Gait Nonlinear Patterns Related to Parkinson's Disease and Age

Gait and posture are regular activities which are fully controlled by the sensorimotor cortex. In this paper, the complexity of fluctuations in human walking stride records is analyzed to assess gait in healthy young, healthy older adults, and patients affected with Parkinson's disease (PD). In this regard, a nonlinear analysis of gait reliability is performed by measuring long-range dependence, chaos, and information content in walking stride records. We seek to test if changes in these measures of gait nonlinear patterns occur with age and pathology. The inferential analyses were conducted by employing various statistical tests. The obtained results show a strong evidence of significant group differences in the measured gait nonlinear patterns. More importantly, values of all the three complexity measures increase with age and occurrence of pathology. In addition, age and PD significantly affect gait nonlinear dynamics. In particular, age shapes randomness, while PD alters regularity and stability. Complexity measures considered in this paper provide new insights to better understand the biomechanics of walk due to aging. In addition, they appear to be valuable tools that can highlight differences in gait nonlinear dynamics with respect to PD patients. In this regard, the measurement of gait nonlinear patterns may possibly afford pertinent clinical information on neuromotor conditions, characterization of some neurological disorders, and rehabilitation.