2026-04-13T18:32:43Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/4714942025-02-03T22:58:32Zcom_2072_98col_2072_378192

00925njm 22002777a 4500 dc Kontaxis, Spyridon author Laporta, Estela author Garcia, Esther author Martinis, Matteo author Leocani, Letizia author Roselli, Lucia author Buron, Mathias Due author Guerrero, Ana Isabel author Zabalza, Ana author Cummins, Nicholas author Vairavan, Srinivasan author Hotopf, Matthew author Dobson, Richard James Butler author Narayan, Vaibhav A. author La Porta, Maria Libera author Costa, Gloria Dalla author Magyari, Melinda author Sørensen, Per S author Nos, Carlos author Bailón, Raquel author Comi, Giancarlo author 2023 The aim of this study was to investigate the feasibility of automatically assessing the 2-Minute Walk Distance (2MWD) for monitoring people with multiple sclerosis (pwMS). For 154 pwMS, MS-related clinical outcomes as well as the 2MWDs as evaluated by clinicians and derived from accelerometer data were collected from a total of 323 periodic clinical visits. Accelerometer data from a wearable device during 100 home-based 2MWD assessments were also acquired. The error in estimating the 2MWD was validated for walk tests performed at hospital, and then the correlation (r) between clinical outcomes and home-based 2MWD assessments was evaluated. Robust performance in estimating the 2MWD from the wearable device was obtained, yielding an error of less than 10% in about two-thirds of clinical visits. Correlation analysis showed that there is a strong association between the actual and the estimated 2MWD obtained either at hospital (r = 0.71) or at home (r = 0.58). Furthermore, the estimated 2MWD exhibits moderate-to-strong correlation with various MS-related clinical outcomes, including disability and fatigue severity scores. Automatic assessment of the 2MWD in pwMS is feasible with the usage of a consumer-friendly wearable device in clinical and non-clinical settings. Wearable devices can also enhance the assessment of MS-related clinical outcomes. Accelerometer sensor Disability level Fatigue severity Walk tests Wearable device Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis