DocumentCode
2821438
Title
Kurtosis and negentropy investigation of myo electric signals during different MVCs
Author
Naik, Ganesh R. ; Kumar, Dinesh K. ; Arjunan, Sridhar P.
Author_Institution
Sch. of Electr. & Comput. Eng., RMIT Univ., Melbourne, VIC, Australia
fYear
2011
fDate
6-8 Jan. 2011
Firstpage
1
Lastpage
4
Abstract
This research deals with computing the non-Gaussianity in Surface Electromyogram signal (sEMG) using Negative entropy and Kurtosis values. The signal was acquired from three different finger and wrist actions at four different levels of Maximum Voluntary Contractions (MVCs). Our experimental analysis shows that at constant force and for non-fatiguing contractions, probability density function (pdf) of sEMG signals were non-Gaussian. For lesser MVCs (below 30% of MVC) pdf measures tends to be Gaussian process. The above measures were verified by computing the kurtosis values for different MVCs.
Keywords
electromyography; entropy; medical signal processing; Maximum Voluntary Contraction; kurtosis; negative entropy; negentropy; nonGaussianity; probability density function; surface electromyogram signal; Electromyography; Fingers; Force; Force measurement; Force sensors; Independent component analysis; Muscles;
fLanguage
English
Publisher
ieee
Conference_Titel
Biosignals and Biorobotics Conference (BRC), 2011 ISSNIP
Conference_Location
Vitoria
Print_ISBN
978-1-4244-8212-2
Type
conf
DOI
10.1109/BRC.2011.5740669
Filename
5740669
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