Authors: Tim Woelfle*, Lucie Bourguignon*, Johannes Lorscheider, Ludwig Kappos, Yvonne Naegelin†, Catherine R. Jutzeler†
Short summary: Limitations of physical activity and functional performance are considered a core problem in people with multiple sclerosis (PwMS). To optimally adopt interventional strategies, continuous monitoring of the functional performance (e.g., the ability to walk, to conduct daily activities) is warranted. Continuous disease monitoring by means of sensor technologies holds the promise to capture subtle changes that might be indicative of disease progression in PwMS. The aim of our review was to generate a comprehensive overview of wearable sensor technologies used in the field of MS and to provide recommendations for harmonizing efforts to ensure reproducibility of results and meaningful comparability of different sensor technologies. Using PubMed/Medline, Scopus, Embase, and Web of Science, we systematically searched the existing literature for studies employing wearable technologies to determine the physical activity and other motor outcomes in PwMS. We included peer-reviewed publications that utilize wearable sensor technology or applications to track and monitor the disease progression (motor function), refine disease diagnostic, or make predictions about the disease trajectories in PwMS. Cross-sectional and longitudinal studies, as well as pediatric and adult populations with MS, were equally considered. The systematic review was performed according to the PRISMA guidelines and registered with PROSPERO (CRD42021243249). Moreover, a quality assessment of all eligible studies was performed. Of 2’088 records identified, 223 articles evaluating different wearable sensor technologies (e.g., actigraphy, smartwatch, smartphone-based) comprising 20’573 PwMS and 3’247 controls (e.g., healthy controls, PwMS, mixed populations) were included in this systematic review. The majority of the studies assessed the physical activity in PwMS in a real-world setting (n = 133, 59.6%). Triaxial accelerometers were the most commonly used sensors to assess motor outcomes in PwMS. Along with technological progress, a surge in sensors embedded in smartphones and smartwatches has been observed. Lastly, the quality of eligible studies ranged from poor (satisfying ≤ 50% of the quality criteria) to very good (satisfying ≥ 90% of the quality criteria). The results of this review can be interactively exploited on our interactive web platform (https://lbourguignon.shinyapps.io/MS-Review/). An ever-growing number of studies is implementing sensor technologies to optimize the quantification of functional performance in PwMS. Our review provides an unprecedented overview of the current literature and highlights shortcomings that have to be addressed to make these technologies widely available and incorporate them in the clinical routine and clinical trials.
Link to web application: Shiny App
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This study was funded by the Swiss National Science Foundation (Ambizione Grant #PZ00P3_186101, Jutzeler).