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Article

Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis

by
Spyridon Kontaxis
1,2,*,
Estela Laporta
1,2,
Esther Garcia
2,3,
Matteo Martinis
4,
Letizia Leocani
4,
Lucia Roselli
4,
Mathias Due Buron
5,
Ana Isabel Guerrero
6,
Ana Zabala
6,
Nicholas Cummins
7,
Srinivasan Vairavan
8,
Matthew Hotopf
9,
Richard J. B. Dobson
7,10,
Vaibhav A. Narayan
11,
Maria Libera La Porta
4,
Gloria Dalla Costa
4,
Melinda Magyari
5,
Per Soelberg Sørensen
5,
Carlos Nos
6,
Raquel Bailon
1,2,
Giancarlo Comi
4,12 and
on behalf of the RADAR-CNS Consortium
†add Show full author list remove Hide full author list
1
Laboratory of Biomedical Signal Interpretation and Computational Simulation (BSICoS), University of Zaragoza, 50018 Zaragoza, Spain
2
Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28006 Barcelona, Spain
3
Department of Microelectronics and Electronic Systems, Autonomous University of Barcelona, 08193 Bellaterra, Spain
4
Department of Medicine and Surgery, University Vita-Salute and Hospital San Raffaele, 20132 Milan, Italy
5
Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital Rigshospitalet, 2100 Copenhagen, Denmark
6
Multiple Sclerosis Center of Catalonia (CEMCAT), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d’Hebron, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain
7
Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
8
Janssen Research and Development, LLC, Titusville, NJ 08560, USA
9
Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
10
Institute of Health Informatics, University College London, London NW1 2DA, UK
11
Davos Alzheimer’s Collaborative, Wayne, PA 19087, USA
12
Casa di Cura del Policlinico, 20144 Milan, Italy
 
add Show full affiliation list
 
remove Hide full affiliation list
*
Author to whom correspondence should be addressed.
†
Available online: www.radar-cns.org, accessed on 1 April 2023.
Sensors 2023, 23(13), 6017; https://doi.org/10.3390/s23136017
Submission received: 1 May 2023 / Revised: 29 May 2023 / Accepted: 10 June 2023 / Published: 29 June 2023
(This article belongs to the Special Issue ECG Signal Processing Techniques and Applications)
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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.
Keywords: wearable device; accelerometer sensor; walk tests; disability level; fatigue severity wearable device; accelerometer sensor; walk tests; disability level; fatigue severity

Share and Cite

MDPI and ACS Style

Kontaxis, S.; Laporta, E.; Garcia, E.; Martinis, M.; Leocani, L.; Roselli, L.; Buron, M.D.; Guerrero, A.I.; Zabala, A.; Cummins, N.; et al. Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis. Sensors 2023, 23, 6017. https://doi.org/10.3390/s23136017

AMA Style

Kontaxis S, Laporta E, Garcia E, Martinis M, Leocani L, Roselli L, Buron MD, Guerrero AI, Zabala A, Cummins N, et al. Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis. Sensors. 2023; 23(13):6017. https://doi.org/10.3390/s23136017

Chicago/Turabian Style

Kontaxis, Spyridon, Estela Laporta, Esther Garcia, Matteo Martinis, Letizia Leocani, Lucia Roselli, Mathias Due Buron, Ana Isabel Guerrero, Ana Zabala, Nicholas Cummins, and et al. 2023. "Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis" Sensors 23, no. 13: 6017. https://doi.org/10.3390/s23136017

APA Style

Kontaxis, S., Laporta, E., Garcia, E., Martinis, M., Leocani, L., Roselli, L., Buron, M. D., Guerrero, A. I., Zabala, A., Cummins, N., Vairavan, S., Hotopf, M., Dobson, R. J. B., Narayan, V. A., La Porta, M. L., Costa, G. D., Magyari, M., Sørensen, P. S., Nos, C., ... on behalf of the RADAR-CNS Consortium. (2023). Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis. Sensors, 23(13), 6017. https://doi.org/10.3390/s23136017

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