本文選題：腦電 + 正問題��； 參考：《鄭州大學》2012年碩士論文

【摘要】：借助于腦電圖(Electroencephalogram, EEG)對大腦皮層電位分布進行分析被視為是確定腦內(nèi)電活動源的一種行之有效的方法,一般在正常情況下,腦電圖描述的皮層電位都呈現(xiàn)出一定的規(guī)律性；然而,當腦組織發(fā)生病變或者功能改變時,相應(yīng)的規(guī)律性就會遭到破壞(比如說波形的改變),本文的研究目的就是利用有限元仿真模型對神經(jīng)興奮組織的電活動進行模擬,得到腦組織發(fā)生病變時在模型表面產(chǎn)生的電位分布,研究利用頭皮表面電位分布逆溯腦內(nèi)電活動偶極子源的優(yōu)化算法,從而協(xié)助癲癇等腦部疾病的診斷與臨床治療,同時也有助于更深入地探討大腦的神經(jīng)機理活動等。 腦電研究領(lǐng)域主要涉及兩個方面：腦電正問題和腦電逆問題,對腦電正問題的研究是求解逆問題的關(guān)鍵基礎(chǔ),正問題能否正確地得到計算直接影響到腦內(nèi)電活動源定位的準確性。本文基于均勻球和三層同心球模型利用有限元分析了大腦頭皮表面電位的分布情況,根據(jù)生物電磁場理論推導了求解腦電場的有限元方程,在給定偶極子作用下求解模型表面的電位分布,從而驗證了仿真模型的有效性,但是對比三層球頭模型與均勻球頭模型的仿真結(jié)果,前者表現(xiàn)出了較好的近似性。此外,進一步分析了不同頭模型下偶極子參數(shù)(位置、方向和大小)對皮層表面電位分布產(chǎn)生的影響,并在相同路徑下對這些差異進行比較分析,為以后各種頭模型下腦電正問題的求解提供借鑒信息。 最后借助于測得的頭皮電位數(shù)據(jù)逆推了產(chǎn)生腦內(nèi)電活動的興奮源,根據(jù)頭皮電位計算值與觀測值的最佳擬合來設(shè)計目標函數(shù),為了得到更穩(wěn)定、誤差最小且唯一的偶極源解,對目標函數(shù)進行正則化處理,并結(jié)合粒子群算法實現(xiàn)對目標函數(shù)的優(yōu)化,通過對施加約束條件矩陣前后的反演數(shù)據(jù)與測量數(shù)據(jù)進行比較,仿真結(jié)果表明施加約束條件后偶極子源的定位精確度要比正則化處理前有很大提高。
[Abstract]:The analysis of the cortical potential distribution by Electroencephalogram (EEG) is regarded as an effective method for determining the source of electrical activity in the brain. Generally, the cortical potential described by the electroencephalogram presents certain regularity under normal conditions; however, when the brain tissue changes or changes in function, it is appropriate. The regularity will be destroyed (such as the change of the waveform). The purpose of this study is to simulate the electrical activity of the nerve excited tissue by the finite element simulation model, obtain the potential distribution on the model surface when the brain tissue is diseased, and study the advantage of the potential distribution of the scalp surface potential distribution back to the dipole source of the electrical activity in the brain. The algorithm can assist in the diagnosis and clinical treatment of epilepsy and other brain diseases. It also helps to further explore the neural mechanism of the brain.
The field of electroencephalography is mainly involved in two aspects: the positive problem of EEG and the inverse problem of EEG. The research on the positive problem of EEG is the key basis for solving the inverse problem. The correctness of the problem can directly affect the accuracy of the location of the electrical activity source in the brain. The finite element analysis is used in this paper based on the uniform sphere and the three layer concentric ball model. The distribution of the surface potential of the cerebral scalp is derived, and the finite element equation for the solution of the electric field is derived according to the theory of the biological electromagnetic field. The potential distribution of the model surface is solved under the given dipole effect, and the validity of the simulation model is verified. However, compared with the simulation results of the three layer ball head model and the homogeneous spherical head model, the former shows the comparison. In addition, the influence of the dipole parameters (position, direction and size) on the cortical surface potential distribution under the different head models is further analyzed, and the differences are compared and analyzed in the same path, which can provide reference information for solving the problem of EEG positive in the subsequent head models.
Finally, by using the measured scalp potential data, the excitatory source that produces the electrical activity in the brain is pushed back, and the target function is designed according to the optimal fitting of the calculated value of the scalp potential and the observed value. In order to get more stable, minimum and only dipole source solution, the objective function is regularized and the target function is realized with the particle swarm optimization algorithm. The optimization of the number is compared with the measured data before and after the application of the constraint condition matrix. The simulation results show that the positioning accuracy of the dipole source is greatly improved after the application of the constraint conditions.
【學位授予單位】：鄭州大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：R338

【引證文獻】

相關(guān)博士學位論文 前2條

1 鄒凌;基于非線性優(yōu)化及獨立分量分析的腦電源定位研究[D];浙江大學;2005年

2 張迎春;有限元素法在三維各向異性腦電正問題及皮層成像技術(shù)中的應(yīng)用[D];浙江大學;2005年

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本文編號：2103103