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
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;
Conference_Titel :
Biosignals and Biorobotics Conference (BRC), 2011 ISSNIP
Conference_Location :
Vitoria
Print_ISBN :
978-1-4244-8212-2
DOI :
10.1109/BRC.2011.5740669