A Stochastic Model of Human Gait Dynamics

Abstract

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 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.