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Aiming at the problems of single function of rehabilitation equipment for hand rehabilitation in medicine, repeated and boring movements during training, and slow recovery process, a gesture recognition rehabilitation system based on computer vision is proposed. First, it introduces the key technologies of computer vision such as image acquisition, segmentation, smoothing, classification, and recognition. Second, it focuses on the implementation details of the gesture rehabilitation system. Collect gesture sample data of people of different ages and genders through the camera, establish a rehabilitation gesture database, use computer vision, convolutional neural network, PyQt graphical interface and other technologies to build a rehabilitation system, and provide interesting, efficient and convenient rehabilitation training programs and treatments Methods to make up for the shortcomings of traditional rehabilitation therapy. The experimental results show that the system is reliable and get 96% accuracy, not only can increase the patient's interest and enthusiasm for rehabilitation training, but also the price is lower than other rehabilitation equipment, and the application prospect is broader.