Title :
Frequency based EMG power spectrum analysis of Salat associated muscle contraction
Author :
Farzana Khanam;Mohiuddin Ahmad
Author_Institution :
Department of Biomedical Engineering, Khulna University of Engineering & Technology (KUET), 9203, Bangladesh
Abstract :
Mean frequency (MNF) based EMG power spectrum analysis is presented to determine Salat associated muscle fatigue and indices. The main complexity of the parameter is a non-linear relationship between muscle fatigue and feature value, especially in large muscle and in cyclic dynamic contraction which is solved by this proposal. By this work, we can compute frequency dependent MNF for dynamic contractions and relaxations. Through Acknowledge software, FB-MNF is calculated and compared with the standard MNF. The results demonstrate that mean parameter of selected FB-MNF has a better linear relationship with muscle contraction compared to the others for different subjects. In addition, it has been observed through analysis of variance (ANOVA), compared to the traditional methods and have a significant difference (p<;0.05) between feature values among the MNF signal data of EMG power spectrum for different subjects. Furthermore, we have computed Mean Power (MNP), Total Power (TTP) and Peak Frequency (PKF) to determine both muscle load and muscle fatigue indices.
Keywords :
"Muscles","Electromyography","Fatigue","Feature extraction","Force","Analysis of variance","Frequency-domain analysis"
Conference_Titel :
Electrical & Electronic Engineering (ICEEE), 2015 International Conference on
Print_ISBN :
978-1-5090-1939-7
DOI :
10.1109/CEEE.2015.7428245