Improvement of Classification Accuracy of Four-Class Voluntary-Imagery fNIRS Signals using Convolutional Neural Networks

Improvement of Classification Accuracy of Four-Class Voluntary-Imagery fNIRS Signals using Convolutional Neural Networks

Multiclass functional Near-Infrared Spectroscopy (fNIRS) signal classification has become a convenient way for optical brain-computer interface. fNIRS signal classification with high accuracy is a challenging assignment while the signals are produced by means of voluntary and imagery movements of th...

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Bibliographic Details
Main Authors: Md. Mahmudul Haque Milu, Md. Asadur Rahman, Mohd Abdur Rashid, Anna Kuwana, Haruo Kobayashi
Format: Article
Language:English
Published: D. G. Pylarinos 2023-04-01
Series:Engineering, Technology & Applied Science Research
Subjects:
fNIRS
voluntary and imagery fNIRS signal
classification accuracy
conventional classifiers
Convolutional Neural Network (CNN)
Online Access:https://etasr.com/index.php/ETASR/article/view/5703

Internet

https://etasr.com/index.php/ETASR/article/view/5703

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