發(fā)布時(shí)間：2018-04-28 10:54

  本文選題：腦機(jī)接口 + 偽隨機(jī)編碼調(diào)制��； 參考：《南昌大學(xué)》2017年碩士論文

【摘要】：腦機(jī)接口(Brain-computer interface,BCI)是通過大腦直接控制外部設(shè)備實(shí)現(xiàn)與外部環(huán)境的交流,打破了傳統(tǒng)的大腦通過肌肉和外周神經(jīng)與外界的交流。如今,隨著腦機(jī)接口技術(shù)的迅速發(fā)展,科研工作者對于頻率調(diào)制的視覺誘發(fā)電位腦機(jī)接口(frequency modulation visual evoked potential BCI,f-VEP BCI)進(jìn)行了大量的研究,而對于偽隨機(jī)編碼調(diào)制的視覺誘發(fā)電位腦機(jī)接口(Pseudo-random code modulated VEP BCI,c-VEP BCI)的研究比較少,傳統(tǒng)的c-VEP BCI是使用一種或者說一個(gè)編碼及其時(shí)間移位來調(diào)制不同的刺激論標(biāo),限制了論標(biāo)數(shù)的增加,從而限制了BCI系統(tǒng)的信息傳輸率。本文從信學(xué)處理的方法以及提高c-VEP BCI的刺激論標(biāo)數(shù)出發(fā),對c-VEP BCI進(jìn)行了研究。基于一個(gè)偽隨機(jī)序列調(diào)制的VEP腦機(jī)接口是通過典型相關(guān)分析(Canonical correlation analysis,CCA)來優(yōu)化空域?yàn)V波器,使用模板匹配法(Template Matching Method,TMM)進(jìn)行論標(biāo)識別。而本文提出了通過信學(xué)分?jǐn)?shù)分析方法(Signal Fraction Analysis,SFA)來優(yōu)化空域?yàn)V波器,使用一類支持向量機(jī)(One Class Support Vector Machine,OCSVM)來分類識別論標(biāo),這兩種優(yōu)化空域?yàn)V波方法和兩種分類識別論標(biāo)方法可以互相組合,形成四種不同形式的方法,實(shí)驗(yàn)結(jié)果表明這四種方法都獲得了較高的論標(biāo)識別準(zhǔn)確率。本文又提出了基于多個(gè)偽隨機(jī)序列調(diào)制的VEP腦機(jī)接口,它是通過兩個(gè)不同的Golay碼和一個(gè)近完美序列來對論標(biāo)進(jìn)行分組調(diào)制,實(shí)現(xiàn)了具有48個(gè)論標(biāo)的刺激器,大幅度提高了刺激論標(biāo)數(shù)。通過典型相關(guān)分析進(jìn)行優(yōu)化空域?yàn)V波器,采用模板匹配法對論標(biāo)進(jìn)行分類識別,獲得了很高的分類識別率。本系統(tǒng)采用了8名實(shí)驗(yàn)者的數(shù)據(jù)進(jìn)行分析,識別準(zhǔn)確率的結(jié)果達(dá)到了94.95%。
[Abstract]:Brain-Computer Interface (BCI) is a direct control of the brain to control the external equipment to achieve communication with the external environment, breaking the traditional brain through muscle and peripheral nerves to communicate with the outside world. Nowadays, with the rapid development of brain-computer interface technology, researchers have done a lot of research on frequency-modulated modulation visual evoked potential BCIf-VEP BCIs. However, there is little research on pseudo-random code modulated VEP BCIc-VEP BCIP BCIP BCII, which is a pseudorandom coded modulation interface. The traditional c-VEP BCI uses one code or one encoding and its time shift to modulate different stimuli. It limits the increase of scalar number, and thus limits the information transmission rate of BCI system. In this paper, c-VEP BCI is studied based on the methods of information processing and the enhancement of the stimulus scalar of c-VEP BCI. Based on a pseudorandom sequence modulated VEP brain-computer interface, the canonical correlation analysis is used to optimize the spatial filter, and the template Matching method is used to identify the spatial filter. In this paper, the signal Fraction Analysis (SFAs) method is proposed to optimize the spatial filter, and a class of support vector machines (SVM) is used to classify and identify the criteria. These two optimal spatial filtering methods and two classification recognition theory methods can be combined with each other to form four different forms of methods. The experimental results show that these four methods have higher accuracy of theoretical identification. In this paper, a VEP brain-computer interface based on multiple pseudorandom sequence modulation is proposed, which modulates the standard by two different Golay codes and a near-perfect sequence, and realizes 48 stimulators with the target of the theory. It greatly increases the number of stimuli. Based on the canonical correlation analysis, the spatial filter is optimized, and the template matching method is used to classify and identify the criteria, and a high classification recognition rate is obtained. The system uses the data of 8 experimenters to analyze, and the result of recognition accuracy reaches 94.95%.
【學(xué)位授予單位】：南昌大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R318;TN911.7

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李茂全;魏慶國;盧宗武;;基于Golay序列調(diào)制的視覺誘發(fā)電位腦機(jī)接口系統(tǒng)[J];科學(xué)技術(shù)與工程;2015年26期

2 傅清秋;謝永華;湯波;張恒德;;基于組合核函數(shù)SVM沙塵暴預(yù)警技術(shù)的研究[J];計(jì)算機(jī)工程與設(shè)計(jì);2014年02期

3 李勃;;腦機(jī)接口技術(shù)研究綜述[J];數(shù)字通信;2013年04期

4 林顥;趙杰文;陳全勝;蔡健榮;周平;;近紅外光譜結(jié)合一類支持向量機(jī)算法檢測雞蛋的新鮮度[J];光譜學(xué)與光譜分析;2010年04期

5 袁軍;譚永東;任俊;;利用WinIo實(shí)現(xiàn)并口數(shù)據(jù)通信[J];計(jì)算機(jī)與現(xiàn)代化;2009年08期

6 涂春勇;張煒;;一種更長周期m序列的實(shí)現(xiàn)方法[J];電子工程師;2008年07期

7 葛瑜;楊鋼;;腦機(jī)接口系統(tǒng)中EEG信號特征提取與分類[J];微計(jì)算機(jī)信息;2008年18期

8 陳罡;趙正予;楊國斌;;近完美序列與m序列的分析和比較[J];電波科學(xué)學(xué)報(bào);2008年01期

9 張志輝;宋花榮;;m序列與Gold序列比較[J];信息技術(shù);2006年06期

10 楊立才,李佰敏,李光林,賈磊;腦-機(jī)接口技術(shù)綜述[J];電子學(xué)報(bào);2005年07期

相關(guān)碩士學(xué)位論文 前1條

1 鄭軍;基于穩(wěn)態(tài)視覺誘發(fā)電位的腦—機(jī)接口實(shí)現(xiàn)與研究[D];華南理工大學(xué);2012年

，

本文編號：1814962