A Boosting-Based Spatial-Spectral Model for Stroke Patients' EEG Analysis in Rehabilitation Training

Studies have shown that a motor imagery electro encephalogram (EEG)-based brain-computer interface (BCI) system can be used as a rehabilitation tool for stroke patients. Efficient classification of EEG from stroke patients is fundamental in the BCI-based stroke rehabilitation systems. One of the mos...

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Veröffentlicht in:	IEEE transactions on neural systems and rehabilitation engineering Jg. 24; H. 1; S. 169 - 179
Hauptverfasser:	Liu, Ye, Zhang, Hao, Chen, Min, Zhang, Liqing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithms Boosting Brain modeling brain-computer interface (BCI) Brain-Computer Interfaces Channels Classification Competition Computer Simulation Diagnosis, Computer-Assisted - methods Electroencephalography Electroencephalography - methods Evoked Potentials, Motor - physiology Feature extraction Frequency bands Human-computer interface Humans Imagination - physiology Models, Neurological Models, Statistical Motor Cortex - physiology Patients Pattern Recognition, Automated - methods Rehabilitation Reproducibility of Results Sensitivity and Specificity spatial-spectral analysis Spatio-Temporal Analysis Stochastic processes Stroke Stroke - diagnosis Stroke - physiopathology Stroke Rehabilitation Strokes Training
ISSN:	1534-4320, 1558-0210, 1558-0210
Online-Zugang:	Volltext
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