Rehabilitation Exercise

Rehabilitation exercise research focuses on developing automated systems for assessing and guiding patient performance, aiming to improve the effectiveness and accessibility of physical therapy. Current research employs various machine learning approaches, including graph convolutional networks (GCNs), transformers, and Gaussian Mixture Models (GMMs), often leveraging data from depth cameras or smartphone video to analyze body movements and provide real-time feedback. These advancements hold significant promise for enhancing the accuracy and efficiency of rehabilitation, potentially addressing therapist shortages and improving patient adherence to home-based programs.