Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis
Spyridon Kontaxis,
Estela Laporta,
Esther Garcia,
Matteo Martinis,
Letizia Leocani,
Lucia Roselli,
Mathias Due Buron,
Ana Isabel Guerrero,
Ana Zabala,
Nicholas Cummins,
Srinivasan Vairavan,
Matthew Hotopf,
Richard J. B. Dobson,
Vaibhav A. Narayan,
Maria Libera La Porta,
Gloria Dalla Costa,
Melinda Magyari,
Per Soelberg Sørensen,
Carlos Nos,
Raquel Bailon,
Giancarlo Comi,
on behalf of the RADAR-CNS Consortium
Affiliations
Spyridon Kontaxis
Laboratory of Biomedical Signal Interpretation and Computational Simulation (BSICoS), University of Zaragoza, 50018 Zaragoza, Spain
Estela Laporta
Laboratory of Biomedical Signal Interpretation and Computational Simulation (BSICoS), University of Zaragoza, 50018 Zaragoza, Spain
Esther Garcia
Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28006 Barcelona, Spain
Matteo Martinis
Department of Medicine and Surgery, University Vita-Salute and Hospital San Raffaele, 20132 Milan, Italy
Letizia Leocani
Department of Medicine and Surgery, University Vita-Salute and Hospital San Raffaele, 20132 Milan, Italy
Lucia Roselli
Department of Medicine and Surgery, University Vita-Salute and Hospital San Raffaele, 20132 Milan, Italy
Mathias Due Buron
Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital Rigshospitalet, 2100 Copenhagen, Denmark
Ana Isabel Guerrero
Multiple Sclerosis Center of Catalonia (CEMCAT), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d’Hebron, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain
Ana Zabala
Multiple Sclerosis Center of Catalonia (CEMCAT), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d’Hebron, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain
Nicholas Cummins
Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
Srinivasan Vairavan
Janssen Research and Development, LLC, Titusville, NJ 08560, USA
Matthew Hotopf
Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
Richard J. B. Dobson
Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
Vaibhav A. Narayan
Davos Alzheimer’s Collaborative, Wayne, PA 19087, USA
Maria Libera La Porta
Department of Medicine and Surgery, University Vita-Salute and Hospital San Raffaele, 20132 Milan, Italy
Gloria Dalla Costa
Department of Medicine and Surgery, University Vita-Salute and Hospital San Raffaele, 20132 Milan, Italy
Melinda Magyari
Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital Rigshospitalet, 2100 Copenhagen, Denmark
Per Soelberg Sørensen
Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital Rigshospitalet, 2100 Copenhagen, Denmark
Carlos Nos
Multiple Sclerosis Center of Catalonia (CEMCAT), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d’Hebron, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain
Raquel Bailon
Laboratory of Biomedical Signal Interpretation and Computational Simulation (BSICoS), University of Zaragoza, 50018 Zaragoza, Spain
Giancarlo Comi
Department of Medicine and Surgery, University Vita-Salute and Hospital San Raffaele, 20132 Milan, Italy
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.
