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Title:Analysis of neuromuscular disorders using statistical and entropy metrics on surface EMG
Authors:ID Istenič, Rok (Author)
ID Kaplanis, Prodromos A. (Author)
ID Pattichis, Constantinos S. (Author)
ID Zazula, Damjan (Author)
Files:URL http://www.wseas.us/e-library/transactions/signal/2008/25-301.pdf
 
Language:English
Work type:Unknown
Typology:1.01 - Original Scientific Article
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:This paper introduces the surface electromyogram (EMG) classification system based on statistical and entropy metrics. The system is intended for diagnostic use and enables classification of examined subject as normal, myopathic or neuropathic, regarding to the acquired EMG signals. 39 subjects in total participated in the experiment, 19 normal, 11 myopathic and 9 neuropathic. Surface EMG was recorded using 4-channel surface electrodes on the biceps brachii muscle at isometric voluntary contractions. The recording time was only 5 seconds long to avoid muscle fatigue, and contractions at fiveforce levels were performed, i.e. 10, 30, 50, 70 and 100 % of maximal voluntary contraction. The feature extraction routine deployed the wavelet transform and calculation of the Shannon entropy across all the scales in order to obtain a feature set for each subject. Subjects were classified regarding the extracted features using three machine learning techniques, i.e. decision trees, support vector machines and ensembles of support vector machines. Four 2-class classifications and a 3-class classification were performed. The scored classification rates were the following: 64+-11% for normal/abnormal, 74+-7% for normal/myopathic, 79+-8% for normal/neuropathic, 49+-20% for myopathic/neuropathic, and 63+-8% for normal/myopathic/neuropathic.
Keywords:surface electromyography, neuromuscular disorders, neuropathy, myopathy, EMG signals, signal processing, wavelet transform, metrics
Year of publishing:2008
PID:20.500.12556/DKUM-26207 New window
UDC:621.391:61
ISSN on article:1790-5052
COBISS.SI-ID:12385046 New window
NUK URN:URN:SI:UM:DK:KIY0RC7I
Publication date in DKUM:31.05.2012
Views:2001
Downloads:46
Metadata:XML DC-XML DC-RDF
Categories:Misc.
:
ISTENIČ, Rok, KAPLANIS, Prodromos A., PATTICHIS, Constantinos S. and ZAZULA, Damjan, 2008, Analysis of neuromuscular disorders using statistical and entropy metrics on surface EMG. WSEAS transactions on signal processing [online]. 2008. [Accessed 9 April 2025]. Retrieved from: http://www.wseas.us/e-library/transactions/signal/2008/25-301.pdf
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Record is a part of a journal

Title:WSEAS transactions on signal processing
Shortened title:WSEAS trans. signal process.
Publisher:World Scientific and Engineering Academy and Society
ISSN:1790-5052
COBISS.SI-ID:2574443 New window

Secondary language

Language:English
Keywords:elektromiografija, nevrologija, medicina, diagnostika, obdelava signalov, obdelava slik, medicinske slike, valčna transformacija


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