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系統識別號 U0026-0812200913520992
論文名稱(中文) 以二次小波轉換為依據之腦波節律特徵萃取及分類之研究
論文名稱(英文) A Study on the Feature Extraction and Classification of EEG Rhythms Based on Double Wavelet Transform
校院名稱 成功大學
系所名稱(中) 電機工程學系碩博士班
系所名稱(英) Department of Electrical Engineering
學年度 95
學期 2
出版年 96
研究生(中文) 吳庭宇
研究生(英文) Tyng-Yeu Wu
電子信箱 tyngyeu.wu@gmail.com
學號 n2694195
學位類別 碩士
語文別 中文
論文頁數 95頁
口試委員 指導教授-戴政祺
口試委員-陳天送
口試委員-毛齊武
口試委員-林志隆
中文關鍵字 癲癇  功率頻譜  腦波節律  二次小波轉換 
英文關鍵字 Double wavelet transform (DWT)  Power spectrum  Epilepsy  EEG rhythms 
學科別分類
中文摘要 在腦波信號的研究過程中,已有許多研究利用不同演算法去分析各種時域或頻域的腦波信號。本研究的目的是找出正常腦波與異常腦波(癲癇波)對於節律上的特徵關係,觀察癲癇病灶對α、β、θ、δ、γ等節律異常能量放電的情形,以增加研究者或醫師判別上的正確性。本研究針對腦波非穩態信號,以小波轉換理論研究正常腦波與癲癇腦波之特徵差異。根據腦波信號不同節律的特性,提出二次小波分解重構不同頻率的濾波器,提取腦波訊號在不同節律的動態特徵,並由此重構各種節律功率頻譜轉換的動態腦部地形圖。為了研究癲癇病灶的腦波信號中各種節律的特性,本文針對正常人與癲癇病灶的病人的臨床腦波數據進行分析與比較,並分析幾組腦波信號各種節律的動態特性與規則。實驗結果證明,癲癇病人在無負擔清醒狀態下的γ節律、β節律、α節律、θ節律、δ節律與正常人有明顯的差異。
英文摘要 In the course of studying the Electroencephalogram (EEG), many researches have been using different algorithms to analyze the EEG signals in time- or frequency-domain. The purpose of our research is to find out the characteristics of rhythm on normal and abnormal (ex. epilepsy waves) EEG signals. The abnormal discharge of γ, β, α, θ and δ rhythms can be observed from the characteristics. And it can help the researcher or doctor to discriminate the EEG signals more accurately. In this study, the wavelet transform decomposition is employed to investigate the normal EEG and epilepsy EEG signals. On the basis of property of different EEG signal rhythms, double wavelet transform (DWT) decomposition is used for designing filters with different frequency characteristics to detect the features in power spectrum of different EEG rhythms, which are used to form the dynamic map of brain activity. In order to examine the dynamic characteristics of all sorts of rhythms which were generated by epilepsy patients, two kinds of clinical EEG data from normal person and epilepsy patient are analyzed and compared. The experimental results indicate that when compared with normal person, the γ, β, α, θ and δ rhythms of epilepsy patients are quite different under conscious state without any load.
論文目次 摘 要 I
ABSTRACT II
誌謝 III
目錄 IV
表目錄 VI
圖目錄 VII
第一章 緒論 1
1.1研究背景 1
1.2 國內外相關文獻回顧 2
1.3 研究動機 5
1.4 研究目的 6
第 二 章 研究背景 7
2.1腦波之生理概述 7
2.2 腦波簡介 8
2.2.1 腦波的生成與特性 8
2.2.2電極的放置與組成範示 10
2.2.3 腦電波之頻率與節律的分類 13
2.3 常見的異常腦波與癲癇症狀簡介 14
2.3.1 常見的異常腦波簡介 14
2.3.2 癲癇症狀簡介 15
第 三 章 理論 19
3.1 小波原理 19
3.2 多分辨率小波應用於腦波節律分析 20
3.2.1 腦波節律特徵提取的定義 20
3.2.2 Mallat演算法在腦波節律上的應用 22
3.3功率上的小波轉換 25
3.3.1 功率上的小波轉換 25
3.3.2 功率上小波轉換檢驗說明 27
第 四 章 資料處理與統計分析討論 30
4.1 臨床數據的取得 30
4.2資料處理流程 32
4.2.1 資料處理流程的內部結構 32
4.2.2 第一次小波節律萃取 33
4.2.3 第二次小波轉換 43
4.3 正常腦波統計與探討 50
4.4異常腦波分析與統計探討 70
第 五 章 結論與未來展望 89
5.1結論 89
5.2未來展望 90
參考文獻 91
自述 95
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