6533b7dafe1ef96bd126f6fc
RESEARCH PRODUCT
Multi axis representation and Euclidean distance of muscle fatigue indexes during evoked contractions
Maxime YochumToufik BakirStéphane BinczakRomuald Leperssubject
medicine.diagnostic_testMuscle fatigueSpeech recognitionMulti axis0206 medical engineeringMathematical analysis02 engineering and technologyElectromyography[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing020601 biomedical engineering[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsEuclidean distance03 medical and health sciences0302 clinical medicineAmplitudeMuscular fatiguemedicineRepresentation (mathematics)[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing030217 neurology & neurosurgeryContinuous wavelet transform[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMathematicsdescription
International audience; In this article, we proposed a new representation of muscular fatigue during evoked muscle contractions based on fatigue indexes such as peak to peak amplitude, RMS of the M wave, mean and median frequency and fatigue index calculated from continuous wavelet transform (I CWT). These new representations of muscle fatigue using multi axis represented and Euclidean distance give better insights on changes in physiological characteristics during muscle fatigue. This technique provides a fatigue index using several muscle characteristics. The use of other kinds of fatigue characteristics as force could also be possible.
year | journal | country | edition | language |
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2014-04-14 |