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      Detection of chaos in human fatigue mechanomyogarphy signals.

      Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

      Signal Processing, Computer-Assisted, Nonlinear Dynamics, methods, Myography, physiology, Muscle, Skeletal, Muscle Fatigue, Muscle Contraction, Humans, Biomechanical Phenomena, Algorithms

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          Abstract

          We undertake the study of the chaotic nature of mechanomygraphy (MMG) signal by recourse to the recent developments in the field of nonlinear dynamics. The MMG signals were measured from biceps brachii muscle of 5 subjects during fatigue of isometric contraction at 80% maximal voluntary contraction (MVC) level. Deterministic chaotic character was detected in all data by using the Volterra-Wiener-Korenberg model and noise titration approach. The noise limit (NL), which is a power indicator of chaos of fatigue MMG signals, is 22.2000 + or - 8.7293. Furthermore, we studied the nonlinear dynamic features of MMG signals by computing their correlation dimension D(2), which is 3.3524 + or - 0.3645 across all the subjects. These results indicate that MMG is a high-dimensional chaotic signal and support the use of the theory of nonlinear dynamics for the analysis and modeling the MMG signals.

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          Journal
          10.1109/IEMBS.2009.5333485
          19964108

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