Abstract
Gait rhythm of patients with Parkinson's disease (PD), Huntington's disease (HD) and amyotrophic lateral sclerosis (ALS) has been studied focusing on the fractal and correlation properties of stride time fluctuations. In this study, we investigated gait asymmetry in these diseases using the multi-resolution entropy analysis of stance time fluctuations. Since stance time is likely to exhibit fluctuations across multiple spatial and temporal scales, the data series were decomposed into appropriate levels by applying stationary wavelet transform. The similarity between two corresponding wavelet coefficient series in terms of their regularities at each level was quantified based on a modified sample entropy method and a weighted sum was then used as gait symmetry index. We found that gait symmetry in subjects with PD and HD, especially with ALS is significantly disturbed. This method may be useful in characterizing certain pathologies of motor control and, possibly, in monitoring disease progression and evaluating the effect of an individual treatment.
Published Version
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