Prediction of fall risk among community-dwelling older adults using a wearable system.

ABSTRACT: Falls are among the most common cause of decreased mobility and independence in older adults and rank as one of the most severe public health problems with frequent fatal consequences. In the present study, gait characteristics from 171 community-dwelling older adults were evaluated to determine their predictive ability for future falls using a wearable system. Participants wore a wearable sensor (inertial measurement unit, IMU) affixed to the sternum and performed a 10-m walking test. Measures of gait variability, complexity, and smoothness were extracted from each participant, and prospective fall incidence was evaluated over the following 6-months. Gait parameters were refined to better represent features for a random forest classifier for the fall-risk classification utilizing three ex

SUBMITTER: Lockhart TE 

PROVIDER: S-EPMC8545936 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature