Design of a virtual reality rehabilitation system for upper limbs that inhibits compensatory movement

Stroke is currently the main cause of death and disability among the elderly in our country. According to medical research, a considerable number of patients with physical disabilities can be recovered through rehabilitation training. However, traditional motor rehabilitation is a continuous, repeated and slow process, and patients tend to feel bored and lose motivation for training. In this paper, we developed a virtual reality rehabilitation system based on Kinect, which is a vision capture sensor, for patients with movement disorders who are at or above Brunnstrom Stage III and have certain motor ability. Through the management platform of the system, physician can obtain the patient's personal information, formulate and adjust the training plan. Patients can control the role in the virtual scene through Kinect sensor, and complete the training action according to the guidance. The system collects the user's motion data in real time and detect the compensation. The system will adaptively evolve to guide the patient to self-correct the compensatory patterns. After the training, the system will evaluate the patients based on the their training performance. Two experiments are also carried out to verify the accuracy of the range of motion and the effectiveness of virtual guidance. It is proved that the virtual reality upper limb rehabilitation training system studied in this paper is reliable, stable, and can guide users to complete the training action and improve the rehabilitation effect.