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The Evaluation Research of Brain Activity Based on EEG

Author: QiaoShiNi
Tutor: ZhangSheng
School: Zhejiang Normal University
Course: Applied Computer Technology
Keywords: EEG Characteristic parameters Wavelet Neural Network Brain Activity
CLC: TN911.6
Type: Master's thesis
Year: 2011
Downloads: 49
Quote: 0
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Abstract


Obstacles assess brain function studies in recent years in the intellectual development of infants and young children, cognitive function, has made significant progress in many areas of the Alzheimer's brain for Disease Control and Prevention, brain fatigue monitoring brain function research. The study of brain function can be divided into subjective assessment method and objective evaluation method. Subjective evaluation method based on the experience of the establishment of the rating scale of the study of brain function, such as fatigue rating scale, schizophrenia Rating Scale, cognitive dysfunction rating scale, subjective evaluation method can not avoid the inherent validity and reliability Lower disadvantages. With advances in technology, an objective means to study brain function, but also in the evaluation of the level of activity of the brain, a quantitative measure. To this end, this article make full use of the advantages of the EEG in brain function analysis, based on a large number of experiments, system modeling, evaluation of a specific brain function corresponding to reflect the state of the brain active - brain activity, as cognitive science research and clinical medicine to provide a quantitative basis. This paper consists of three parts, as follows: The first part of overall brain function Research, research methods and problems in the merits based on the analysis of a variety of research methods, based on analysis of EEG brain active degree model. On top of this, a brief introduction of the generation mechanism of the EEG signal processing method of the collection method and the characteristics of the EEG time domain, frequency domain, time-frequency and non-linear dynamic analysis' using wavelet entropy of depression in patients with EEG complexity analysis. The second part is mainly carried out based on the EEG excitement, fear, sleepiness and awakened four emotional classification. The steps are as follows: (1) collection corresponding to the four emotional video clips; (2) collection of four emotional video playback test evoked EEG, and anti-jamming pretreatment; (3) extracted EEG AR model coefficients of the signal band energy and fractal dimension as a characteristic parameter; (4) based on principal component analysis for feature reduction; selected 10 of the most relevant leads Lead selection based on mutual information method (eventually), and using genetic algorithm for feature selection; (5) with the Fisher classifier based on the genetic algorithm and PCA-based Fisher classifier for classification of four types of emotional research, found that the former is higher than the latter recognition rate. The third part of the brain active in different emotional state of research. Activity modeling steps are as follows: (1) Acquisition of volunteers under different stimulus intensity the four emotions evoked EEG paper the emotional intensity of stimulation divided into none, weak, strong four grades, define its activity were 0,0.3,0.6,1; (2) to extract the characteristic parameters of the power spectrum and complexity; (3) using wavelet neural network model build brain activity. First, based on the definition of emotional signal network learning, validation and prediction. Fear of emotion, for example, modeling studies of brain activity. Collection of video clips of four different level of fear, and then collected Evoked Potentials, the Activity model assessment studies of brain activity. The results verify the credibility and accuracy of the model. In this paper, EEG analysis methods and activity model for further development of intellectual development, cognitive impairment assessment, Brain Disease Control and Prevention, brain fatigue monitoring study to provide a quantitative basis, with good prospects for application.

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