Multiday EMG-Based Classification of Hand Motions with Deep Learning Techniques

Pattern recognition of electromyography (EMG) signals can potentially improve the performance of myoelectric control for upper limb prostheses with respect to current clinical approaches based on direct control. However, the choice of features for classification is challenging and impacts long-term...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 18; no. 8; p. 2497
Main Authors:	Zia ur Rehman, Muhammad, Waris, Asim, Gilani, Syed Omer, Jochumsen, Mads, Niazi, Imran Khan, Jamil, Mohsin, Farina, Dario, Kamavuako, Ernest Nlandu
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 01.08.2018 MDPI
Subjects:	Adult Artificial Limbs autoencoders Classification convolutional neural networks Deep Learning Discriminant analysis Electromyography Electromyography - methods Female Hand - physiology Humans Male multiday classification MYO band myocontrol Neural networks pattern recognition Young Adult autoencoders MYO band electromyography convolutional neural networks multiday classification myocontrol pattern recognition
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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