Title :
Adaptive estimation of spectral parameters for myoelectric signals by means of AR modelling
Author :
Biagini, M. ; D´Alessio, T. ; Paggi, S.
Author_Institution :
Dept. Infocom, Roma Univ., Italy
Abstract :
The authors report the results obtained using an autoregressive (AR) method in the study of myoelectric signals during sustained contractions, when fatigue is supposed to occur. The differences between this sequential method and a batch Burg method are reported. Good results were obtained when the method was applied to experimentally recorded signals, and the computational burden was acceptable. The adaptive algorithm used makes it possible to estimate spectral parameters almost continuously and to control the variance of the estimates
Keywords :
bioelectric potentials; muscle; parameter estimation; physiological models; adaptive algorithm; adaptive estimation; autoregressive modelling; batch Burg method; computational burden; estimates variance; experimentally recorded signals; muscular fatigue; myoelectric signals; sequential method; spectral parameters; sustained contractions; Adaptive estimation; Estimation error; Fatigue; Filters; Frequency; Iterative algorithms; Parameter estimation; Parametric statistics; Reflection; White noise;
Conference_Titel :
Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in
Conference_Location :
Seattle, WA
DOI :
10.1109/IEMBS.1989.95934
