Deep Convolutional Neural Network For Featureless Electromyogram Pattern Recognition Using Time-Frequency Distribution

Feature extraction is an essential step to extract useful information from electromyogram (EMG) signal in the classification of upper limb movements. However, the process of feature extraction and selection require expert knowledge and experience. Therefore, this paper proposed a new approach for an...

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Bibliographic Details

Main Authors:	Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah, Mohd Ali, Nursabillilah, Tengku Zawawi, Tengku Nor Shuhada
Format:	Article
Language:	en
Published:	American Scientific Publishers 2018
Subjects:	T Technology (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utem.edu.my/id/eprint/23005/2/Deep%20Convolutional%20Neural%20Network%20for%20Featureless%20EMG%20Pattern%20Recognition%20Using%20Time-Frequency%20Distribution.pdf http://eprints.utem.edu.my/id/eprint/23005/ https://www.ingentaconnect.com/content/asp/senlet/2018/00000016/00000002/art00002
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