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In the process of identification of Amyotrophic Lateral Sclerosis (ALS) which is a motor neuron disorder, extraction of feature is the most important step. In this work normal and ALS class for identification and monitoring have been included. Analysis of surface electromyography (sEMG) signal for ALS identification using discrete wavelet transform is most simple and powerful method being used all over the world. Time domain parameters, like Zero Crossing Rate (ZCR) and Root Mean Square (RMS) and frequency domain parameters like Mean Frequency (MF) and Waveform Length (WL) are considered. Threshold values for the above mentioned parameters are calculated for both the normal and ALS classes. Discrete Wavelet Transform (DWT) parameters are considered and their threshold values are also calculated for both normal and ALS classes. Surface EMG (sEMG) signal database of normal and ALS patients for both male and female is considered.
Archana Bhaskarrao Sonone. 2017. \u201cDWT based Identification of Amyotrophic Lateral Sclerosis Using Surface EMG Signal\u201d. Global Journal of Medical Research - F: Diseases GJMR-F Volume 17 (GJMR Volume 17 Issue F2): .
Crossref Journal DOI 10.17406/gjmra
Print ISSN 0975-5888
e-ISSN 2249-4618
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Total Score: 101
Country: India
Subject: Global Journal of Medical Research - F: Diseases
Authors: Archana Bhaskarrao Sonone (PhD/Dr. count: 0)
View Count (all-time): 182
Total Views (Real + Logic): 3411
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Publish Date: 2017 08, Mon
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In the process of identification of Amyotrophic Lateral Sclerosis (ALS) which is a motor neuron disorder, extraction of feature is the most important step. In this work normal and ALS class for identification and monitoring have been included. Analysis of surface electromyography (sEMG) signal for ALS identification using discrete wavelet transform is most simple and powerful method being used all over the world. Time domain parameters, like Zero Crossing Rate (ZCR) and Root Mean Square (RMS) and frequency domain parameters like Mean Frequency (MF) and Waveform Length (WL) are considered. Threshold values for the above mentioned parameters are calculated for both the normal and ALS classes. Discrete Wavelet Transform (DWT) parameters are considered and their threshold values are also calculated for both normal and ALS classes. Surface EMG (sEMG) signal database of normal and ALS patients for both male and female is considered.
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