Automatic assessment of the 2-minute walk distance for remote monitoring of people with multiple sclerosis

Kontaxis, Spyridon (Universidad de Zaragoza) ; Laporta, Estela ; Garcia, Esther ; Martinis, Matteo ; Leocani, Letizia ; Roselli, Lucia ; Buron, Mathias Due ; Guerrero, Ana Isabel ; Zabala, Ana ; Cummins, Nicholas ; Vairavan, Srinivasan ; Hotopf, Matthew ; Dobson, Richard J. B. ; Narayan, Vaibhav A. ; La Porta, Maria Libera ; Costa, Gloria Dalla ; Magyari, Melinda ; Sørensen, Per Soelberg ; Nos, Carlos ; Bailon, Raquel (Universidad de Zaragoza) ; Comi, Giancarlo

Resumen: 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.

Idioma: Inglés

DOI: 10.3390/s23136017

Año: 2023

Publicado en: Sensors 23, 13 (2023), 6017 [11 pp.]
ISSN: 1424-8220

Financiación: info:eu-repo/grantAgreement/ES/DGA/T39-23R
Financiación: info:eu-repo/grantAgreement/EC/H2020/115902/EU/Remote Assessment of Disease and Relapse in Central Nervous System Disorders/RADAR-CNS
Financiación: info:eu-repo/grantAgreement/EUR/MICINN/TED2021-131106B-I00

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)