About: Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery-based Brain-Machine Interfaces

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type	http://eprints.org/ontology/ArticleEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #88354 Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery-based Brain-Machine Interfaces
sameAs	Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery-based Brain-Machine Interfaces
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dc:hasVersion	Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery-based Brain-Machine Interfaces (PDF) Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery-based Brain-Machine Interfaces (PDF)
Title	Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery-based Brain-Machine Interfaces
described by	https://demo.openlinksw.com/about/id/entity/https/www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
Date	2021-07-17
Creator	Ki Jun Yu Young C Jang Panote Siriaraya Shinjae Kwon Kyowon Kang Otkhmezuri, Boris Jeongmoon Choi Yun-Soung Kim Chee Siang Ang Woon-Hong Yeo Musa Mahmood
status	peer reviewed published
Publisher	Wiley
abstract	Motor imagery offers an excellent opportunity as a stimulus-free paradigm for brain-machine interfaces. Conventional electroencephalography (EEG) for motor imagery requires a hair cap with multiple wired electrodes and messy gels, causing motion artifacts. Here, we introduce a wireless scalp electronic system with virtual reality for real-time, continuous classification of motor imagery brain signals. This low-profile, portable system integrates imperceptible microneedle electrodes and soft wireless circuits. Virtual reality addresses subject variance in detectable EEG response to motor imagery by providing clear, consistent visuals and instant biofeedback. The wearable soft system offers advantageous contact surface area and reduced electrode impedance density, resulting in significantly enhanced EEG signals and classification accuracy. The combination with convolutional neural network-machine learning provides a real-time, continuous motor imagery-based brain-machine interface. With four human subjects, the scalp electronic system offers a high classification accuracy (93.22±1.33% for four classes), allowing wireless, real-time control of a virtual reality game.
Is Part Of	Advanced Science https://kar.kent.ac.uk/id/repository
Subject	Q Science QA76.9.H85 Human computer interaction
list of authors	https://kar.kent.ac.uk/id/eprint/88354#authors
is topic of	https://www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #88354 Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery-based Brain-Machine Interfaces

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