A New method for Improvement of the Accuracy of Character Recognition in P300 Speller System: Optimization of Channel Selection by Using Recursive Channel Elimination Algorithm Based on Deep Learning

A New method for Improvement of the Accuracy of Character Recognition in P300 Speller System: Optimization of Channel Selection by Using Recursive Channel Elimination Algorithm Based on Deep Learning

<strong><em>Background and purpose:</em></strong>P300 speller is a kind of Brain-Computer Interface (BCI) system in which the user may type words by using the responses obtained from human focus on different characters. The high sensitivity of brain signals against noise in p...

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Bibliographic Details
Main Authors: Seyed Vahab Shojaedini, Maryam Adeli
Format: Article
Language:English
Published: Shiraz University of Medical Sciences 2020-01-01
Series:Journal of Health Management & Informatics
Subjects:
p300 speller
brain-computer interface
channel selection
optimization
deep learning
recursive channel elimination
convolutional neural network
Online Access:http://jhmi.sums.ac.ir/article_46627_d11628e432333abe6af03ec0ad1d4139.pdf

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