Department of Joint Surgery, The Fourth People's Hospital of Jinan, Jinan 250031, Shandong, China.
J Healthc Eng. 2021 Feb 9;2021:6646977. doi: 10.1155/2021/6646977. eCollection 2021.
With the aggravation of the problem of aging population, all kinds of lower limb paralysis caused by various diseases occur frequently. People's demand for lower limb nursing and rehabilitation treatment is growing. In this paper, combined with intelligent medical technology and lower limb kinematics model, this paper proposes to build a lower limb joint nursing and rehabilitation system based on intelligent medical treatment. It is expected that, through the following limb joint rehabilitation robot as the main rehabilitation means, a smart nursing rehabilitation system which can quickly respond to users and realize remote rehabilitation nursing can be designed. First of all, it is clear that the main body of the lower limb joint rehabilitation system consists of the robot body and the state display system. Then, the sensor, amplifier, and data acquisition card are set in the data acquisition system, and the plantar balance force is detected using a FlexiForce film pressure sensor. The final control system mainly includes the main control module program and the lower limb action recognition program. The motor control software adopts PID regulation method, and the lower limb action recognition adopts SVM one-to-one classification method. After the construction of lower limb joint nursing and rehabilitation system, the accuracy rate of action recognition and classification was tested. In the third experiment, the accuracy of all the movements was 100%. Then, the joint displacement and angle changes of the experimenter assisted by the system were analyzed. The experimenter's knee joint and hip joint show a normal walking state, and the joint angle changes tend to be normal. Ten out of 55 rehabilitation system users were randomly selected for interview survey. The total scores of operation convenience, wearing comfort, intensity suitability, and movement science of the system were 90, 83, 84, and 91, respectively. This shows that the rehabilitation action designed by the system is scientific and easy to operate and can be put into use in rehabilitation training after improving the wearing comfort.
随着人口老龄化问题的加剧，各种疾病导致的各种下肢瘫痪频繁发生，人们对下肢护理和康复治疗的需求不断增长。本文结合智能医疗技术和下肢运动学模型，提出构建基于智能医疗的下肢关节护理和康复系统。预计通过以下肢关节康复机器人为主要康复手段，设计一种能够快速响应用户并实现远程康复护理的智能护理康复系统。首先，明确下肢关节康复系统的主体由机器人主体和状态显示系统组成。然后，在数据采集系统中设置传感器、放大器和数据采集卡，并使用 FlexiForce 薄膜压力传感器检测足底平衡力。最终控制系统主要包括主控模块程序和下肢动作识别程序。电机控制软件采用 PID 调节方法，下肢动作识别采用 SVM 一对一分类方法。构建下肢关节护理和康复系统后，对动作识别和分类的准确率进行测试。在第三个实验中，所有动作的准确率均为 100%。然后，分析了系统辅助实验者的关节位移和角度变化。实验者的膝关节和髋关节呈现正常行走状态，关节角度变化趋于正常。随机选择 55 名康复系统用户中的 10 人进行访谈调查。系统操作方便性、佩戴舒适性、强度适宜性和运动科学性的总评分为 90、83、84 和 91，这表明系统设计的康复动作科学合理，易于操作，并可在提高佩戴舒适性后投入康复训练使用。
