| 智能多姿态下肢康复训练设备控制系统研究 |
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| 引用本文： | 孟利国,喻洪流,孟巧玲,朱文杰. 智能多姿态下肢康复训练设备控制系统研究[J]. 教育技术导刊, 2021, 20(1): 142-147. DOI: 10.11907/rjdk.202489 |
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| 作者姓名： | 孟利国 喻洪流 孟巧玲 朱文杰 |
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| 作者单位： | 1.上海理工大学 康复工程与技术研究所；2.上海康复器械工程技术研究中心；3.民政部神经功能信息与康复工程重点实验室，上海200093 |
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| 基金项目： | 上海市“科技创新行动计划”产学研医合作领域项目（15D1941902） |
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| 摘 要： | 为了更好地帮助下肢功能障碍者进行居家下肢康复训练,重获行动能力,走向独立生活,设计一种基于轮椅的智能多姿态下肢康复训练设备控制系统.该系统选用STM32F103系列单片机作为主控芯片,采用模块化设计思想,对人机交互模块、运动控制模块、姿态变换与下肢康复训练模块的软硬件进行设计.实验结果表明,人机交互摇杆按键控制姿态变换...
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| 关 键 词： | 康复训练 人机交互 模块化 智能控制 语音控制 |
| 收稿时间： | 2020-11-28 |
Research on Control System of Intelligent Multi-gesture Lower Limb Rehabilitation Training Equipment |
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| MENG Li-guo,YU Hong-liu,MENG Qiao-ling,ZHU Wen-jie. Research on Control System of Intelligent Multi-gesture Lower Limb Rehabilitation Training Equipment[J]. Introduction of Educational Technology, 2021, 20(1): 142-147. DOI: 10.11907/rjdk.202489 |
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| Authors: | MENG Li-guo YU Hong-liu MENG Qiao-ling ZHU Wen-jie |
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| Affiliation: | 1. Institute of Rehabilitation Engineering and Technology， University of Shanghai for Science and Technology；2. Shanghai Engineering Research Center of Assistive Devices；3. Key Laboratory of Neural-functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs，Shanghai 200093，China |
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| Abstract: | In order to better help the patients with lower limb dysfunction to carry out lower limb rehabilitation training at home， regain mobility and move towards an independent life， an intelligent multi-gesture lower limb rehabilitation training equipment control system based on wheelchair is designed. This system uses STM32F103 series single chip microcomputer as the main control chip， and adopts modular design idea to design the software and hardware of man-machine interaction module， motion control module， attitude transformation and lower limb rehabilitation training module. The experimental results show that the success rate of human-computer interaction joystick control posture change can reach 97.5%， and the success rate of voice control as well as mobile phone and tablet APP can also reach 92.5% and 95.3%. The control system operates stably， which lays a foundation for further improving the intelligent multi-posture lower limb rehabilitation training equipment. |
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| Keywords: | rehabilitation training human-computer interaction modularization intelligent control voice conctrol |
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