Physiological systems serve as a fascinating playground for the
analysis techniques, which stem from the discipline of nonlinear
dynamics. The essential non-linearities and the complexity of
physiological interactions limit to the ability of linear analysis
to provide full description of the underlying dynamics. This makes
nonlinear analysis an invaluable tool for the analysis of
physiological signals. Robust time series analysis measures are
needed to quantify the dynamics of physiological signals.Despite of
the fundamental difference in their regulation, the research in
heart rate variability analysis has spurred the similar
investigations in gait variability analysis.This study is
methodological approach for quantifying the dynamics of heart rate
and stride interval signals in health and disease. Two nonlinear
measures: Threshold based acceleration change index (TACI) and
normalized corrected Shannon entropy (NCSE) at different threshold
values have been used to quantify the dynamics of heart and stride
interval time series of healthy and diseased subjects.
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