A dynamic and self-adaptive classification algorithm for motor imagery EEG signals

•A high accuracy motor imagery based BCI algorithm is proposed.•Spatial and spectral features of EEG signals related to left and right hand movements are extracted and classified using many algorithms.•A novel dynamic and self-adaptive algorithm (DSAA) based on the least-squares method is proposed t...

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Veröffentlicht in:	Journal of neuroscience methods Jg. 327; S. 108346
Hauptverfasser:	Belwafi, Kais, Gannouni, Sofien, Aboalsamh, Hatim, Mathkour, Hassan, Belghith, Abdelfattah
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.11.2019
Schlagworte:	Brain–computer interface (BCI) dynamic classification Electroencephalography (EEG) motor imagery voting technique motor imagery Electroencephalography (EEG) voting technique dynamic classification Brain–computer interface (BCI)
ISSN:	0165-0270, 1872-678X, 1872-678X
Online-Zugang:	Volltext
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