NDLI: Analysis of ALS and normal EMG signals based on empirical mode decomposition

Content Provider	IET Digital Library
Author	Mishra, Vipin K. Bajaj, Varun Kumar, Anil Singh, Girish Kumar
Abstract	Electromyogram (EMG) signals contain a lot of information about the neuromuscular diseases like amyotrophic lateral sclerosis (ALS). ALS progressively degenerates the motor neurons in spinal cord. In this study, a new technique for the analysis of normal and ALS EMG signals is proposed. EMG signals are decomposed into narrow band intrinsic mode functions (IMFs) by using empirical mode decomposition (EMD) technique. The area of complex plot, two bandwidths namely amplitude modulation bandwidth (B AM) and frequency modulation bandwidth (B FM), normalised instantaneous frequency (IF n ), spectral momentum of power spectral density (SMPSD) and mean of first derivative of instantaneous frequency (MFDIF) are extracted from analytic IMFs obtained by EMD technique. These six features are used as input in least square support vector machine classifier for the classification of ALS and normal EMG signals. Experimental results and comparative analysis show that classification performance of the proposed method is better than other existing method in the same database.
Starting Page	963
Ending Page	971
Page Count	9
ISSN	17518822
Volume Number	10
e-ISSN	17518830
Issue Number	Issue 8, Nov (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-smt/10/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-smt.2016.0208
Journal	IET Science, Measurement & Technology
Publisher Date	2016-11-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	ALS Analysis Amplitude Modulation Amplitude Modulation Bandwidth Amyotrophic Lateral Sclerosis Bioelectric Signal Biology And Medical Computing Decomposition Digital Signal Processing Diseases Electrodiagnostics And Other Electrical Measurement Technique Electromyogram Signal Electromyography EMD Technique Empirical Mode Decomposition Frequency Modulation Frequency Modulation Bandwidth IMF Interpolation And Function Approximation Knowledge Engineering Technique Least Square Support Vector Machine Classifier Least Squares Approximation Medical Signal Processing Modulation And Coding Method Motor Neuron Degeneration Narrow Band Intrinsic Mode Function Neuromuscular Disease Neurophysiology Normal EMG Signal Analysis Normalised Instantaneous Frequency Numerical Analysis Numerical Approximation And Analysis Power Spectral Density Signal Classification Signal Processing And Detection Spectral Momentum Spinal Cord Support Vector Machine
Content Type	Text
Resource Type	Article
Subject	Atomic and Molecular Physics, and Optics Electrical and Electronic Engineering

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