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Updated: Apr 9, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
Association of wearable sensor-based gait analysis with phenoconversion trajectories in idiopathic REM sleep behavior
Shanshan Cen1,2, Hui Zhang1,2, Yuan Li1,2
1Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.
Abstract:
Idiopathic rapid eye movement sleep behavior disorder (iRBD) is a well-established prodromal manifestation of α-synucleinopathies, with two principal phenoconversion trajectories: parkinsonism-first and dementia-first. Although subtle gait abnormalities have been observed prior to phenoconversion, their predictive value remains unclear. We investigated whether wearable sensor-based gait parameters are associated with phenoconversion and its clinical trajectories in iRBD. Sixty-eight polysomnography-confirmed iRBD patients and 61 healthy controls were enrolled at baseline. The iRBD cohort was followed for a mean of 3.68 years, with 21 patients converting to neurodegenerative diseases; 38 patients completed follow-up gait assessment. Participants performed one-minute walking trials under normal, fast, and dual-task conditions while wearing six inertial sensors. At baseline, iRBD patients exhibited significant gait abnormalities compared with controls. Several gait parameters were more strongly associated with subsequent conversion to Parkinson's disease (PD) than to dementia with Lewy bodies (DLB), including shorter stride length, greater swing time variability, reduced arm swing range, increased arm swing variability, and lower peak arm swing velocity. Longitudinally, converters showed a steeper decline in stride length and greater increases in dual-task cost. Wearable sensor-based gait assessment may serve as a digital biomarker for predicting phenoconversion in iRBD, particularly along the parkinsonism-first trajectory.
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