【摘要】：由于意外傷害和疾病導(dǎo)致的上肢截肢患者日益增多，并且嚴(yán)重地影響著患者的正常生活，因此研究出一種可代替人手運(yùn)動(dòng)功能的假肢手是亟待解決的問(wèn)題。隨著生理信號(hào)研究的發(fā)展以及相應(yīng)檢測(cè)技術(shù)的進(jìn)步，表面肌電信號(hào)（sEMG）由于無(wú)創(chuàng)性以及信號(hào)處理方法靈活，已廣泛應(yīng)用于臨床醫(yī)學(xué)、計(jì)算機(jī)控制、人工智能等方面，尤其是在假肢控制方面的應(yīng)用，國(guó)內(nèi)外學(xué)者已經(jīng)進(jìn)行了大量的研究，并取得了階段性的成果，成為假肢控制的理想信號(hào)源。肌電假肢能輔助截肢患者日常生活、工作，并可減少患者的心理壓力，具有直觀、自然的特點(diǎn)，在臨床康復(fù)中具有重要的意義。 sEMG信號(hào)用于假肢控制的前提是有效地拾取并分析人體表面的肌電信號(hào)，本文首先介紹了基于LabVIEW的多通道sEMG信號(hào)實(shí)時(shí)檢測(cè)系統(tǒng)，該系統(tǒng)包括前置調(diào)理電路和軟件編程兩部分。其中前置調(diào)理電路由前級(jí)放大、帶通濾波、50Hz陷波以及主放大部分組成，軟件編程部分主要是完成對(duì)信號(hào)的采集以及分析、處理，它采用圖形化的編程語(yǔ)言LabVIEW設(shè)計(jì)，包括信號(hào)的實(shí)時(shí)采集顯示和時(shí)域、頻域的特征分析顯示。結(jié)合前臂表面肌電電極陣列以及手部運(yùn)動(dòng)機(jī)能實(shí)驗(yàn)系統(tǒng)，實(shí)驗(yàn)利用該系統(tǒng)采集并分析了受試者在力量增大時(shí)前臂肌肉的sEMG信號(hào)及其均方根、功率譜峰值。結(jié)果表明，課題設(shè)計(jì)的多通道sEMG信號(hào)實(shí)時(shí)檢測(cè)分析系統(tǒng)能實(shí)現(xiàn)4通道sEMG信號(hào)的實(shí)時(shí)采集顯示及其時(shí)頻域特征分析，并且其均方根和功率譜峰值會(huì)隨著力量水平的增加而增大，說(shuō)明了sEMG信號(hào)可用于假肢手指輸出力量的控制。 為了進(jìn)一步研究sEMG信號(hào)在假肢控制中的應(yīng)用，本課題設(shè)計(jì)了一個(gè)三指假肢手，并且選用步進(jìn)電機(jī)作為驅(qū)動(dòng)方式，通過(guò)數(shù)字信號(hào)處理器DSP TMS320F2812完成對(duì)不同力量水平下sEMG信號(hào)的實(shí)時(shí)檢測(cè)分析，，并轉(zhuǎn)換為相應(yīng)的控制信號(hào)輸出，驅(qū)動(dòng)步進(jìn)電機(jī)，從而控制假肢手輸出力量。課題首先設(shè)計(jì)了基于DSP的sEMG信號(hào)實(shí)時(shí)檢測(cè)分析系統(tǒng)，由sEMG信號(hào)前端采集電路以及DSP軟件采集、分析部分組成，通過(guò)檢測(cè)分析受試者手指在不同力量水平下的sEMG信號(hào)，獲得sEMG信號(hào)與手指力量間的關(guān)系，然后利用數(shù)字信號(hào)處理器DSPTMS320F2812將手指在不同力量水平下拾取的sEMG信號(hào)，轉(zhuǎn)換為相應(yīng)的脈沖信號(hào)PWM，輸出驅(qū)動(dòng)步進(jìn)電機(jī)，控制假肢手指輸出力量的大小。此外，本課題還通過(guò)采集手指在不同運(yùn)動(dòng)姿態(tài)下的sEMG信號(hào)，控制假肢手屈伸運(yùn)動(dòng)。實(shí)驗(yàn)結(jié)果表明，手指在不同運(yùn)動(dòng)狀態(tài)下收縮產(chǎn)生的sEMG信號(hào)能實(shí)現(xiàn)對(duì)假肢手指運(yùn)動(dòng)的控制。 本課題主要是對(duì)sEMG信號(hào)實(shí)時(shí)檢測(cè)分析系統(tǒng)以及假肢控制進(jìn)行了初步研究，設(shè)計(jì)的多通道sEMG信號(hào)實(shí)時(shí)檢測(cè)分析系統(tǒng)能實(shí)現(xiàn)對(duì)sEMG信號(hào)的實(shí)時(shí)檢測(cè)以及時(shí)域、頻域的分析處理，并且拾取的sEMG信號(hào)可用于假肢控制的研究，從而為后續(xù)進(jìn)一步研究基于模式識(shí)別的多通道sEMG信號(hào)在假肢手指運(yùn)動(dòng)姿態(tài)控制中的應(yīng)用奠定了基礎(chǔ)。
[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.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TN911.7;R318.0

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