含有手部运动反馈的穿戴式上肢运动功能重建系统

发布时间：2018-01-28 08:04

本文关键词： Edison 运动功能康复肌电桥自动寻点 Android交互神经肌肉电刺激　出处：《东南大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着全世界瘫痪病人数量的持续增长,康复医学研究领域的瘫痪病人肢体运动功能重建逐渐成为研究热点。目前各类医疗仪器普遍采用神经肌肉电刺激(NMES)方法,在外周神经系统上施加电刺激脉冲,使周边肌肉产生人工动作电位,完成预定的动作。与其它生物医学方法相比,功能电刺激(FES)具有使用方便、效果显著的优势。本课题组提出了"肌电桥"发明专利思想,研发了一种基于通信原理和肌电信号控制的运动功能重建系统,克服了传统NMES系统刺激模式单一、瘫痪病人主动参与度低等缺点。然而,前期研发的系统不够便携,且缺少手部运动的反馈功能,没有相应的评价机制。本论文基于课题组前期提出的"肌电桥"系统理论,将肢体运动功能重建系统移植到Intel公司的Edison嵌入式平台上,实现了可穿戴的效果,提高了系统的便携性能。同时,系统中增加了数据手套模块,可以检测并反馈手部的运动情况,从而将系统改进成闭环结构,丰富了系统功能,优化了用户体验。本文将穿戴式上肢运动功能康复系统划分为三个子系统进行详细阐述:"肌电桥"子系统紧贴"肌电桥"的概念,由肌电探测模块和电刺激模块组成,采用Socket网络通信。根据肌电探测模块获得的实时肌电信号,经过算法处理和通道映射,驱动电刺激模块产生幅度、频率等参数均可控的电刺激脉冲,实现实时远程无线肌电控制电刺激功能。自动寻点子系统基于多位点电极(Multi-pad)概念,由多位点电极板、电极驱动模块、电刺激模块和数据手套组成,模块间依旧采用Socket进行网络通信。通过电极驱动模块控制轮询选通多位点电极并在电极上输出电刺激脉冲,接着根据数据手套反馈的手部运动数据进行实时评价,最终自动找出对应于病人手部各运动功能的最佳刺激位点。人机交互子系统基于Android设备,研发了一系列APP与各模块配合实现人机交互功能。例如:与肌电探测模块配合实现肌电信号简易示波器的功能;与数据手套模块配合实现3D模拟手部运动状态的功能;与电刺激模块配合实现输出任意可调刺激脉冲电流的功能。三个子系统只是穿戴式上肢运动功能重建系统的典型应用,本系统具有很强的扩展性,可以基于各模块的基础功能继续拓展更多的应用方向。此外,Edison平台的开放性也有助于系统进入互联网移动医疗领域,在大数据、云计算的背景下获得海量康复数据,大大加速系统的优化创新进程。
[Abstract]:As the number of paralyzed patients around the world continues to grow. The reconstruction of limb motor function of paralyzed patients in the field of rehabilitation medicine has gradually become a hot topic. At present, neuromuscular electrical stimulation (NMES) is widely used in all kinds of medical instruments. Electrical stimulation pulse is applied to peripheral nervous system to produce artificial action potential and complete predetermined action. Compared with other biomedical methods, functional electrical stimulation (FESs) is easy to use. This paper puts forward the idea of "myoelectric bridge" invention patent, and develops a motion function reconstruction system based on communication principle and EMG signal control. It overcomes the disadvantages of single stimulation mode of traditional NMES system and low active participation of paralytic patients. However, the system developed in the early stage is not portable enough and lacks the feedback function of hand movement. There is no corresponding evaluation mechanism. Based on the "myoelectric bridge" system theory put forward earlier by the research group, the limb motor function reconstruction system is transplanted to the Edison embedded platform of Intel Company. The wearable effect is realized, and the portable performance of the system is improved. At the same time, the data glove module is added in the system, which can detect and feedback the movement of the hand, thus improving the system into a closed-loop structure. This paper divides the wearable upper limb motor rehabilitation system into three subsystems to elaborate in detail: the "myoelectric bridge" subsystem is close to the concept of "myoelectric bridge". It is composed of electromyography detection module and electrical stimulation module, and uses Socket network to communicate. According to the real-time EMG signal obtained by EMG detection module, it is processed by algorithm and mapped by channel. The amplitude and frequency of the driving electrical stimulation module are controlled. The automatic point finding system is based on the concept of Multi-Pad, which is driven by multi-site electrode board and electrode driving module. The electrical stimulation module and the data glove are composed of the modules, the Socket is still used for network communication between the modules, and the polling-gating multi-site electrode is controlled by the electrode driving module and the electrical stimulation pulse is output on the electrode. Then according to the data glove feedback hand movement data real-time evaluation, finally automatically find out corresponding to the patient's hand movement function of the best stimulation site. Human-computer interaction subsystem based on Android equipment. A series of APP are developed to realize man-machine interaction with each module. For example, the EMG simple oscilloscope is realized with the EMG detection module. Cooperating with data glove module to realize 3D simulation of hand motion state; The three subsystems are only typical applications of wearable upper limb motor function reconstruction system, and this system has strong expansibility. Can continue to expand the application direction based on the basic functions of each module. In addition, the openness of Edison platform will also help the system enter the field of mobile medical treatment on the Internet, in big data. In the background of cloud computing, massive rehabilitation data are obtained, which greatly accelerate the optimization and innovation process of the system.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R496

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