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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/7071
Title: An efficient method for analysis of EMG signals using improved empirical mode decomposition
Authors: Mishra V.K.
Bajaj V.
Kumar A.
Sharma D.
Singh, Girish Kumar
Published in: AEU - International Journal of Electronics and Communications
Abstract: In this paper, a simple technique with improved empirical mode decomposition (IEMD) in conjunction with four different features is used for the analysis of amyotrophic lateral sclerosis (ALS) and normal EMG signals. EMG signals consist of noise from various sources, such as electronic instruments, moving artifacts and electrical instruments. The empirical mode decomposition (EMD) method followed by median filter (MF) has been employed to remove the impulsive noise from intrinsic mode function (IMF) components generated through EMD. The filtered IMF components are summed together to generate a new signal. EMD process is further applied to new EMG signal to generate improved IMFs called as improved EMD method. In the IEMD algorithm for the first time, a new technique is proposed to choose the window size of median filter. For this, the features namely amplitude modulation bandwidth (BAM), frequency modulation bandwidth (BFM), spectral moment of power spectral density (SMPSD), and first derivative of instantaneous frequency (MFDIF) extracted from the improved IMFs are used to discriminate between ALS and normal EMG signals. Finally, it is observed that IEMD method increases the discrimination ability of these features as compared to the EMD method and the adaptively fast ensemble empirical mode decomposition (AFEEMD) method. © 2016 Elsevier GmbH
Citation: AEU - International Journal of Electronics and Communications (2017), 72(): 200-209
URI: https://doi.org/10.1016/j.aeue.2016.12.008
http://repository.iitr.ac.in/handle/123456789/7071
Issue Date: 2017
Publisher: Elsevier GmbH
Keywords: Amyotrophic lateral sclerosis (ALS)
Electromyography (EMG)
Improved empirical mode decomposition (IEMD)
Impulsive noise
Median filter
ISSN: 14348411
Author Scopus IDs: 57191228384
57209289122
57215268681
57002098800
57193351909
Author Affiliations: Mishra, V.K., Department of Electronics and Communication Engineering, PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur, India
Bajaj, V., Department of Electronics and Communication Engineering, PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur, India
Kumar, A., Department of Electronics and Communication Engineering, PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur, India
Sharma, D., Department of Electronics and Communication Engineering, PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur, India
Singh, G.K., Department of Electrical Engineering, Indian Institute Technology, Roorkee, India
Corresponding Author: Bajaj, V.; Department of Electronics and Communication Engineering, PDPM Indian Institute of Information Technology, Design and Manufacturing JabalpurIndia; email: bajajvarun056@yahoo.co.in
Appears in Collections:Journal Publications [EE]

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