Open-source dataset reveals relationship between walking bout duration and fall risk classification performance in persons with multiple sclerosis.

ABSTRACT: Falls are frequent and associated with morbidity in persons with multiple sclerosis (PwMS). Symptoms of MS fluctuate, and standard biannual clinical visits cannot capture these fluctuations. Remote monitoring techniques that leverage wearable sensors have recently emerged as an approach sensitive to disease variability. Previous research has shown that fall risk can be identified from walking data collected by wearable sensors in controlled laboratory conditions however this data may not be generalizable to variable home environments. To investigate fall risk and daily activity performance from remote data, we introduce a new open-source dataset featuring data collected from 38 PwMS, 21 of whom are identified as fallers and 17 as non-fallers based on their six-month fall history. This data

SUBMITTER: Meyer BM 

PROVIDER: S-EPMC9931255 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature