下肢表面肌电信号采集与处理系统设计与实现

发布时间：2018-04-18 09:11

本文选题：肌肉 + 表面肌电信号　；参考：《武汉理工大学》2012年硕士论文

【摘要】：当人体运动时,肌肉上方的皮肤表面将会产生出一种微弱的生物电信号,即表面肌电信号(surface electromyography, sEMG),这种生物电信号可以真实地反映出人体的运动状况,而且提取该信号的方法简便,具有无痛、无创等优点。研究人员通过运用科学的方法,能够从表面肌电信号中提取出反映肌肉疲劳程度、肢体运动意图等有用信息,所以生物电信号在肢体康复训练、智能假体、医学诊断等研究领域具有很高的研究价值。由于人体是一种优良的导体,其中充满着各种电磁干扰噪声,人体表面的肌电信号的幅值通常在mV级以下,而干扰噪声的幅值通常在mV级以上,所以从人体皮肤表面提取的肌电信号常常淹没在干扰噪声之中。为了提取有效的生物信息,在进行信号特征提取之前,需要放大有用信号,滤除干扰噪声。本文针对目前表面肌电信号研究中所存在的相关问题,提出了一种易于实现的下肢表面肌电信号采集与处理系统方案,并结合下肢康复训练机器人,对系统的实时性和稳定性进行实验测试。本文的研究内容主要包括以下四个方面： (1)在了解表面肌电信号国内外研究状况的基础上,描述了肌电信号的特征、产生机理,表面肌电信号的特征,以及人体下肢关节运动与下肢肌肉之间的关系。 (2)设计了表面肌电信号采集仪的硬件电路。系统地阐述了电路的整体结构设计,分模块叙述了电路的设计与组成,并对电路的原理、所采用的设计方法及所使用的元器件进行了详尽的介绍。 (3)设计并实现了表面肌电信号处理软件系统。叙述了软件的整体设计结构、开发环境,提出并实现了一种简单、高效的信号特征提取方案,利用已有的支持向量机开发包实现了运动意图的分类识别。 (4)给出了系统的测试环境及实验测试结果。叙述了下肢康复训练机器人的构造结构、工作机制,利用TCP协议实现了表面肌电信号处理系统与机器人控制系统之间的无差错通信。作为湖北省国际合作重点项目“多自由度下肢骨骼复位手术与康复训练机器人研究”的一部分,本文实现了对人体下肢表面肌电信号的采集、处理,并将本文的研究成果与下肢康复训练机器人研究成果相结合,初步实现了利用下肢运动动作控制机器人运动的目标。
[Abstract]:When the human body moves, the skin surface above the muscle will produce a weak bioelectrical signal, namely, the surface electromyography, which can truly reflect the movement of the human body.Moreover, the method of extracting the signal is simple, painless and non-invasive.By using scientific methods, researchers can extract useful information from surface EMG signals to reflect muscle fatigue, limb motion intentions, and so on, so bioelectrical signals are used in limb rehabilitation training and intelligent prosthesis.Medical diagnosis and other research areas have high research value.Because the human body is a kind of excellent conductor, which is full of various electromagnetic interference noise, the amplitude of the EMG signal on the human surface is usually below MV, and the amplitude of the interference noise is usually above the MV level.Therefore, EMG signals extracted from human skin surface are often submerged in interference noise.In order to extract effective biological information, it is necessary to amplify useful signals and filter interference noise before extracting signal features.Aiming at the problems existing in the research of surface electromyography (EMG) signals, this paper presents a scheme of collecting and processing the SEMG signals of the lower extremity which is easy to realize, and combines with the robot of lower extremity rehabilitation training.The real-time and stability of the system are tested.The research contents of this paper mainly include the following four aspects:1) on the basis of understanding the research status of surface electromyography (EMG) at home and abroad, this paper describes the characteristics of SEMG, the mechanism of EMG, the characteristics of SEMG, and the relationship between the joint motion of human lower extremity and the muscles of lower extremity.The hardware circuit of the surface EMG signal acquisition instrument is designed.The whole structure design of the circuit is described systematically. The design and composition of the circuit are described in detail. The principle of the circuit, the design method adopted and the components used are introduced in detail.The software system of surface EMG signal processing is designed and implemented.The overall design structure and development environment of the software are described. A simple and efficient signal feature extraction scheme is proposed and implemented. The existing support vector machine development kit is used to realize the classification and recognition of motion intention.The test environment and experimental results are given.The structure and working mechanism of the lower limb rehabilitation training robot are described. The error-free communication between the surface EMG signal processing system and the robot control system is realized by using the TCP protocol.As a part of Hubei Province international cooperation project, "Research on the robot of multi-degree-of-freedom lower extremity skeletal reduction and rehabilitation training", this paper has realized the acquisition and processing of EMG signals on human lower extremity surface.Combining the research results of this paper with the research results of the lower limb rehabilitation training robot, the goal of controlling the robot movement by using the lower extremity motion action is preliminarily realized.
【学位授予单位】：武汉理工大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：R318.0

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