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

doi:10.3390/s23136017

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

Sensors (Basel). 2023 Jun 29;23(13):6017. doi: 10.3390/s23136017.

Authors

Spyridon Kontaxis^{1

2}, Estela Laporta^{1

2}, Esther Garcia^{2

3}, Matteo Martinis⁴, Letizia Leocani⁴, Lucia Roselli⁴, Mathias Due Buron⁵, Ana Isabel Guerrero⁶, Ana Zabala⁶, Nicholas Cummins⁷, Srinivasan Vairavan⁸, Matthew Hotopf⁹, Richard J B Dobson^{7

10}, Vaibhav A Narayan¹¹, Maria Libera La Porta⁴, Gloria Dalla Costa⁴, Melinda Magyari⁵, Per Soelberg Sørensen⁵, Carlos Nos⁶, Raquel Bailon^{1

2}, Giancarlo Comi^{4

12}, On Behalf Of The Radar-Cns Consortium

Affiliations

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.

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: accelerometer sensor; disability level; fatigue severity; walk tests; wearable device.

MeSH terms

Fatigue
Humans
Multiple Sclerosis*
Walk Test
Walking

Grants and funding

The RADAR-CNS project received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 115902. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA (www.imi.europa.eu). This communication reflects the views of the RADAR-CNS consortium, and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein. This paper represents independent research partly funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London, Maudsley NHS Foundation Trust, and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. This work was also funded by TED2021-131106B-I00 (Ministerio de Ciencia e Innovación and European Social Fund), Spain, and by European Social Fund (EU) and Aragón Government, Spain through BSICoS group, Spain T39_23R.