Literature DB >> 6186466

Automatic classification of electromyographic signals.

J L Coatrieux, P Toulouse, B Rouvrais, R Le Bars.   

Abstract

The results of the application of classification methods to electromyograph signals of weak contractions in normal and myopathic subjects are described. Methods of pattern recognition, previously presented, allow the selection of representative motor unit action potentials. The analysis is done with ordinal qualitative variables obtained by identification of shape descriptive parameters (amplitude, duration, number of phases, number of extrema). From this analysis, characteristic classes for normality and myopathy appear, from which a diagnostic aid by assignment can be made.

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Year:  1983        PMID: 6186466     DOI: 10.1016/0013-4694(83)90212-2

Source DB:  PubMed          Journal:  Electroencephalogr Clin Neurophysiol        ISSN: 0013-4694


  1 in total

1.  Decoding subtle forearm flexions using fractal features of surface electromyogram from single and multiple sensors.

Authors:  Sridhar Poosapadi Arjunan; Dinesh Kant Kumar
Journal:  J Neuroeng Rehabil       Date:  2010-10-21       Impact factor: 4.262

  1 in total

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