title: Parametric time-varying spectrum and its application to SEMG signals.
abstract: Frequency spectrum of surface electromyographic signals (SEMGs) exhibits a non-stationary nature even in case of constant level isometric muscle contractions. This changes are related to muscle fatigue processes and can be evaluated by methods for estimation of time-varying (TV) spectrum. We describe a two estimation techniques: sliding window approach and decomposition of linear model coefficients trajectories. Drawback of the first is its large variance which causes unrealistic abrupt changes in the curve of overall dynamics, calculated either as the second derivative of the MF or as the ARMA distance between subsequent linear models forming the TV parametric spectrum. We demonstrate, that the second method is more appropriate for description of a slowly changing spectrum of surface EMG signals. Dynamics measures obtained from this estimation are proposed as an indication of the fatigue process character.
authors.affiliation: Faculty of Electrical Engineering and Computer Science, University of Maribor, Slovenia. dean.korosec@uni-mb.si
authors.forename: D
authors.initials: D
authors.lastname: Korosec
mesh_terms: D004576:Electromyography; D005583:Fourier Analysis; D006801:Humans; D007537:Isometric Contraction / Q000502:physiology; D016014:Linear Models; D018763:Muscle Fatigue / Q000502:physiology; D012016:Reference Values; D012815:Signal Processing, Computer-Assisted