Abstract
Analysis of Parkinson's disease (PD) patient's gait pattern from foots vertical ground reaction forces' (VGRF) is a thought-provoking research problem with substantial scientific applications. The purpose of the present work is to advance this approach further and investigate relationship of VGRF signals obtained from patients with PD foots as a function of time. Gait analysis based on instrumented technique has been extensively used in gait laboratories and there is a lack of understanding gait patterns in different phases of gait cycle. In this study, a modern signal processing method called wavelet-based semblance analysis is performed on time series signals obtained from VGRF sensors placed under the foots of PD patients. Semblance analysis between VGRF signals of PD patients in normal walking and dual tasking shows that it has high cross correlation (P SEM ) is always greater than 1 for control subjects and is ≤ 1 for subjects with PD. These findings pave way for measuring the degree of similarity and quantifying dual tasking gait dynamics of PD patients from a normal walking.
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