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基于MI-BCI的上肢在線運(yùn)動(dòng)康復(fù)原型系統(tǒng)

MI-BCI based online prototype system for upper limb rehabilitation

作者: 李明愛  羅新勇  崔燕  楊金福 
單位:北京工業(yè)大學(xué)電子信息與控制工程學(xué)院(北京<p>100124)</p><p></p>
關(guān)鍵詞: 運(yùn)動(dòng)想象腦電信號(hào);  上肢;  在線康復(fù);腦機(jī)接口;原型系統(tǒng) 
分類號(hào):R318.04
出版年·卷·期(頁碼):2017·36·3(273-278)
摘要:

目的 為實(shí)現(xiàn)單側(cè)肢體運(yùn)動(dòng)想象與實(shí)際運(yùn)動(dòng)康復(fù)的身體部位及運(yùn)動(dòng)模式的一致化,進(jìn)一步改善康復(fù)效果,本文設(shè)計(jì)了一種基于MI-BCI的上肢在線運(yùn)動(dòng)功能康復(fù)原型系統(tǒng)。方法 該系統(tǒng)主要包括以g.MOBIlab腦電儀為核心的運(yùn)動(dòng)想象腦電信號(hào)(motor imagery electroencephalogram, MI-EEG)實(shí)時(shí)采集模塊、在線處理模塊及機(jī)械手臂控制模塊等幾部分。利用 MATLAB和C語言混合編程及多線程技術(shù)完成對MI-EEG的實(shí)時(shí)采集、眼電偽跡去除、特征提取與分類,基于ARM9的S3C2440A微處理器設(shè)計(jì)機(jī)械手臂控制系統(tǒng),控制模塊與PC機(jī)間采用基于請求響應(yīng)模式的通信協(xié)議,用手臂伸/屈MI-EEG的分類結(jié)果實(shí)現(xiàn)對機(jī)械手臂伸/屈同運(yùn)動(dòng)模式的實(shí)時(shí)控制。結(jié)果 對5名受試者進(jìn)行實(shí)際測試,對手臂伸/屈MI-EEG的平均識(shí)別率為76.75%,驗(yàn)證了系統(tǒng)的實(shí)用性。結(jié)論 本系統(tǒng)具有良好的自適應(yīng)性和實(shí)時(shí)性,為研制出更加自然、可臨床應(yīng)用的上肢運(yùn)動(dòng)康復(fù)系統(tǒng)奠定了基礎(chǔ)。

Objective To achieve the unification of unilateral limb movement imagination and the actual movement rehabilitation, a MI-BCI based online prototype system is designed to improve the rehabilitation performance for upper limb motor function.Methods The system consists of the real-time motor imagery electroencephalogram (MI-EEG) acquisition module based on g.MOBIlab, the online processing module, the mechanical arm and control module, etc.The real-time acquisition, ocular artifact removal, feature extraction and classification of MI-EEG are applicable by hybrid programming with MATLAB and C Language, and as well as multithreading technology.The control module is designed for mechanical arm based on a microprocessor “S3C2440A”.The request response communication protocol between control module and personal computer is defined to control the corresponding extension/flexion action of mechanical arm during motor imagery.Results The average recognition rate of this system is 76.75% with 5 subjects being evaluated.Conclusions This system has excellent adaptability and real-time performance,which lay a solid foundation for development of more natural and advantageous clinical application system for upper limb rehabilitation.

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