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|Title:||Nonlinear analysis of EMG signals - A chaotic approach|
|Source:||Padmanabhan, P.,Puthusserypady, S. (2004). Nonlinear analysis of EMG signals - A chaotic approach. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings 26 I : 608-611. ScholarBank@NUS Repository.|
|Abstract:||This paper aims to present a systematic characterisation of the electromyogram (EMG) signal using a nonlinear chaotic approach. EMG signals from 10 muscles in the leg during walking and maximum voluntary contraction (MVC) were obtained and pre-processed using wavelet based denoising techniques. All signals were tested for non-linearity, stationarity and determinism. Chaotic characterization was done by calculating invariants such as correlation dimension (D 2), Lyapunov spectrum (λ i) and Kaplan-Yorke dimension (D KY). The EMG signals were non-linear and short-term stationary. Determinism and structure was found in the phase-space by studying the recurrence plots. Based on the values of the chaotic invariants, EMG signals were found to exhibit signs of chaotic behaviour with a dimension between 2 and 3 for walking and 3 and 4 for MVC data.|
|Source Title:||Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings|
|Appears in Collections:||Staff Publications|
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