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A Study of Optimized EEG Signal Induction/Extraction Techniques for Basic Motion Control of Personal Robots for Physically Impaired Users

A Study of Optimized EEG Signal Induction/Extraction Techniques for Basic Motion Control of Personal Robots for Physically Impaired Users

JeongHoon Shin, DongJun Lee
Copyright: © 2021 |Volume: 9 |Issue: 3 |Pages: 12
ISSN: 2166-7160|EISSN: 2166-7179|EISBN13: 9781799862789|DOI: 10.4018/IJSI.2021070106
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MLA

Shin, JeongHoon, and DongJun Lee. "A Study of Optimized EEG Signal Induction/Extraction Techniques for Basic Motion Control of Personal Robots for Physically Impaired Users." IJSI vol.9, no.3 2021: pp.79-90. http://doi.org/10.4018/IJSI.2021070106

APA

Shin, J. & Lee, D. (2021). A Study of Optimized EEG Signal Induction/Extraction Techniques for Basic Motion Control of Personal Robots for Physically Impaired Users. International Journal of Software Innovation (IJSI), 9(3), 79-90. http://doi.org/10.4018/IJSI.2021070106

Chicago

Shin, JeongHoon, and DongJun Lee. "A Study of Optimized EEG Signal Induction/Extraction Techniques for Basic Motion Control of Personal Robots for Physically Impaired Users," International Journal of Software Innovation (IJSI) 9, no.3: 79-90. http://doi.org/10.4018/IJSI.2021070106

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Abstract

When interfaces utilizing EEG signals are used, these signals can be induced through diverse association techniques. In the present article, differences in recognition performance of the systems related to robot control techniques according to diverse association techniques have been analyzed. For this purpose, elements that can affect the performance other than association techniques were excluded as much as possible, and the focus was placed on the performance analysis per association technique. According to the study results of the present article, the movement association technique based on gestures showed the highest recognition performance in the robot control system for multiple users. In the robot control system for single users, hearing-based phonation association is considered to show the highest recognition performance. In the study results of the present article, superior recognition performance is considered to be derived than the recognition performance displayed by existing systems when applied to the robot control area utilizing EEG signals.

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