本文關(guān)鍵詞： 失重 頭低位臥床實驗 腦電特征 典型相關(guān)分析 雙層統(tǒng)計模型　出處：《蘭州大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：航天員在失重飛行期間,大腦對其適應(yīng)重力變化、調(diào)節(jié)生理和心理反應(yīng),起著十分重要的控制作用。腦功能狀態(tài)的改變可能引起人體控制調(diào)節(jié)功能的紊亂,影響航天員的身體健康和航天任務(wù)的順利完成。在航天醫(yī)學(xué)領(lǐng)域,通過腦功能的研究發(fā)現(xiàn),失重或模擬失重會引起腦電的變化,這些變化可能與生理、心理功能的失調(diào)有關(guān)。但由于傳統(tǒng)失重腦研究綜合性的欠缺,以及多模態(tài)數(shù)據(jù)異構(gòu)性對相關(guān)分析帶來的困難,目前絕大多數(shù)失重腦電改變機(jī)制的研究都是來自間接性的推斷,很少有來源于數(shù)據(jù)相關(guān)分析的直接證據(jù)。 在此背景下,本文將典型相關(guān)分析方法引入到失重條件下的腦電變化與其他生理、心理變化的關(guān)系研究中。面對實際應(yīng)用情況,將典型相關(guān)分析與多層統(tǒng)計模型思想結(jié)合,提出了基于典型相關(guān)分析的雙層線性模型。利用典型相關(guān)分析對異構(gòu)數(shù)據(jù)的適應(yīng)性,在—6°頭低位臥床模擬失重條件下,從心血管功能、情緒狀態(tài)、認(rèn)知能力各方面對腦電的影響進(jìn)行相關(guān)分析。同時,針對腦電信號導(dǎo)極的位置分布,將各方面對腦電的影響在20個腦電電極位置上進(jìn)行具體的定位建模,確定可能發(fā)生功能性或結(jié)構(gòu)性變化的具體腦區(qū)域。并采用“K最近鄰分類器”來驗證典型相關(guān)分析建模方法的有效性。 通過典型相關(guān)建模分析發(fā)現(xiàn),模擬失重時腦電、情緒、認(rèn)知能力以及心血管功能均表現(xiàn)出一定程度的改變,其中心血管功能、認(rèn)知能力的改變與腦電的變化顯著相關(guān)。心血管功能主要與兩側(cè)顳區(qū)的腦電相關(guān),情緒相關(guān)的認(rèn)知能力與腦的頂枕區(qū)相關(guān),而注意以及其他基本認(rèn)知能力的改變主要與額區(qū)和中央?yún)^(qū)相關(guān)。分類驗證結(jié)果表明通過典型相關(guān)分析算法融合后的多模態(tài)特征具有更高的分類正確率,證實了典型相關(guān)分析方法在本文應(yīng)用中的可靠性和有效性。
[Abstract]:The astronauts in weightlessness during the flight, the gravity to adapt to changes in brain, regulate the physiological and psychological reactions, plays a very important role. The change of human brain function may control regulation function disorder caused by impact, astronaut's health and the smooth completion of the task space. In the field of space medicine, through the study of brain function found that weightlessness or simulated weightlessness will cause changes in EEG, these changes may be related to physiological, psychological function disorder. But because of the lack of traditional weight-loss comprehensive brain research, and the difficulty of multi-modal data heterogeneity of correlation analysis, the vast majority of the EEG change mechanism of weightlessness are from indirect the inferred that there was little direct evidence from the analysis data.
Under this background, the canonical correlation analysis method is applied to EEG changes in conditions of weightlessness and other physiological and psychological changes in the relationship. In the face of the actual application, the canonical correlation analysis and the idea of combining multilevel statistical model, we proposed a two-level linear model based on canonical correlation analysis. By using canonical correlation analysis of heterogeneous the data in weightlessness condition adaptability, 6 degree head down tilt simulated, from the cardiovascular function, emotional status, analyze the effects of the cognitive ability of the EEG. At the same time, the EEG signal guide position distribution, the influence of various aspects of EEG localization specific modeling in 20 EEG electrode position, determine the specific brain regions may have functional or structural changes. And the validity of canonical correlation analysis and modeling method of K nearest neighbor classifier ".
Through the typical modeling analysis, simulated weightlessness EEG, emotion, cognitive ability and cardiovascular function showed a certain degree of change, which was related to cardiovascular function, cognitive changes and EEG changes. Cardiovascular function is mainly related to EEG on both sides of the temporal region, emotional cognitive ability and brain the occipital region, and attention and other basic cognitive ability change mainly with frontal and central areas. The verification results show that the classification through multi-modal feature fusion algorithm of canonical correlation analysis with the correct classification rate is higher, has confirmed the method of canonical correlation analysis in this paper the application of reliability and validity.

【學(xué)位授予單位】：蘭州大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：R85

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本文編號：1444929