Abstract
AbstractPhysical function decline due to aging or disease can be assessed with quantitative motion analysis, but this currently requires expensive laboratory equipment. We introduce a self-guided quantitative motion analysis of the widely used five-repetition sit-to-stand test using a smartphone. Across 35 US states, 405 participants recorded a video performing the test in their homes. We found that the quantitative movement parameters extracted from the smartphone videos were related to a diagnosis of osteoarthritis, physical and mental health, body mass index, age, and ethnicity and race. Our findings demonstrate that at-home movement analysis goes beyond established clinical metrics to provide objective and inexpensive digital outcome metrics for nationwide studies.
Funder
National Science Foundation
U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering
U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development
U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke
Stanford Catalyst for Collaborative Solutions; the Mobilize Center; the Center for Reliable Sensor Technology- Based Outcomes for Rehabilitation
Publisher
Springer Science and Business Media LLC
Subject
Health Information Management,Health Informatics,Computer Science Applications,Medicine (miscellaneous)
Cited by
14 articles.
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