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Design of a Low Cost EEG Headset for Educational Research

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Student Division Technical Session 2

Tagged Division

Student

Page Count

20

DOI

10.18260/1-2--36917

Permanent URL

https://peer.asee.org/36917

Download Count

432

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Paper Authors

biography

Kevin Zhu University of Toronto

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Kevin Zhu is an undergraduate student at the University of Toronto pursuing his Bachelor of Applied Science in Engineering Science. He is interested in brain-computer interfaces and how they can be applied to various aspects of life and society.

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Aoran Jiao University of Toronto

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Aoran Jiao is an undergraduate student at the Division of Engineering Science at the University of Toronto. He has a wide array of research interests including engineering education, software development, machine intelligence, and biomedical engineering.

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Xinyue (Crystal) Liu University of Toronto

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Crystal Liu is a graduate student at the University of Toronto in the department of Materials Science and Engineering. Her research focuses on engineering design and education. She obtained her BASc in Mechanical Engineering at the University of Toronto in 2019. She has worked in product development and is interested in application of technology and design in engineering education research.

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Scott Ramsay P.Eng. University of Toronto

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Scott Ramsay is an Associate Professor, Teaching Stream in the department of Materials Science and Engineering at the University of Toronto, in Toronto, Canada, and a registered professional engineer in Ontario. Scott earned his PhD in Materials Science and Engineering from the University of Toronto. Scott's current primary academic interests are in improving the quality of undergraduate engineering education through the use of various reusable learning objects. Scott has taught extensively in Material Science, teaching courses ranging from introductory materials science to thermodynamics, diffusion, materials selection, manufacturing, biomaterials, and building science.

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Abstract

Electroencephalography signals are used widely in medical and pedagogical research because they quantitatively and non-invasively reflect brain activity. However, commercially available EEG devices are often either prohibitively expensive, or do not offer the correct capabilities such as enough electrodes. This work-in-progress study aims to address this gap through the design of a low-cost, easy-to-use, and effective EEG headset for engineering educational research studies.

The current study includes a relatively small sample size (N=6); however, it does identify some preliminary trends. For example, although most participants found the authors’ current design to be more comfortable than commercially available designs, the design also had a much larger range of reported comfort levels. Additionally, no distinct conclusion could be drawn from the signal quality comparison between the current design and the commercial device due to limited sample size and large variation among collected data. This exploratory study provides a framework for future studies when more data could be collected. There is potential for such a device to provide insight into learner behavior in the remote learning environment due to its lower cost, light weight, and small size.

Zhu, K., & Jiao, A., & Liu, X. C., & Ramsay, S. (2021, July), Design of a Low Cost EEG Headset for Educational Research Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36917

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