MOTOR IMAGERY EEG SIGNAL PROCESSING AND CLASSIFICATION USING MACHINE LEARNING APPROACH

MOTOR IMAGERY EEG SIGNAL PROCESSING AND CLASSIFICATION USING MACHINE LEARNING APPROACH

Typically, people with severe motor disabilities have limited opportunities to socialize. Brain-Computer Interfaces (BCIs) can be seen as a hope of restoring freedom to immobilized individuals. Motor imagery (MI) signals recorded via electroencephalograms (EEGs) are the most convenient basis for des...

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Bibliographic Details
Main Authors: S. R. Sreeja, Debasis Samanta, Pabitra Mitra, Monalisa Sarma
Format: Article
Language:English
Published: Scientific Research Support Fund of Jordan (SRSF) and Princess Sumaya University for Technology (PSUT) 2018-08-01
Series:Jordanian Journal of Computers and Information Technology
Subjects:
Motor imagery
Brain computer interface
Electroencephalography
Feature extraction
Feature selection
Machine learning
Online Access:http://jjcit.org/Volume%2004,%20Number%2002/1-DOI%2010.5455-jjcit.71-1512555333.pdf

Internet

http://jjcit.org/Volume%2004,%20Number%2002/1-DOI%2010.5455-jjcit.71-1512555333.pdf

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