also contains a 20 MHz crystal oscillator as a clock source, on-board buck converters (TPS6226x from Texas Instruments), a battery charger circuit (LTC4065 from Linear Technology), and a 6-axis accelerometer and gyroscope (MPU-6050 from InvenSense). While WANDmini can record up to 64 channels of electrophysiological data and motion information from the accelerometer, the drowsiness detection application only uses 11 channels for ExG monitoring. Future applications may integrate real-time motion artifact cancellation and classification directly into the WANDmini’s SoC FPGA.

Subject selection and earpiece application

Nine subjects (7 male, 2 female, ages 18–27) volunteered for this study. Subjects were requested not to exercise or drink caffeine before any trial. Prior to the first experiment, subjects tried out small, medium, and large earpieces and selected the pair they felt were most comfortable and secure in ear. During this onboarding session, subjects also familiarized themselves with the GUI.

At the start of the drowsiness trials, subjects were given their preferred ear EEG earbuds to wear, as well as an electronics headband with a fully charged Li-Po battery and the WANDmini recording hardware. To maintain a realistic daily use scenario, the subjects did not clean or prepare their skin and no hydrogel or saline was applied to the earpiece dry electrodes. The trial hosts also did not help subjects don/doff the headband or earpieces unless explicitly requested. After the experiments, the earpieces were cleaned with 70% isopropyl alcohol since they would be later used by other subjects.

Electrophysiological recording setup

Each earpiece has six electrodes, four inside the ear canal and two outside the ear canal. The default recording arrangement employs two contralaterally worn earpieces to maximize spatial coverage and recorded signal power 27 , 39 . These two earpieces provide up to 11 ExG channels with a common reference. Either of the concha cymba electrodes can be used as a reference (the un-used one can be used as an additional sense electrode). After initial experimentation, it was determined that the right concha cymba electrode was sufficient as a reference electrode across all subjects. As a result, each ExG channel is referenced against the right concha cymba electrode in a monopolar montage (electrode Y in Fig.  2a ). A single wet Ag/AgCl electrode was applied to the subject’s right mastoid and connected to battery ground for interference reduction.

Drowsiness trial overview

Subjects participated in multiple drowsiness trials to enable both user-specific and user-generic training. Subjects were not familiar with the ear EEG work when selected. No more than five trials were recorded per subject to maintain a diverse data pool. Prior to the trials, subjects were informed of the study purpose and requested to have a ‘normal night’s rest’ (subjectively) and not drink caffeine prior to the trial. Trials took place in a quiet, indoor office space between 8 a.m. and 5 p.m. when the lights were on. After donning the ear eeg system, the subject was left alone in the trial space until the end of the recording session. During the trial, the subject would sit at a desk in front of a laptop with a custom GUI. Subjects were instructed to only perform the reaction game task and not look at personal devices for the extent of the trial. Subjects were allowed to move their heads, readjust in their seat, and move their arms, but were asked to stay seated during the entire session (to minimize motion artifacts). Each trial was 40–50 min in length and was self-ended by the subject to prevent the interruption of a drowsy event. At the end of the trial, the subjects removed the headband and earpieces themselves. They were instructed to wait at least 24 h before participating in subsequent drowsiness trials to maximize variation between trials.

Label generation

Recording both objective and subjective drowsiness measures made the label generation process robust to user-error momentary distractions (when an alert user looks away from the laptop). Ear ExG samples were labeled as “drowsy” if the user reported a drowsiness Likert item >5 and if their reaction time was more than double the average from the first 5 min of recording. The labels were then passed through a 3-sample rolling average filter and thresholded to achieve a binary label.

Re-referencing and filtering

ExG re-referencing was used to maximize spatial covering across contralateral earpieces. Each in-ear electrode was re-referenced to the left concha cymba electrode and processed with the 11 EEG channels recorded with the right concha cymba electrode. To remove power-line interference (60 Hz in North America) while maintaining as much EEG activity as possible, both the recorded and re-referenced EEG channels were bandpass filtered from 0.05–50 Hz. Filters were implemented with a 5th order butterworth high pass filter (corner of 0.05 Hz) and a 5th order Butterworth low pass filter (corner of 50 Hz). Both filters were implemented in python but can also be implemented with infinite impulse response (IIR) filters with 16 bit registers for use in FPGA/embedded applications.

Data segmentation

Filtered ExG was segmented to remove ExG artifacts related to decision-making and motor planning in response to GUI cues. Each epoch began 10 s after a reaction time cue and ended when the next reaction time cue was provided. When using the maximum window size, features were calculated for these 50 s epochs. When using a reduced window size, each 50 s epoch and its corresponding label were divided into five 10 s windows. To focus classification on drowsiness onset, epochs were considered “sleep” if a subject’s rection time exceeded 10 s. These epochs were excluded from the study.

Feature extraction and selection

Temporal and spectral features were extracted in Python 3.8 from the segmented ExG data. Low-complexity features were calculated for each window of ExG data and across all the recorded and re-referenced channels. Voltage standard deviation and maximum peak-to-peak voltage amplitude were calculated in the time-domain to target eye blink artifacts and motion. Welch’s method (using a 1000-point Fourier transform, 500 sample overlap, and Hamming window) was used to calculate the power spectral density (PSD) and attain frequency characteristics that relate attention and relaxation. The following spectral features were calculated prior to training: maximum PSD, peak frequency, and PSD variance were calculated for δ, θ, α, β, γ EEG bands. Absolute and relative band powers were also calculated for the following bands and ratios: δ, θ, α, β, γ, α/β, θ/β, (α + θ)/β, and (α + θ)/(α + β). Relative bandpower is the specific band relative to the total PSD from 0.5–50 Hz. Furthermore, features of the previous epoch were included to account for changes in ExG activity, since temporal and spectral features relate to characteristics that changes during the onset of drowsiness such as attention and eye movement. A complete table of features used in offline training (prior to feature selection) is in Table  3 .

All features were scaled by subtracting the median and scaling according to their interquartile range. To reduce input feature count, feature selection using an analysis of variance (scikit-learn Python 3.8) was performed to determine the top 20 features (total) that minimize redundancy and maximize class variation during training. Only these 20 features are included during model training and validation. This feature selection also implicitly selected best performing electrodes across users (most likely due to some electrodes fitting better than others). The same feature type was also selected for multiple channels (e.g., the top 20 features would include alpha band power from channels 1, 5, and 10). Contralateral channels (where sense and reference electrodes are in different ears) were always weighted higher than ipsilateral channels. The most used features (in order of importance) are shown in Table  4 .

Spectral features associated with eye movement, relaxation, and drowsiness were the most important for model training. Furthermore, the previous epoch’s features were also generally important. This is corroborated by results from other works on scalp data in refs. 14 , 15 , 79 . All feature extraction was performed in Python using numpy. For implementation into an embedded/FPGA environment, these features can be calculating using a coarse fast-Fourier transform, look-up-tables, and the CORDIC algorithm.

Statistics and reproducibility

No statistical method was used to predetermine sample size. No data were excluded from the analyses. The experiments were not randomized. The investigators were not blinded to allocation during experiments and outcome assessment.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

The Experimental Ear EEG data collected in this study is available at https://github.com/MullerGroup/EarEEG_Drowsiness . Due to IRB restrictions, access may be restricted to any raw EEG data. If there are any issues accessing the repository, please contact [email protected], [email protected] or [email protected]. Example code and a deployable notebook can be found in the GitHub repository. Source data used in all figures are provided with this paper.  Source data are provided with this paper.

Code availability

The source code used for offline model validation and analysis of results is available at https://github.com/MullerGroup/EarEEG_Drowsiness .

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Acknowledgements

The authors thank the Ford University Research Program, Bakar Spark Award, Cortera Neurotechnologies (acq. Nia Therapeutics), and the Berkeley Wireless Research Center sponsors. The authors would also like to thank Prof. Jan Rabaey and team, Miguel Montalban, Andy Yau, Adelson Chua, Justin Doong, Aviral Pandey, and Natalie Tetreault for technical support.

Author information

These authors contributed equally: Ryan Kaveh, Carolyn Schwendeman.

Authors and Affiliations

University of California Berkeley, Berkeley, CA, 94708, USA

Ryan Kaveh, Carolyn Schwendeman, Leslie Pu, Ana C. Arias & Rikky Muller

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Contributions

R.K. developed the earpieces and fabrication techniques. R.K., C.S., and L.P. fabricated all test sensors. C.S. developed and implemented the machine learning algorithms. R.K. and C.S. performed the experiments and analysis. R.M. oversaw all aspects of the research project. A.C.A. and R.M. oversaw the fabrication process development. R.K., C.S., A.C.A., and R.M. wrote and edited the manuscript.

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Correspondence to Ryan Kaveh , Carolyn Schwendeman or Rikky Muller .

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Kaveh, R., Schwendeman, C., Pu, L. et al. Wireless ear EEG to monitor drowsiness. Nat Commun 15 , 6520 (2024). https://doi.org/10.1038/s41467-024-48682-7

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Received : 01 October 2023

Accepted : 09 May 2024

Published : 02 August 2024

DOI : https://doi.org/10.1038/s41467-024-48682-7

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