Haiyan Wang
Computer vision, robot collaboration, sports, rehabilitation training system
At present, the research on the sports rehabilitation training system of robot cooperation mechanism is faced with challenges such as the lack of system accuracy and adaptability, and poor user interaction experience. The existing methods face some key problems, such as tracking errors, lack of robot coordination and lack of personalised rehabilitation training programs. In view of this, this paper is based on computer vision technology and robot cooperation mechanism optimisation in order to overcome the limitations of existing methods. The system designed in this study uses computer vision technology to capture the patient’s body posture and movement trajectory in real time, achieve accurate identification and analysis, and achieve an error rate of less than 1%. On the other hand, highly customised rehabilitation robots, with their flexible joint structure and precise power control, can provide stable physical support, intelligently adjust the treatment intensity and mode according to the needs of different stages of rehabilitation, and achieve a personalised matching rate of up to 95%. To quantify the effectiveness of the system, this study conducted a series of controlled clinical trials and invited 50 volunteers with knee injuries to participate in a six-month rehabilitation program. Compared to traditional physical therapy, participants trained with the system showed faster recovery in muscle strength, joint flexibility and gait stability, with average improvements of 37%, 32% and 29%, respectively. In the prevention of secondary injury, due to the effective intervention of an intelligent early warning module, the re-injury rate of system users is only about half of that of the control group. This study not only provides a new technical means for sports rehabilitation training but also provides a new idea for the application of computer vision and robot technology in the field of medical rehabilitation. ∗ Beijing Institute of Technology, Zhuhai 519087, China; e-mail: [email protected] Corresponding author: Haiyan Wang Recommended by Jiankun Wang
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