A Stochastic Model of Human Gait Dynamics

By Y. Ashkenazy, Jeffrey M. Hausdorff, Plamen Ch. Ivanov, Ary L. Goldberger, H. Eugene Stanley. 2001

160 citations recorded by the source corpus.

We present a stochastic model of gait rhythm dynamics, based on transitions between different “neural centers”, that reproduces distinctive statistical properties of normal human walking. By tuning one model parameter, the transition (hopping) range, the model can describe alterations in gait dynamics from childhood to adulthood—including a decrease in the correlation and volatility exponents with maturation. The model also generates time series with multifractal spectra whose broadness depends only on this parameter. Moreover, we find that the volatility exponent increases monotonically as a function of the width of the multifractal spectrum, suggesting the possibility of a change in multifractality with maturation.

Subfields: Cognitive Neuroscience, Economics and Econometrics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/b51b1403ebadff402c2fffcf9b7e4dfdb9039a8a