The classification of EEG-based wink signals: A CWT-Transfer Learning pipeline

The classification of EEG-based wink signals: A CWT-Transfer Learning pipeline

Brain–Computer Interface technology plays a vital role in facilitating post-stroke patients’ ability to carry out their daily activities of living. The extraction of features and the classification of electroencephalogram (EEG) signals are pertinent parts in enabling such a system. This research inv...

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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: Article
Language:English
Published: Elsevier 2021
Subjects:
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/30701/
http://umpir.ump.edu.my/id/eprint/30701/2/The%20classification%20of%20EEG-based%20wink%20signals.pdf

Internet

http://umpir.ump.edu.my/id/eprint/30701/
http://umpir.ump.edu.my/id/eprint/30701/2/The%20classification%20of%20EEG-based%20wink%20signals.pdf

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