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The Classification of Wink-Based EEG Signals: The Identification of Significant Time-Domain Features

Brain-Computer Interface (BCI) has become popular with physically challenged individuals, particularly in enhancing their activities of daily living. Electroencephalogram (EEG) signals are used to control BCI-based devices. Nonetheless, it is worth noting that the use of a multitude of features may...

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Bibliographic Details
Main Authors: Jothi Letchumy, Mahendra Kumar, Rashid, Mamunur, Musa, Rabiu Muazu, Mohd Azraai, Mohd Razman, Norizam, Sulaiman, Rozita, Jailani, Anwar, P. P. Abdul Majeed
Format: Conference or Workshop Item
Language:English
Published: Springer, Singapore 2021
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/30699/1/The%20Classification%20ofWink-Based%20EEG%20Signals1.pdf
http://umpir.ump.edu.my/id/eprint/30699/
https://doi.org/10.1007/978-981-15-7309-5_28
https://doi.org/10.1007/978-981-15-7309-5_28
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http://umpir.ump.edu.my/id/eprint/30699/1/The%20Classification%20ofWink-Based%20EEG%20Signals1.pdf
http://umpir.ump.edu.my/id/eprint/30699/
https://doi.org/10.1007/978-981-15-7309-5_28
https://doi.org/10.1007/978-981-15-7309-5_28

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