Kontaxis, Spyridon;
Laporta, Estela;
Garcia, Esther;
Martinis, Matteo;
Leocani, Letizia;
Roselli, Lucia;
Buron, Mathias Due;
... RADAR, CNS Consortium; + view all
(2023)
Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis.
Sensors
, 23
(13)
, Article 6017. 10.3390/s23136017.
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Abstract
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.
| Type: | Article |
|---|---|
| Title: | Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis |
| Location: | Switzerland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3390/s23136017 |
| Publisher version: | https://doi.org/10.3390/s23136017 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Science & Technology, Physical Sciences, Technology, Chemistry, Analytical, Engineering, Electrical & Electronic, Instruments & Instrumentation, Chemistry, Engineering, wearable device, accelerometer sensor, walk tests, disability level, fatigue severity, DISABILITY STATUS SCALE, ABILITY |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10175868 |
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