Fluctuations in stride interval series show complex dynamical behavior in healthy young adults. Hypothesizing that these stride interval complexity changes would be altered by changes in neurological function associated with aging and certain disease states, we aimed to develop a tool to facilitate clinical judgments to assess the complex dynamical behavior in the stride series in discerning young, elderly, and Parkinson’s disease (PD) classes. This novel approach, which employs a new variant of coarse-graining in conjunction with Lempel–Ziv complexity measure, yields useful, reliable, and predictive results. We also show the presence of nonlinear deterministic structures in the stride time series and appropriateness of the application of our nonlinear approach through surrogate data analysis. The findings show that the fluctuations are more complex/random in elderly and PD classes than those in young class. These findings may add to the growing body of literature supporting the clinical utility of this new approach to stride time series.
|Publication status||Published - 01-01-2016|
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Chemical Engineering(all)