The classification of blinking: an evaluation of significant time-domain features
Stroke is one of the most widespread causes of disability-adjusted life-years (DALYs). EEG-based Brain-Computer Interface (BCI) system is a potential solution for the patients to help them regain their mobility. The study aims to classify eye blinks through features extracted from time-domain EEG si...
Saved in:
Main Authors: | Kai, Gavin Lim Jiann, Mahendra Kumar, Jothi Letchumy, Rashid, Mamunur, Rabiu Muazu, Musa, Mohd Azraai, Mohd Razman, Norizam, Sulaiman, Rozita, Jailani, Abdul Majeed, Anwar P. P. |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
Springer
2022
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/33325/1/The%20classification%20of%20blinking-%20an%20evaluation.pdf http://umpir.ump.edu.my/id/eprint/33325/ https://doi.org/10.1007/978-981-33-4597-3_91 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The Classification of Wink-Based EEG Signals: The Identification of Significant Time-Domain Features
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021) -
The Classification of Hallucination: The Identification of Significant Time-Domain EEG Signals
by: Chin, Hau Lim, et al.
Published: (2022) -
The classification of electrooculography signals: A significant feature identification via mutual information
by: Hwa, Phua Jia, et al.
Published: (2022) -
The identification of significant mechanomyography time-domain features for the classification of knee motion
by: Said Mohamed, Tarek Mohamed Mahmoud, et al.
Published: (2021) -
The Classification of Wink-Based EEG Signals: The identification on efficiency of transfer learning models by means of kNN classifier
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021)