Invariant density analysis: modeling and analysis of the postural control system using Markov chains.

Abstract

In this paper, a novel analysis technique, invariant density analysis (IDA), is introduced. IDA quantifies steady-state behavior of the postural control system using center of pressure (COP) data collected during quiet standing. IDA relies on the analysis of a reduced-order finite Markov model to characterize stochastic behavior observed during postural sway. Five IDA parameters characterize the model and offer physiological insight into the long-term dynamical behavior of the postural control system. Two studies were performed to demonstrate the efficacy of IDA. Study 1 showed that multiple short trials can be concatenated to create a dataset suitable for IDA. Study 2 demonstrated that IDA was effective at distinguishing age-related differences in postural control behavior between young, middle-aged, and older adults. These results suggest that the postural control system of young adults converges more quickly to their steady-state behavior while maintaining COP nearer an overall centroid than either the middle-aged or older adults. Additionally, larger entropy values for older adults indicate that their COP follows a more stochastic path, while smaller entropy values for young adults indicate a more deterministic path. These results illustrate the potential of IDA as a quantitative tool for the assessment of the quiet-standing postural control system.