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研究生:曾昱渂
研究生(外文):Yu Wen Tseng
論文名稱:以多維特徵分析法分析帕金森氏病之微電極記錄
論文名稱(外文):Analysis of Microelectrode Recording for Parkinson’s Disease based on Multi-Feature
指導教授:李宜軒李宜軒引用關係
指導教授(外文):Yi Hsuan Lee
口試委員:李宜軒梁勝富蔡德明
口試委員(外文):Yi Hsuan LeeSheng Fu LiangDe Ming Tsai
口試日期:2014-07-08
學位類別:碩士
校院名稱:國立臺中教育大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:中文
論文頁數:50
中文關鍵詞:帕金森氏病深層腦電刺激微電極記錄動作電位
外文關鍵詞:Parkinson’s diseasedeep brain stimulationmicroelectrode recordingaction potential
相關次數:
  • 被引用被引用:1
  • 點閱點閱:195
  • 評分評分:
  • 下載下載:3
  • 收藏至我的研究室書目清單書目收藏:0
帕金森氏病 (Parkinson’s disease, PD) 是一種慢性中樞神經退化疾病,常見症狀有四肢肌肉顫抖或僵硬及運動障礙。由於帕金森氏病後期藥物治療效果有限,因此會採用深層腦電刺激 (Deep Brain Stimulation, DBS) 來進行更有效的治療。深層腦電刺激是將微電極藉由外科手術植入腦部特定區域,設定適當的參數持續給予電刺激,臨床上已證實可有效舒緩病人症狀。目前手術流程是先以核磁共振及腦部斷層影像配合立體定位軟體決定電極的初始植入軌跡,再於植入過程中持續觀察微電極記錄 (microelectrode recording, MER),由臨床醫師依其本身經驗判斷植入位置。這種方式缺乏客觀判斷條件,而且在手術中常需要反覆確認正確位置,大幅增加手術時間及醫療風險。
本篇論文內容分為兩個部分。第一部分將植入過程錄製的微電極記錄計算其特徵值,利用多維特徵分析法量化並分析微電極記錄在不同植入位置的變化,並提出一個準則判斷視丘下核 (subthalamic nucleus, STN) 的位置,希望能以系統性的判斷方式協助臨床醫師將電極植入預期目標。第二部分針對在STN中不同位置錄製的微電極記錄擷取其動作電位 (action potential),經由相空間轉換 (phase space reconstruction)、k-means clustering分群及對齊等方式判斷週圍神經元個數,同時分析動作電位波形特徵,希望能對STN中微電極記錄的錄製位置做更進一步的判斷。結果顯示相較於臨床醫師的主觀判斷,我們提出基於多維特徵分析法的判斷準則平均正確率為80%,確實可以協助醫生判斷STN位置。而STN中不同位置的微電極記錄在神經元個數及動作電位波形特徵方面也有差異,可以用來對STN做更精確的定位。

Parkinson’s disease (PD) is a progressive neurodegenerative disease, and its typical symptoms contain muscle tremor, rigidity, and bradykinesia. Today deep brain stimulation (DBS) is one of the most effective surgical treatments for Parkinson’s disease. After implanting electrical leads into the brain and setting suitable stimulation patterns, patient’s conditions usually can be relieved. Before the surgery, the basic implanting trajectory is decided according to CT/MRI images and stereotactic software. However, a neurosurgeon still has to identify the exact location based on the microelectrode recording (MER) signals and his subjective judgment. This approach not only lacks of objective determination, but also spends more time in the surgery for repeatedly judging the appropriate location.
We divided this paper into two parts. In the first part, we compute feature of MER and analysis of Multi-Feature to quantify and analyze the changes implanted microelectrode recording in a different location. We proposed a criterion to judge subthalamic nucleus (subthalamic nucleus, STN) position. We hope to use the systematically to assist doctor to judge the electrode implanted targets. In the second part, for MER signals recorded near the subthalamic nucleus, we extract and analyze the shape of action potentials in some detail. Before analyses action potentials are translated to phase space to decrease the interferences caused by time shifting and noise. After classifying and aligning action potentials based on their shapes, we can measure the number of originated neurons for each recorded MER signal.
The results show that multi-dimensional feature analysis of average accuracy rate of 80%, slope analyses can be really applied during the surgery to help the neurosurgeon identify the exact implanting target.

Abstract I
摘要 II
目錄 III
圖目錄 V
表目錄 VII
第一章 序論 1
1.1 帕金森氏病簡介 1
1.2 腦部深層刺激手術簡介 1
1.3 研究動機與目標 3
1.4 論文的內容架構 3
第二章 相關研究 4
2.1 動作電位偵測 4
2.2 特徵分析 7
2.3 動作電位分群對齊 10
第三章 多維特徵分析 12
3.1 MER訊號之組成方法 12
3.2 閥值偵測設計及特徵值計算方式 13
3.3 Activity map建製 14
3.4 多維特徵分析法結果 16
3.5 多維特徵分析法討論 21
第四章 波形特徵分析 22
4.1 動作電位分類 22
4.1.1 相空間轉換 22
4.1.2 動作電位分群與合併 25
4.1.3 分群對齊方法 28
4.2 波形特徵計算 28
4.3 分群結果與波形特徵分析結果 29
4.3.1 單段訊號分析結果 29
4.3.2 連續訊號分析結果 35
4.4 波形特徵討論 38
第五章 討論與未來展望 39
參考文獻 40
附錄A 病患之多維特徵分析結果 43

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