Enhanced Recognition of Amputated Wrist and Hand Movements by Deep Learning Method Using Multimodal Fusion of Electromyography and Electroencephalography

Motion classification can be performed using biometric signals recorded by electroencephalography (EEG) or electromyography (EMG) with noninvasive surface electrodes for the control of prosthetic arms. However, current single-modal EEG and EMG based motion classification techniques are limited owing...

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Detalles Bibliográficos

Principais autores:	Sehyeon Kim, Dae Youp Shin, Taekyung Kim, Sangsook Lee, Jung Keun Hyun, Sung-Min Park
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2022-01-01
Series:	Sensors
Assuntos:	brain–computer interface (BCI) convolutional neural network (CNN) electroencephalography (EEG) electromyography (EMG) transforearm amputees transfer learning (TL)
Acceso en liña:	https://www.mdpi.com/1424-8220/22/2/680
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