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Upper and Lower Limb Training Evaluation System Based on Virtual Reality Technology

Overview
Journal Sensors (Basel)
Publisher MDPI
Specialty Biotechnology
Date 2024 Nov 9
PMID 39517807
Authors
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Abstract

Upper and lower limb rehabilitation training is essential for restoring patients' physical movement ability and enhancing muscle strength and coordination. However, traditional rehabilitation training methods have limitations, such as high costs, low patient participation, and lack of real-time feedback. The purpose of this study is to design and implement a rehabilitation training evaluation system based on virtual reality to improve the quality of patients' rehabilitation training. This paper proposes an upper and lower limb rehabilitation training evaluation system based on virtual reality technology, aiming to solve the problems existing in traditional rehabilitation training. The system provides patients with an immersive and interactive rehabilitation training environment through virtual reality technology, aiming to improve patients' participation and rehabilitation effects. This study used Kinect 2.0 and Leap Motion sensors to capture patients' motion data and transmit them to virtual training scenes. The system designed multiple virtual scenes specifically for different upper and lower limbs, with a focus on hand function training. Through these scenes, patients can perform various movement training, and the system will provide real-time feedback based on the accuracy of the patient's movements. The experimental results show that patients using the system show higher participation and better rehabilitation training effects. Compared with patients receiving traditional rehabilitation training, patients using the virtual reality system have significantly improved movement accuracy and training participation. The virtual reality rehabilitation training evaluation system developed in this study improves the quality of patients' rehabilitation and provides personalized treatment information to medical personnel through data collection and analysis, promoting the systematization and personalization of rehabilitation training. This system is innovative and has broad application potential in the field of rehabilitation medicine.

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