Quantitative mobility metrics from a wearable sensor predict incident parkinsonism in older adults.

ABSTRACT:

Introduction

Mobility metrics derived from wearable sensor recordings are associated with parkinsonism in older adults. We examined if these metrics predict incident parkinsonism.

Methods

Parkinsonism was assessed annually in 683 ambulatory, community-dwelling older adults without parkinsonism at baseline. Four parkinsonian signs were derived from a modified Unified Parkinson's Disease Rating Scale (UPDRS). Parkinsonism was based on the presence of 2 or more signs. Participants wore a sensor on their back while performing a 32 foot walk, standing posture, and Timed Up and Go (TUG) tasks. 12 mobility scores were extracted. Cox proportional hazards models with backward elimination were used to identify combinations of mobility scores independently associated with incident park

SUBMITTER: von Coelln R 

PROVIDER: S-EPMC6774889 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature