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The classification of electrooculography signals: A significant feature identification via mutual information

Stroke is currently known as the third most frequent reason for disability worldwide where the quality of life of its survivors in terms of their daily functioning is seriously affected. Brain-Computer Interface (BCI) is a system that can acquire and transform brain activity into readable outputs. T...

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Bibliographic Details
Main Authors: Hwa, Phua Jia, Mahendra Kumar, Jothi Letchumy, 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 2022
Subjects:
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/33359/1/The%20classification%20of%20electrooculography%20signals-%20A%20significant.pdf
http://umpir.ump.edu.my/id/eprint/33359/
https://doi.org/10.1007/978-981-33-4597-3_92
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http://umpir.ump.edu.my/id/eprint/33359/1/The%20classification%20of%20electrooculography%20signals-%20A%20significant.pdf
http://umpir.ump.edu.my/id/eprint/33359/
https://doi.org/10.1007/978-981-33-4597-3_92

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