Emily Matijevich
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Wearable sensor algorithms powered by machine learning could be key to preventing runners’ injuries
A trans-institutional team of Vanderbilt engineering, data science and clinical researchers has developed a novel approach for monitoring bone stress in recreational and professional athletes, with the goal of anticipating and preventing injury. Using machine learning and biomechanical modeling techniques, the researchers built multisensory algorithms that combine data from lightweight, low-profile wearable sensors in shoes... Read MoreOct 28, 2020
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Vanderbilt trans-institutional team shows how next-gen wearable sensor algorithms powered by machine learning could be key to preventing injuries that sideline runners
An interdisciplinary team of researchers led by Karl Zelik explores how wearable sensor technology can monitor bone stress in runners, developing a new multi-sensor algorithm that could save runners from months of pain and recovery time. Read MoreOct 28, 2020