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Quantifying longitudinal gait changes in ALS using wearable digital health technology metrics

Burke, K. M.; Calcagno, N.; Mandepudi, S.; Premasiri, A.; Hall, K. C.; Vieira, F. G.; Berry, J. D.; Straczkiewicz, M.

2026-05-28 neurology
10.64898/2026.05.27.26354200 medRxiv
Show abstract

Wearable digital health technologies may complement traditional gait assessments in amyotrophic lateral sclerosis (ALS) by sensitively capturing real-world mobility changes. In this study, we validated six digital gait metrics derived from ankle-worn sensors in a natural history cohort of 182 individuals with ALS. Investigated metrics correspond to various aspects of gait, including volume, speed, intensity, similarity, variability, and fragmentation. Longitudinal analyses showed significant declines in step count, peak cadence, stride intensity, and stride similarity, with increasing stride duration variability and walking fragmentation over 52 weeks. Many participants exhibited greater relative change in the gait metrics than the self-reported ALS Functional Rating Scale-Revised (ALSFRS-RSE). Stratified analyses revealed that digital metrics captured significant functional decline even in participants with stable walking scores on the ALSFRS-RSE. These findings support the potential utility of these metrics for disease monitoring in ALS clinical care and trials.

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