EMG Signal Analysis Using Intrinsic Mode Functions to Discriminate Upper Limb Movements

In this modern era analysis of sEMG (Surface Electromyography) signals plays a supreme task in the areas of human-machine interaction, diagnosing neuromuscular disorders, rehabilitation, and numerous relevant applications. EMG demonstrates the electrical activity during the contraction of the skelet...

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Bibliographic Details
Published inThe ... CSI International Symposium on Artificial Intelligence & Signal Processing (Online) pp. 1 - 3
Main Authors Karuna, M., Guntur, Sitaramanjaneya Reddy
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2020
Subjects
Artificial intelligence
discrimination
Electrodes
Electromyography
EMD
Empirical mode decomposition
Feature extraction
Muscles
Wrist
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ISBN9781728144566
1728144566
ISSN2640-5768
DOI10.1109/AISP48273.2020.9073313

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Summary:In this modern era analysis of sEMG (Surface Electromyography) signals plays a supreme task in the areas of human-machine interaction, diagnosing neuromuscular disorders, rehabilitation, and numerous relevant applications. EMG demonstrates the electrical activity during the contraction of the skeletal muscle. Purpose of this research is to distinguish the various muscle responses of the forearm with Empirical Mode Decomposition (EMD) and calculated Time-domain (TD) features of 10 intact subjects' benchmark EMG data base called Ninapro, in which database-2 has been used for identifying the basic wrist movements.
ISBN:9781728144566
1728144566
ISSN:2640-5768
DOI:10.1109/AISP48273.2020.9073313