Complexity analysis of the gait time series using fine-grained permutation entropy

In this paper we analyze the complexity of human gait time series from healthy subjects and Parkinson sufferers using the recently developed fine-grained permutation entropy (FGPE). It is found that FGPE is more sensitive for distinguishing the complexity of three groups of peoples. According to FGPE, the complexity of gaits is the largest for healthy young adults, next larger for the healthy old adults, and the smallest for Parkinson sufferers. The findings have implications for characterizing pathologic states of motor control and for evaluating the effect of treatment.