下肢外骨骼机器人智能传感系统设计及应用

发布时间：2018-07-15 13:59

【摘要】：下肢外骨骼机器人作为一种帮助截瘫患者或行动不便老人等重新恢复行走功能的关键康复医疗设备,可帮助患者康复或恢复部分运动功能。鉴于患者本身体质具有一定缺陷,必须避免二次伤害的发生,因此保证患者穿戴下肢外骨骼机器人行走时的安全性和舒适性至关重要。本文基于其功能需求及实际使用情况,研发了一套智能传感系统,用以保证下肢外骨骼机器人的安全可靠运行以及提高穿戴者的舒适度。分析下肢外骨骼机器人的功能需求,结合其研究现状,明确拟研传感系统方案和各传感器选型,进而设计相应功能实现电路并完成制作。通过搭建电路硬件平台实现传感器数据采集功能。根据传感器测量原理及信号输入输出特性曲线对传感器进行标定,使传感器的测量精度有了明显提高,满足系统功能需求。实现惯性测量单元平台设计制作,其能精确测量下肢外骨骼机器人在行走过程中的三维姿态数据以及步长、步高等步态数据,并将此数据反馈至主控系统,为其实时调整行走步态提供必备信息。基于压力传感器受力时序及大小判定行走步态周期以及进行阶段划分。基于压力传感器精确测量数据,利用零力矩原理计算得到下肢外骨骼机器人足底压力中心位置坐标,为其行走时保持良好的稳定性提供数据支持。实现系统对穿戴者运动意图的识别,基于传感系统各传感器功能,收集测试者穿戴下肢外骨骼机器人进行行走实验时各传感器数据,将此数据作为训练样本,利用支持向量机建模方法使下肢外骨骼机器人对实验训练样本进行学习训练。进一步,基于机器学习结果对穿戴者运动意图进行识别,并进行实验检测。结果表明,本方法在对穿戴者运动意图识别功能上取得了很好的效果。同时,本系统能有效地降低手动控制时,下肢外骨骼机器人从收到命令到执行命令的延时,能显著提升穿戴者的舒适感。
[Abstract]:The lower extremities exoskeleton robot, as a key rehabilitative medical device to help the paraplegia or the inconvenient old people to restore the walking function, can help the patients recover or recover part of the movement function. In view of the patient's own physical defects, it is necessary to avoid the occurrence of two injuries, thus ensuring the patient to wear the lower limb exoskeleton machine. In this paper, based on its functional requirements and actual use, a set of intelligent sensing system is developed to ensure the safe and reliable operation of the lower limb exoskeleton robot and to improve the wearer's comfort. According to the principle of the sensor and the characteristic curve of the input and output of the signal, the sensor is calibrated, and the measurement accuracy of the sensor is greatly improved. In order to realize the functional requirement of the foot system, the inertial measurement unit platform is designed and made. It can accurately measure the three dimensional attitude data and step size and step gait data of the lower limb exoskeleton robot in the walking process, and feed this data to the main control system to provide the necessary information for the actual adjustment of the walking state. The order and size determine the walking gait cycle and stage division. Based on the pressure sensor, the position coordinates of the foot pressure center of the lower limb exoskeleton robot are calculated by the principle of zero moment, which provides the data support for the good stability of the walking time. Each sensor function of the sensor system is used to collect the data of each sensor in the walking experiment of the lower limb exoskeleton robot. This data is used as a training sample, and the support vector machine modeling method is used to make the lower limb exoskeleton robot learn and train the experimental training samples. Further, based on the machine learning results, the wearer's movement is carried out. The results show that this method has a good effect on the wearer's movement intention recognition function. At the same time, when the system can effectively reduce manual control, the lower limb exoskeleton robot can significantly improve the wearer's comfort from the delay of receiving the command to the execution command.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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