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Signals obtained from biological systems exhibit pronounced complexity. The patterns of change contain valuable information about the dynamics of underlying control mechanism of the complex biological systems. Human gait is a complex process with multiple inputs and numerous outputs.Various complexity analysis tools have been proposed to extract information from human gait time series. In this study, we used recently developed threshold based symbolic entropy to compare the spontaneous output of the human locomotors system during constrained and metronomically paced walking protocols. The…mehr

Produktbeschreibung
Signals obtained from biological systems exhibit pronounced complexity. The patterns of change contain valuable information about the dynamics of underlying control mechanism of the complex biological systems. Human gait is a complex process with multiple inputs and numerous outputs.Various complexity analysis tools have been proposed to extract information from human gait time series. In this study, we used recently developed threshold based symbolic entropy to compare the spontaneous output of the human locomotors system during constrained and metronomically paced walking protocols. The findings indicated that the unprompted output of human locomotors system is more complex during unconstrained normal walking as compared with slow, fast or metronomically paced walking. The results was compared with the Multiscale Entropy (MSE) Analysis proposed and we concluded that the Symbolic Analysis is more robust than multiscale entropy method as well as our method is also useful for smaller time series whereas MSE is not suitable for shorter time series.
Autorenporträt
Anees Qumar Abbasi has obtained his Master of Philosophy (M.Phil.) in Computer Sciences from University of Azad Jammu and Kashmir Muzaffarabad in 2013.During his studies he was involved in investigating the biological signals using different signal processing techniques.Currently he is research scholar at Dept. of CS&IT AJK University Muzaffarabad.