Abstract

With the complex changes in social and demographic structure, the problem of aging is becoming increasingly serious, and the demand for equipment in the field of medical rehabilitation is also increasing. Given the above situation, various countries have proposed using rehabilitation robots to assist patients in treatment, and have achieved certain results. The rehabilitation robot helps the injured area gradually recover autonomous movement through repeated auxiliary actions, thereby achieving the goal of physical rehabilitation training. However, most robot configurations face insufficient energy and power, as well as bulky and inflexible equipment. Based on the above issues, this article adopts an improved fuzzy algorithm control strategy to optimize the energy storage device and applies the energy system to the wrist rehabilitation training robot device. Firstly, a fuzzy adaptive algorithm is added to the traditional energy controller to combine system control with operational status, achieving precise control and dynamic adjustment of energy allocation. The research has added filter optimization design, which improves the accuracy and effectiveness of fuzzy algorithms. Finally, this article establishes an upper limb motion model of the rehabilitation robot and configures relevant hardware systems. At the same time, this article also uses manufacturing materials that meet functional requirements to construct auxiliary equipment. The results indicate that the improved fuzzy algorithm can improve the auxiliary effect in energy control of wrist rehabilitation robots. It has obvious advantages in the process of wrist rehabilitation training.

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