sEMG信号实时检测及假肢手指控制的初步研究
发布时间：2019-01-04 08:14
【摘要】：由于意外伤害和疾病导致的上肢截肢患者日益增多，并且严重地影响着患者的正常生活，因此研究出一种可代替人手运动功能的假肢手是亟待解决的问题。随着生理信号研究的发展以及相应检测技术的进步，表面肌电信号（sEMG）由于无创性以及信号处理方法灵活，已广泛应用于临床医学、计算机控制、人工智能等方面，尤其是在假肢控制方面的应用，国内外学者已经进行了大量的研究，并取得了阶段性的成果，成为假肢控制的理想信号源。肌电假肢能辅助截肢患者日常生活、工作，并可减少患者的心理压力，具有直观、自然的特点，在临床康复中具有重要的意义。 sEMG信号用于假肢控制的前提是有效地拾取并分析人体表面的肌电信号，本文首先介绍了基于LabVIEW的多通道sEMG信号实时检测系统，该系统包括前置调理电路和软件编程两部分。其中前置调理电路由前级放大、带通滤波、50Hz陷波以及主放大部分组成，软件编程部分主要是完成对信号的采集以及分析、处理，它采用图形化的编程语言LabVIEW设计，包括信号的实时采集显示和时域、频域的特征分析显示。结合前臂表面肌电电极阵列以及手部运动机能实验系统，实验利用该系统采集并分析了受试者在力量增大时前臂肌肉的sEMG信号及其均方根、功率谱峰值。结果表明，课题设计的多通道sEMG信号实时检测分析系统能实现4通道sEMG信号的实时采集显示及其时频域特征分析，并且其均方根和功率谱峰值会随着力量水平的增加而增大，说明了sEMG信号可用于假肢手指输出力量的控制。 为了进一步研究sEMG信号在假肢控制中的应用，本课题设计了一个三指假肢手，并且选用步进电机作为驱动方式，通过数字信号处理器DSP TMS320F2812完成对不同力量水平下sEMG信号的实时检测分析，，并转换为相应的控制信号输出，驱动步进电机，从而控制假肢手输出力量。课题首先设计了基于DSP的sEMG信号实时检测分析系统，由sEMG信号前端采集电路以及DSP软件采集、分析部分组成，通过检测分析受试者手指在不同力量水平下的sEMG信号，获得sEMG信号与手指力量间的关系，然后利用数字信号处理器DSPTMS320F2812将手指在不同力量水平下拾取的sEMG信号，转换为相应的脉冲信号PWM，输出驱动步进电机，控制假肢手指输出力量的大小。此外，本课题还通过采集手指在不同运动姿态下的sEMG信号，控制假肢手屈伸运动。实验结果表明，手指在不同运动状态下收缩产生的sEMG信号能实现对假肢手指运动的控制。 本课题主要是对sEMG信号实时检测分析系统以及假肢控制进行了初步研究，设计的多通道sEMG信号实时检测分析系统能实现对sEMG信号的实时检测以及时域、频域的分析处理，并且拾取的sEMG信号可用于假肢控制的研究，从而为后续进一步研究基于模式识别的多通道sEMG信号在假肢手指运动姿态控制中的应用奠定了基础。
[Abstract]:Due to the increasing number of patients with upper limb amputation caused by accidental injuries and diseases, and the serious impact on patients' normal life, it is an urgent problem to develop a prosthetic hand that can replace the function of manual movement. With the development of physiological signal research and the development of corresponding detection technology, surface electromyography (sEMG) has been widely used in clinical medicine, computer control, artificial intelligence and so on because of its noninvasive and flexible signal processing methods. Especially in the application of prosthetic control, scholars at home and abroad have done a lot of research, and have achieved periodic results, and become an ideal signal source for prosthetic control. Myoelectric prosthesis can assist amputation patients in their daily life and work, and can reduce the psychological pressure of the patients. It has the characteristics of intuition and nature, and is of great significance in clinical rehabilitation. The premise of sEMG signal used in artificial limb control is to effectively pick up and analyze the EMG signal of human body surface. This paper first introduces a multichannel sEMG signal real-time detection system based on LabVIEW. The system includes two parts: preconditioning circuit and software programming. The preconditioning circuit is composed of preamplifier, bandpass filter, 50Hz notch and main amplifier. The software programming part mainly completes the acquisition and analysis of the signal, and it is designed with the graphical programming language LabVIEW. It includes real-time signal acquisition and display, time domain, frequency domain feature analysis and display. Combined with the forearm surface electromyography electrode array and the hand motor function experiment system, the sEMG signals, root mean square (RMS) and peak power spectrum of the forearm muscles were collected and analyzed with the system. The results show that the real-time detection and analysis system of multi-channel sEMG signal can realize the real-time acquisition and display of 4-channel sEMG signal and its time-frequency domain characteristic analysis, and the root mean square and the peak value of power spectrum will increase with the increase of power level. It is shown that sEMG signal can be used to control the output force of prosthetic finger. In order to further study the application of sEMG signal in artificial limb control, a three-finger prosthetic hand is designed in this paper, and the stepper motor is chosen as the driving mode. Through the digital signal processor (DSP TMS320F2812), the real-time detection and analysis of sEMG signal at different power levels are completed, and the corresponding control signal output is converted to drive the stepper motor to control the output force of the prosthetic hand. Firstly, a real-time detection and analysis system of sEMG signal based on DSP is designed, which is composed of sEMG signal front-end acquisition circuit and DSP software. The analysis part is composed of sEMG signal under different strength level. The relationship between the sEMG signal and the finger force is obtained, and then the sEMG signal picked up by the finger at different force levels is converted into the corresponding pulse signal PWM, output to drive the stepper motor by using the digital signal processor (DSPTMS320F2812). Control the output force of the prosthetic finger. In addition, the motion of prosthetic hand is controlled by collecting the sEMG signals of fingers in different motion positions. The experimental results show that the sEMG signal produced by finger contraction in different motion states can control the finger motion of prosthetic limb. This paper mainly studies the real time detection and analysis system of sEMG signal and the control of prosthesis. The design of multi channel real time detection and analysis system of sEMG signal can realize the real time detection of sEMG signal and the analysis and processing of time domain and frequency domain. And the picked up sEMG signal can be used in the study of prosthetic limb control, which lays a foundation for further research on the application of multi-channel sEMG signal based on pattern recognition in finger motion and attitude control of prosthetic limb.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TN911.7;R318.0
[Abstract]:Due to the increasing number of patients with upper limb amputation caused by accidental injuries and diseases, and the serious impact on patients' normal life, it is an urgent problem to develop a prosthetic hand that can replace the function of manual movement. With the development of physiological signal research and the development of corresponding detection technology, surface electromyography (sEMG) has been widely used in clinical medicine, computer control, artificial intelligence and so on because of its noninvasive and flexible signal processing methods. Especially in the application of prosthetic control, scholars at home and abroad have done a lot of research, and have achieved periodic results, and become an ideal signal source for prosthetic control. Myoelectric prosthesis can assist amputation patients in their daily life and work, and can reduce the psychological pressure of the patients. It has the characteristics of intuition and nature, and is of great significance in clinical rehabilitation. The premise of sEMG signal used in artificial limb control is to effectively pick up and analyze the EMG signal of human body surface. This paper first introduces a multichannel sEMG signal real-time detection system based on LabVIEW. The system includes two parts: preconditioning circuit and software programming. The preconditioning circuit is composed of preamplifier, bandpass filter, 50Hz notch and main amplifier. The software programming part mainly completes the acquisition and analysis of the signal, and it is designed with the graphical programming language LabVIEW. It includes real-time signal acquisition and display, time domain, frequency domain feature analysis and display. Combined with the forearm surface electromyography electrode array and the hand motor function experiment system, the sEMG signals, root mean square (RMS) and peak power spectrum of the forearm muscles were collected and analyzed with the system. The results show that the real-time detection and analysis system of multi-channel sEMG signal can realize the real-time acquisition and display of 4-channel sEMG signal and its time-frequency domain characteristic analysis, and the root mean square and the peak value of power spectrum will increase with the increase of power level. It is shown that sEMG signal can be used to control the output force of prosthetic finger. In order to further study the application of sEMG signal in artificial limb control, a three-finger prosthetic hand is designed in this paper, and the stepper motor is chosen as the driving mode. Through the digital signal processor (DSP TMS320F2812), the real-time detection and analysis of sEMG signal at different power levels are completed, and the corresponding control signal output is converted to drive the stepper motor to control the output force of the prosthetic hand. Firstly, a real-time detection and analysis system of sEMG signal based on DSP is designed, which is composed of sEMG signal front-end acquisition circuit and DSP software. The analysis part is composed of sEMG signal under different strength level. The relationship between the sEMG signal and the finger force is obtained, and then the sEMG signal picked up by the finger at different force levels is converted into the corresponding pulse signal PWM, output to drive the stepper motor by using the digital signal processor (DSPTMS320F2812). Control the output force of the prosthetic finger. In addition, the motion of prosthetic hand is controlled by collecting the sEMG signals of fingers in different motion positions. The experimental results show that the sEMG signal produced by finger contraction in different motion states can control the finger motion of prosthetic limb. This paper mainly studies the real time detection and analysis system of sEMG signal and the control of prosthesis. The design of multi channel real time detection and analysis system of sEMG signal can realize the real time detection of sEMG signal and the analysis and processing of time domain and frequency domain. And the picked up sEMG signal can be used in the study of prosthetic limb control, which lays a foundation for further research on the application of multi-channel sEMG signal based on pattern recognition in finger motion and attitude control of prosthetic limb.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TN911.7;R318.0
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