Finger rehabilitation training and evaluation system based on EEG signals, machine learning and Fugl-Meyer scale

For patients with digital hemiplegia caused by stroke, equipment such as mechanical exoskeleton devices are currently used to help recovery, but they are limited to many shortcomings of this method. This paper proposes to collect electroencephalogram(EEG) information through brain-computer interface...

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Veröffentlicht in:	Journal of physics. Conference series 2022-12, Vol.2395 (1), p.12060
Hauptverfasser:	Liang, Xiaohu, Zhao, Qicheng, Liang, Junming
Format:	Artikel
Sprache:	eng
Schlagworte:	Deep learning Electroencephalography Exoskeletons Feature extraction Human-computer interface Machine learning Physics Recovery Rehabilitation Training
Online-Zugang:	Volltext
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