Complexity Analysis of Gait Time Series under the Different Physiological States

The underlying correlation between gait time series and the different physiological states is investigated by means of complexity measure in this paper. The definition and algorithm of Lem-Ziv complexity are introduced first, and then the gait data analysis was implemented by using this method. The results show that a strong relation between the age and the gait complexity was found, such as the older the subject is, the larger the complexity of gait becomes. In the end of this paper the mere fringes of the finite length effect was discussed as well. This research suggests that the method may be a new way to understand human gait. Nonetheless, because of the relatively short length of the sequences and the relatively small number of subjects in our each group, it is possible that we failed to detect more subtle distinctions among the groups, especially in subgroup analysis. Future study of a larger group of subjects is required to confirm our conclusions.