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Multidimensional ground reaction forces and moments from wearable sensor accelerations via deep learning
Competing convolutional neural network (CNN) deep learning models were trained using laboratory-derived stance phase GRF/M data and simulated sensor accelerations for running and sidestepping maneuvers derived from nearly half a million legacy motion trials.
On-field player workload exposure and knee injury risk monitoring via deep learning
In sports analytics, an understanding of accurate on-field 3D knee joint moments (KJM) could provide an early warning system for athlete workload exposure and knee injury risk.
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