本文關(guān)鍵詞：握力握速和FMRI環(huán)境下的任務(wù)狀態(tài)對(duì)腦活動(dòng)的影響　出處：《昆明理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 動(dòng)態(tài)腦網(wǎng)絡(luò) ELM FMRI 光纖傳感器

【摘要】：目前的腦機(jī)接口研究主要是集中在多領(lǐng)域多技術(shù)多模式的融合中進(jìn)行的復(fù)雜研究,既有BCI的多種運(yùn)動(dòng)大小速率的研究,也有FMRI環(huán)境下的任務(wù)狀態(tài)對(duì)腦活動(dòng)的影響,雖然很多在研工作已經(jīng)走出了實(shí)驗(yàn)室,甚至進(jìn)行了產(chǎn)業(yè)化發(fā)展,然而,很多工作并不精細(xì)。本文探討了握力握速和FMRI環(huán)境下的任務(wù)狀態(tài)對(duì)腦活動(dòng)的影響,得到了良好的結(jié)論,這對(duì)于未來(lái)腦電和FMRI的融合技術(shù)形成重大意義。論文的主要內(nèi)容如下:主要在以下幾個(gè)方面展開(kāi)研究,并取得了一定的成果:(1)基于腦機(jī)接口研究握力及想象對(duì)腦電活動(dòng)的調(diào)制機(jī)理,通過(guò)右手實(shí)際握力和想象握速的三種任務(wù)狀態(tài)進(jìn)一步證實(shí)握速及想象的腦電活動(dòng)是可以區(qū)分的,且握力值的大小也會(huì)對(duì)腦電值產(chǎn)生影響。通過(guò)CSP特征提取、SVM分類和腦網(wǎng)絡(luò)分析方法識(shí)別握速運(yùn)動(dòng)及想象是有效的,尤其是SVM分類最高可達(dá)SVM分類最高可達(dá)92%,握力及想象對(duì)運(yùn)動(dòng)對(duì)側(cè)腦區(qū)產(chǎn)生重要影響,將對(duì)腦電精細(xì)控制產(chǎn)生重要影響。(2)基于腦機(jī)接口研究握速及想象對(duì)腦電活動(dòng)的調(diào)制機(jī)理,通過(guò)左右手實(shí)際握速和想象握速的三種任務(wù)狀態(tài)進(jìn)一步證實(shí)握速及想象的腦電活動(dòng)是可以區(qū)分的,且握速值的大小也會(huì)對(duì)腦電值產(chǎn)生影響。通過(guò)CSP特征提取、SVM分類和腦網(wǎng)絡(luò)分析方法識(shí)別握速運(yùn)動(dòng)及想象是有效的,尤其是SVM分類最高可達(dá)93%,握速及想象對(duì)運(yùn)動(dòng)對(duì)側(cè)腦區(qū)產(chǎn)生重要影響,該研究的思路和方法可望做后續(xù)的相關(guān)研究(3)綜合前人的研究基礎(chǔ),綜述了 FMRI對(duì)腦活動(dòng)的調(diào)制研究,明確了 FMRI可以提供更直接和更精確的測(cè)量大腦活動(dòng)的快速變化,從而有助于BCI的發(fā)展,更提出了用于研究功能核磁共振環(huán)境下的腦區(qū)激活分布和腦網(wǎng)絡(luò)連接的握力球。
[Abstract]:The current BCI research is mainly focused on the multi-domain multi-technology and multi-mode fusion of the complex research, there are a variety of BCI research on the size and speed of motion. There is also the impact of task status on brain activity in the FMRI environment, although a lot of research work has been out of the laboratory, even industrial development, however. A lot of work is not elaborate. This paper discusses the impact of grip grip speed and task state in FMRI environment on brain activity, and draws a good conclusion. This is of great significance for the future of EEG and FMRI fusion technology. The main contents of this paper are as follows: mainly in the following aspects of research. Some achievements were obtained: (1) based on brain-computer interface, the modulation mechanism of grip force and imagination to EEG activity was studied. Through the right hand actual grip strength and imaginary grip speed of the three task states further confirmed that grip speed and imaginary EEG activity can be distinguished and the size of grip force value will also affect the EEG value. CSP feature extraction. SVM classification and brain network analysis are effective in identifying grip motion and imagination, especially in SVM classification up to 92% SVM classification. Grip strength and imagination have an important effect on the contralateral brain area, which will have an important effect on the fine control of EEG.) based on the brain-computer interface, the modulation mechanism of grip speed and imagination to EEG activity is studied. Through the left and right hand grip speed and imagination grip speed of the three mission states further confirmed that grip speed and imaginary EEG activity can be distinguished. And the size of the holding speed will also affect the EEG value. It is effective to identify the grip motion and imagination by CSP feature extraction and brain network analysis. In particular, the SVM classification can be up to 93 percent, grip speed and imagination have an important impact on the contralateral motor brain area. In this paper, the modulation of brain activity by FMRI is reviewed. It is clear that FMRI can provide more direct and accurate measurement of the rapid changes of brain activity, thus contributing to the development of BCI. Furthermore, a gripping ball was proposed to study the distribution of brain activation and the connections of brain networks under functional nuclear magnetic resonance (fMRI).
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP181;R318

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