The classification of wink-based eeg signals by means of transfer learning models
Stroke is one of the dominant causes of impairme nt. An estimation of half post-stroke survivors suffer from a severe motor or cognitive deterioration, that affects the functionality of the affected parts of the body, which in turn, prevents the patients from carrying out Activities of Daily Living...
Saved in:
Main Author: | Jothi Letchumy, Mahendra Kumar |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/34356/1/The%20classification%20of%20wink-based%20eeg.pdf http://umpir.ump.edu.my/id/eprint/34356/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
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 EEG-based winking signals: a transfer learning and random forest pipeline
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021) -
The classification of EEG-based wink signals: A CWT-Transfer Learning pipeline
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021) -
An evaluation of different fast fourier transform - transfer learning pipelines for the classification of wink-based EEG signals
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2020) -
The Classification of Wink-Based EEG Signals: The Identification of Significant Time-Domain Features
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021)