Abstract
This study aimed to develop a convolutional neural network (CNN) model to predict shoulder joint reaction forces from 3D body kinematics. Results showed a good convergence between CNN model prediction and musculoskeletal model estimation for six novel tasks. Therefore, a CNN-based deep learning model can be used as a simple and relatively less time- and labor-intensive method to identify unsafe shoulder exertions in order to prevent the incidence of shoulder injuries or pathologies in occupational settings.
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