Design of a wireless multi-channel surface EMG signal acquisition system

2017 ◽  
Author(s):  
Rong Zhou ◽  
Qiang Luo ◽  
Xiaorong Feng ◽  
Chenglong Li
Keyword(s):  
Surface Emg ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Emg Signal ◽  
Channel Surface ◽  
Surface Emg Signal

scholarly journals Surface EMG Signal Acquisition Analysis and Classification for the Operation of a Prosthetic Limb

2018 ◽  
Vol 8 (1) ◽  
pp. 32-41
Author(s):  
Kasun Samarawickrama ◽  
◽  
Sadun Ranasinghe ◽  
Yasoja Wickramasinghe ◽  
Wageesha Mallehevidana ◽  
...  
Keyword(s):  
Surface Emg ◽  
Signal Acquisition ◽  
Prosthetic Limb ◽  
Emg Signal ◽  
Surface Emg Signal

Classification of Surface Electromyogram Signals Acquired from the Forearm of a Healthy Volunteer

2016 ◽  
pp. 315-333
Author(s):  
Uvanesh K. ◽  
Suraj Kumar Nayak ◽  
Biswajeet Champaty ◽  
Goutam Thakur ◽  
Biswajit Mohapatra ◽  
...  
Keyword(s):  
Neural Network ◽  
Surface Emg ◽  
Acquisition System ◽  
Discrete Wavelet ◽  
Signal Acquisition ◽  
Semg Signal ◽  
Emg Signal ◽  
Flexor Carpi Ulnaris ◽  
Artificial Neural Network Ann

Surface EMG (sEMG) signals from the palmaris longus, flexor carpi radialis and flexor carpi ulnaris muscles were recorded using an in-house developed EMG signal acquisition system. The bandwidth of the acquisition system was 1500 Hz. The extracted sEMG signal was processed using Discrete Wavelet Transform (DWT). The features of the extracted and the wavelet processed signals were determined and were used for probable classification using Artificial Neural Network (ANN). A classification efficiency of more than 90% was achieved using ANN classifiers. The results suggested that the sEMG may be successfully used for designing efficient control system.

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