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Quantifying Gait Velocity with the ActiMyo Wearable Devices in ALS
ALS trials depend on quantifiable measures of function to detect if an experimental therapy is working. Current ALS outcomes, like the ALS Functional Rating Scale – Revised (ALSFRS-R) and vital capacity, are collected in clinic and thus are recorded infrequently and yield small trial datasets. Advances in machine learning and artificial intelligence are revolutionizing medicine but require large datasets. Mobile apps and wearable sensors can collect large datasets about daily function while participants do very little except wear a device or answer questions on a mobile app. The ActiMyo device is a wearable sensor for the ankle and wrist that collects information regarding movement of the limbs. Algorithms calculate activity and walking metrics – specifically the 95th percentile stride velocity (SV95C), which regulators have accepted as a trial endpoint in muscular dystrophy. The Beiwe smartphone app obtains activity data and delivers questionnaires to evaluate the effect of ALS on people’s daily life. We will conduct a 12-month study of 30 participants with ALS wearing the ActiMyo device and using the Beiwe smartphone app to compare the SV95C and other digital outcome measures to traditional in-clinic ALS trial outcome measures, including the ALSFRS-R. Our goal is to collect more data, more rapidly and more easily to hasten ALS drug development. Specifically, we will confirm the utility of the SV95C and other digital features of movement as trial endpoints in ALS.
Digital Object Identifier (DOI)
Grantee: James Berry, M.D.
Grant type: Research Grant
Award total: $200,000.00
Institution: Massachusetts General Hospital (Mass General)
Country: United States