基于Arduino和STM32的主动式手部训练系统
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1.南京信息工程大学电子与信息工程学院 南京 210044; 2 南京信息工程大学江苏省大气环境与 装备技术协同创新中心 南京 210044

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TP242

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国家自然科学基金青年基金(11504176, 61601230)、江苏省自然科学基金青年基金(BK20141004)项目资助


Active hand training system based on Arduino and STM32
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1.School of Electronics and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China; 2.Jiangsu Province Atmospheric Environment and Equipment Technology Collaborative Innovation Center, Nanjing University of Information Science & Technology, Nanjing 210044, China

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    摘要:

    手部功能障碍患者在家自行练习康复动作时,由于缺乏科学的指导,训练步骤混乱,动作的精度与强度难以得到保证,从而影响了康复效果。本文设计了一套基于Arduino和STM32的主动式手部训练系统,系统分为数据手套、动作指导手掌和上位机三大部分,数据手套通过传感器获取手指和手腕的转动角数据并进行处理,然后将数据无线传输给动作指导手掌,动作指导手掌中的控制器STM32将接收数据与标准动作数据库进行比对,分析动作标准度,然后通过语音指导患者做出调整。STM32根据运动数据驱动六个数字舵机带动仿生手掌运动,从而模仿人手动作,系统使用LD3320识别患者命令,进行人机交互。系统通过上位机将标准动作数据库下载至STM32外扩闪存中,用于患者手部动作数据比对。实验结果表明,该系统能够有效指导患者完成整套康复训练动作,数据读取准确,指导精准可靠,交互性强,可以帮助我国约600万脑卒中手部运动功能障碍患者进行康复训练,具有很强的应用价值。

    Abstract:

    When patients with hand dysfunction practice rehabilitation movements by themselves at home, the training steps are confusing due to the lack of scientific guidance, and the precision and intensity of the movements are difficult to be guaranteed, thus affecting the rehabilitation effect. In this paper, an active hand training system based on Arduino and STM32 is designed. The system is divided into three major parts: data glove, movement guiding palm and upper computer, The data glove obtains and processes the rotation angle data of the fingers and wrist through sensors, and then transmits the data wirelessly to the movement guidance palm, and the controller STM32 in the movement guidance palm compares the received data with the standard movement database, analyzes the movement standard, and then instructs the patient to make adjustments by voice.STM32 drives six digital servos to drive the movement of the bionic palm according to the movement data, thus imitating the human movement. The system uses the LD3320 to recognize patient commands and perform human-computer interaction. The system downloads the standard movement database to the STM32 external flash memory through the upper computer, which is used to compare the patient's hand movement data. The experimental results show that the system can effectively guide patients to complete the whole set of rehabilitation training movements with accurate data reading, precise and reliable guidance, and strong interactivity. It can help about 6 million stroke patients with hand motor dysfunction in China for rehabilitation training, which has strong application value.

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董千恒,张秀再,许芝也.基于Arduino和STM32的主动式手部训练系统[J].电子测量技术,2023,46(3):114-120

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  • 在线发布日期: 2024-02-26
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