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一種運動想象腦機接口訓(xùn)練系統(tǒng)的設(shè)計

Training system for brain computer interface based on motor imagery

作者: 楊幫華  陸文宇  鄭曉明  劉麗 
單位:上海大學(xué)機電工程與自動化學(xué)院(上海 200072)
關(guān)鍵詞: 腦機接口;訓(xùn)練系統(tǒng);交互訓(xùn)練 
分類號:
出版年·卷·期(頁碼):2012·31·1(72-76)
摘要:

目的 為提高運動想象的腦機接口訓(xùn)練速度和效率,本文設(shè)計了一種訓(xùn)練系統(tǒng)。系統(tǒng)功能主要包括參數(shù)設(shè)置、EEG采集、特征提取、分類及其結(jié)果反饋、分類器模型建立。方法 在訓(xùn)練系統(tǒng)設(shè)計中,首先使用VC++編寫的腦電信號采集軟件獲取腦電信號,而后通過TCP/IP實現(xiàn)與MATLAB之間的數(shù)據(jù)傳輸,在MATLAB中實現(xiàn)特征提取與分類識別,并將識別結(jié)果實時反饋給受試者,使受試者能夠及時調(diào)整自身狀態(tài),并選擇合適的反饋方式,從而在較短時間內(nèi)生成有效的分類器模型。結(jié)果 該系統(tǒng)具有接口方便、功能強大、界面友好的特點,通過建立的在線系統(tǒng)對訓(xùn)練系統(tǒng)進行了初步檢驗。結(jié)論 該系統(tǒng)可使使用者進行方便有效的訓(xùn)練,進而縮短訓(xùn)練時間并提高腦機接口系統(tǒng)的識別正確率,為腦機接口應(yīng)用系統(tǒng)的實現(xiàn)奠定了基礎(chǔ)。

Objective To improve the training efficiency of brain computer interface(BCI)training based on motor imagery,the paper designs a training system including parameter setting,electroencephalography(EEG)acquisition,feature extraction,classification,feedback of results and the foundation of classifier model. Methods Firstly,the training system acquires the EEG signals of motor imagery by EEG acquisition software,and then transmits data to MATLAB with TCP/IP protocol.So the feature extraction and classification are realized in the MATLAB. After that,the training system feedbacks the recognition results with the progress bar at the same time,and allows subjects to adjust their status in the training. Finally the system generates an effective classification model by choosing a proper feedback mode in a short time. Results The characteristics of the system are convenient intervention,powerful function and friendly interface. A BCI online system is established to test the training system and an effective classification model can be completed in a relatively short period of time. Conclusions The training system can improve the recognition rate and shorten the training time for BCI application systems,which lays the foundations for BCI application systems.

參考文獻:

[1]楊幫華,顏國正,丁國清,等. 腦機接口關(guān)鍵技術(shù)研究[J]. 北京生物醫(yī)學(xué)工程,2005,24(4):308-310.
[2]Ricardo Ron-Angevin,Miguel Angel Lopez,and Francisco Pelayo,The Training Issue in Brain-Computer Interface:A Multi-disciplinary Field [J].IWANN. 2009, 5517: 666-673.
[3]伍亞舟,何慶華,黃華,等. 基于想象左右手運動腦機接口實驗研究及分析[J].生物醫(yī)學(xué)工程學(xué)雜志,2008,25(5):983-988.
[4]Daly JJ,Cheng R,Rogers J. Feasibility of a new application of noninvasive brain computer interface(BCI):a case study of training for recovery of volitional motor control after stroke[J]. Journal of Neurologic Physical Therapy,2009,33(4):58-65.
[5]袁玲,楊幫華,馬世偉. 基于HHT和SVM的運動想象腦電識別[J].儀器儀表學(xué)報,2010(3):649-654.
[6]萬柏坤,綦宏志,趙麗,等. 基于腦電Alpha波的腦-機接口控制實驗[J]. 天津大學(xué)學(xué)報,2006,39(8):978-984.
[7]楊幫華,劉麗,陸文宇,等.基于虛擬現(xiàn)實技術(shù)的腦機交互反饋系統(tǒng)設(shè)計[J].北京生物醫(yī)學(xué)工程,2011,30(4):401-404.

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