Movability assessment on physiotherapy for shoulder periarthritis via fine-grained 3D ResNet deep learning

We present a novel approach to movability assessment on physiotherapy for shoulder periarthritis via fine-grained 3D Residual Networks (R3D) deep learning. The unique deep neural networks is able to automatically extract the spatiotemporal features from the RGB-D videos. In our preliminary studies, we have a set of VR sports games customized for the immersive and interactive sports environment, to regulate the patient’s rehabilitation exercises. In this way, acquisition of RGB-D action videos can be more specific to the subject and defined movements; and fine-grained feature discrimination of the same subject can be better achieved from the longitudinal study, to increase the accuracy of therapeutic assessment.