An evaluation of different fast fourier transform - transfer learning pipelines for the classification of wink-based EEG signals
Brain Computer-Interfaces (BCI) offers a means of controlling prostheses for neurological disorder patients, primarily owing to their inability to control such devices due to their inherent physical limitations. More often than not, the control of such devices exploits the use of Electroencephalogra...
Saved in:
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: |
Penerbit UMP
2020
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/30700/2/An%20Evaluation%20of%20Different%20Fast%20Fourier%20Transform%20-%20Transfer%20Learning%20Pipelines%20for%20the%20Classification%20of%20Wink-based%20EEG%20Signals.pdf http://umpir.ump.edu.my/id/eprint/30700/ https://journal.ump.edu.my/mekatronika/article/view/5939/1099 https://doi.org/10.15282/mekatronika.v2i1.4881 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The classification of EEG-based wink signals: A CWT-Transfer Learning pipeline
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021) -
The classification of EEG-based winking signals: a transfer learning and random forest pipeline
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021) -
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 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) -
The classification of wink-based eeg signals by means of transfer learning models
by: Jothi Letchumy, Mahendra Kumar
Published: (2021)