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基于無線表面肌電信號采集的上肢動作識別

發(fā)布時(shí)間:2018-04-09 02:11

  本文選題:表面肌電 切入點(diǎn):信號采集 出處:《北京生物醫(yī)學(xué)工程》2016年06期


【摘要】:目的為識別上肢動作并應(yīng)用于人機(jī)交互領(lǐng)域以及為相關(guān)患者提供上肢康復(fù)訓(xùn)練,設(shè)計(jì)一個(gè)無線表面肌電信號采集及識別系統(tǒng)。方法系統(tǒng)主要由硬件部分與軟件部分組成。硬件設(shè)計(jì)方面,由增強(qiáng)型80C51作為各個(gè)模塊的控制中心。貼片電極采集的肌電信號,經(jīng)儀表放大器AD8422放大處理,并進(jìn)行A/D轉(zhuǎn)換,最后通過無線方式將信號發(fā)送給接收盒并傳送至PC。軟件設(shè)計(jì)方面,在VC平臺下,通過均方根、自回歸系數(shù)提取特征值,利用支持向量機(jī)算法進(jìn)行動作模式識別。結(jié)果設(shè)備的采集部分體積為37 mm×27 mm×15 mm,可方便地實(shí)現(xiàn)穿戴式,上位機(jī)部分則可以滿足對信號的各種分析以及作為人機(jī)交互界面。結(jié)論該系統(tǒng)可實(shí)現(xiàn)對患者的康復(fù)訓(xùn)練,也可擴(kuò)展到游戲娛樂。
[Abstract]:Objective to design a radio surface electromyography (EMG) acquisition and recognition system for the purpose of identifying upper limb movements and applying them to the field of human-computer interaction and providing rehabilitation training for related patients.Methods the system consists of hardware and software.In hardware design, enhanced 80C51 is used as the control center of each module.The electromyography (EMG) signals collected by the patch electrode are amplified by the instrument amplifier (AD8422) and converted into A / D. Finally, the signals are sent to the receiving box and transmitted to the PCs by wireless means.In the aspect of software design, in VC platform, the feature value is extracted by root mean square and autoregressive coefficient, and the action pattern recognition is carried out by support vector machine (SVM) algorithm.Results the volume of the acquisition part of the equipment is 37mm 脳 27mm 脳 15mm, which can be easily wearable, and the upper computer can satisfy all kinds of signal analysis and serve as the man-machine interface.Conclusion the system can achieve rehabilitation training for patients, but also can be extended to games and entertainment.
【作者單位】: 上海理工大學(xué)醫(yī)療器械與食品學(xué)院;上海健康醫(yī)學(xué)院醫(yī)療器械學(xué)院;
【基金】:上海市自然科學(xué)基金(14ZR1440100)資助
【分類號】:R49;TN911.7

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相關(guān)碩士學(xué)位論文 前2條

1 吳齊云;基于Kinect的上肢運(yùn)動康復(fù)交互系統(tǒng)研究[D];廣東工業(yè)大學(xué);2016年

2 高曉陽;基于多模態(tài)交互和反饋的虛擬康復(fù)系統(tǒng)研究[D];燕山大學(xué);2016年

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