Portable EMG Data Acquisition Module for Upper Limb Prosthesis Application

Electromyography (EMG) signals are gaining popularity to develop the prosthetics. In this paper, an efficient multi-channel EMG signal acquisition system has been proposed for upper limb prosthetic application. Various arm exercises have been performed to obtain EMG signals from five different arm m...

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Bibliographic Details
Published inIEEE sensors journal Vol. 18; no. 8; pp. 3436 - 3443
Main Authors Pancholi, Sidharth, Joshi, Amit M.
Format Journal Article
LanguageEnglish
Published IEEE 15.04.2018
Subjects
Acquisition
classification
Electrodes
Electromyography
Feature extraction
k-NN
LDA
Muscles
prosthetic
Prosthetics
QDA
sEMG
Skin
SVM
Wrist
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Summary:Electromyography (EMG) signals are gaining popularity to develop the prosthetics. In this paper, an efficient multi-channel EMG signal acquisition system has been proposed for upper limb prosthetic application. Various arm exercises have been performed to obtain EMG signals from five different arm muscles for the validation of developed hardware. The muscle's position has been selected by palpation method. Furthermore, the classification algorithms have been examined for seven different activities. Total 29 subjects have been chosen (25 intact and four Amputees) to acquire the EMG data by these activities. To classify the recorded EMG data set, nine time domain and seven frequency domain features have been extracted. A comparative analysis of different classifiers is presented for different muscle position of electrodes. The signal processing and classification algorithms have been processed in MATLAB 2016a. The accuracy of classification ranges for different classification algorithms from 57.69% to 99.92% for all subjects.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2018.2809458