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姓名 謝孟桓(Meng-Huan Hsieh)  查詢紙本館藏   畢業系所 機械工程學系
論文名稱 以經驗模態分解法為基礎的非線性分析應用於妥瑞氏症全腦腦波分析
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摘要(中) 妥瑞氏症是一種常見的神經內科疾病,好發於男性孩童及青少年,主要的症狀是
動作型,如快速而短促的眨眼睛、噘嘴、裝鬼臉;以及聲語型,如清喉嚨、大叫。目
前缺乏單一的標準來判定是否為妥瑞氏症。臨床上多以精神疾病診斷與統計手冊及耶
魯抽動症整體量表為妥瑞氏症疾病輔助診斷及區分嚴重程度。
本研究以妥瑞氏症患者的全腦腦電波數據為素材(包含張眼與閉眼兩種情形之腦 電波數據)。藉由經驗模態分解法及尺度相關的固有熵分析,找尋與妥瑞氏症相關的動 態生醫指標。研究得到的動態生醫指標可以作為妥瑞氏症臨床診斷的輔助工具。此 外,也使用量化的腦波特徵參數與 YGTSS 之間的關係,建立新的指標應用於妥瑞氏症 嚴重程度的參考。
本研究發現,能量密度與尺度相關的固有熵用在實驗組與對照組間存在有顯著的 統計差異(P<0.001)。能量密度的動態生醫指標與 YGTSS 之間的關係存在一定的相關性 (R = 0.39)。隨著嚴重程度的上升,高頻腦波能量密度呈負相關,低頻腦波能量密度呈 正相關。然而,尺度相關的固有熵在與 YGTSS 的相關性並沒有能量密度來的好。
本研究根據張眼能量密度定義的動態生醫指標在診斷妥瑞氏症上有較佳的表現。
由閉眼能量密度定義的動態生醫指標則與妥瑞氏症的嚴重程度有較佳的相關性。與診
斷妥瑞氏症相關的動態生醫指標多來自於右前腦區。然而本研究存在樣本不足的問
題,期待能後續的研究中能得到更多的樣本,提升研究成果在臨床在的應用價值。
摘要(英) Tourette syndrome (TS) is a common neurological disorder. Most of patients are male children and adolescents. TS is characterized by motor tics and vocal (phonic) tics, such as eye blinking, grinning, grimacing, throat clearing, and shouting. So far, there is no clinical standard for diagnosing the TS. The Diagnostic and Statistical Manual of Mental Disorders (DSM) and Yale Global Tic Severity Scale (YGTSS) are two common tools for diagnosing and evaluating TS.
In this study, whole-brain electroencephalography (EEG) recordings, for two examination conditions of eye-open and eye-closed, were analyzed by empirical mode decomposition (EMD) and scale-dependent intrinsic entropy analysis. The aim of this study is to figure out the dynamic biomarkers for characterizing TS. These dynamic biomarkers are helpful for diagnosing TS as a complementary tool in clinical practices. Furthermore, we defined a new assessment according to the relationships between the dynamical biomarkers and YGTSS for evaluating the severity of TS.
As our findings, the statistical differences between the control and experimental groups are significant (p-value < 0.001) for many dynamic biomarkers, using the energy densities on specific channel within specific frequency bands. The dynamic biomarkers using energy densities are significantly correlated with YGTSS (the correlation coefficient is 0.39). The high-frequency energy density increases with the increase of YGTSS, and the low- frequency energy density decreases with the increase of YGTSS. The diagnostic performance using the biomarkers of energy density is better than that using biomarkers of entropies.
In summary, the biomarkers using energy densities with eye-closed performed ii
better than those using energy densities with eye-open did. The new assessment using the energy densities with eye-open is significantly correlated to the severity of TS represented by YGTSS. Most of the dynamic biomarkers locate on the right hemisphere and frontal lobe. However, only a limited number of subjects were investigated in this study. The findings of this study cannot be used in clinical practices before a sufficient number of subjects are investigated in the future works.
關鍵字(中) ★ 非線性分析
★ 腦波
★ 經驗模態分解法
★ 尺度相關的固有熵
★ 妥瑞氏症
關鍵字(英) ★ nonlinear analysis
★ electroencephalogram
★ Empirical Mode Decomposition
★ scale-dependent intrinsic entropy
★ Tourette
論文目次 中文摘要 .............................................................................................................................i Abstract...............................................................................................................................ii 誌謝 ...................................................................................................................................iv 目錄 ...................................................................................................................................vi 圖目錄 ...............................................................................................................................ix 表目錄 ...............................................................................................................................xi 符號說明 ..........................................................................................................................xii 第一章 緒論......................................................................................................................1
1-1 研究背景 ............................................................................................................ 1
1-2 文獻回顧-腦波分析 ........................................................................................... 2
1-3 研究動機 ............................................................................................................ 5
1-4 論文架構 ............................................................................................................ 8
第二章 實驗設計與分析方法........................................................................................10
2-1 腦波採集實驗設計 .......................................................................................... 10
2-1-1 腦波採集環境 .......................................................................................... 10
2-1-2 人類研究倫理審查委員會(IRB)認證 ..................................................... 10
2-1-3 實驗設計 .................................................................................................. 11
2-2 分析方法 .......................................................................................................... 12
2-2-1 希爾伯特-黃轉換 (Hilbert-Huang Transform) ....................................... 12
2-2-2 尺度相關的固有熵 (Scaled-dependent Intrinsic Entropy) ..................... 21
2-2-3 統計分析 .................................................................................................. 25
vi
第三章 腦波分析與結果................................................................................................32
3-1 腦波數據頻率分解 .......................................................................................... 32
3-1-1 腦波數據的選擇 ...................................................................................... 32
3-1-2 IMFs 的分解 ............................................................................................ 33
3-1-3 IMF 頻率的訂定 ...................................................................................... 34
3-2 能量密度量化分析 .......................................................................................... 35
3-2-1 量化結果 .................................................................................................. 36
3-2-2 統計上的結果 .......................................................................................... 36
3-2-3 能量密度與 YGTSS 相關性 ................................................................... 37
3-3 訂定閥值及閥值的應用 .................................................................................. 41
3-3-1 閥值訂定方式 .......................................................................................... 41
3-3-2 閥值用於疾病區分的效果 ...................................................................... 42
3-3-3 通過動態生醫指標個數與 YGTSS 量表的相關性 ............................... 42
3-4 尺度相關的固有熵量化分析 .......................................................................... 46
3-4-1 尺度相關的固有熵量化結果 .................................................................. 46
3-4-2 尺度相關的固有熵與 YGTSS 的相關性 ............................................... 46
3-4-3 尺度相關的固有熵用於疾病區分的效果 .............................................. 50
3-4-4 通過生物標記點個數與 YGTSS 的相關性 ........................................... 50
第四章 討論與未來展望................................................................................................53
4-1 研究限制 ......................................................................................................... 53
4-1-1 數據的限制 .............................................................................................. 53
4-2 研究發現......................................................................................................... 54
4-2-1 研究結果 .................................................................................................. 54
4-2-2 根據本研究的結果推論 .......................................................................... 55 4-3 未來展望 ......................................................................................................... 55
4-3-1 再多收取一組非妥瑞氏症患者做驗證組,對本研究提出改善的方法 55
4-3-2 改用神經網路區分妥瑞氏症的嚴重程度 .............................................. 56
4-3-3 觀察妥瑞氏症患者與非妥瑞氏症患者在多次張閉眼過程中能量變化
情形 56
參考 .................................................................................................................................. 57
附錄一 ..................................................................................................................................
附錄二 ..................................................................................................................................
參考文獻 [1] Centers for Disease Control and Prevention(CDC), “Prevalence of diagnosed Tourette Syndrome in persons aged 6-17 years – United States, 2007.”, MMWR Morb Mortal Wkly Rep., 58(21): 581-5, 2009.
[2] 陳旺金,「臨床探討-妥瑞氏症的診斷與治療」,中醫藥研究論叢,14 卷 1 期, 76 – 84 頁,2011 年 3 月。
[3] S. Bohlhalter, A. Goldfine, S. Matteson, G. Garraux, T. Hanakawa, K. Kansaku R. Wurzman, M. Hallett, “Neural correlates of tic generation in Tourette syndrome: an event-related functional MRI study”, Brain., 129(Pt 8):2029-37, 2006 Aug.
[4] Richard D. Sweet, Gail E. Solomon, Henriette Wayne, Elaine Shapiro, Arthur K. Shapiro, “Neurological features of Gilles de la Tourette’s syndrome”, J Neurol Neurosurg Psychiatry, 36(1), PP.1-9, 1973.
[5] 王煇雄,「台灣兒科醫學會第 165 屆學術演講會教育演講-兒童妥瑞症簡介」,台 灣兒科醫學會雜誌,42(s),8-12 頁。
[6] Joseph Jankovic, “PHENOMENOLOGY AND CLASSIFICATION OF TICS.”, Neurologic Clinic, Volume 15, Issue 2, Pages 267–275, 1997.
[7] MM Robertson, “The Gilles de la Tourette syndrome: the current status”, The British Journal of Psychiatry, 154(2), PP.147-169, 1989.
[8] Leckman JF, Riddle MA, Hardin MT, Ort SI, Swartz KL, Stevenson J, Cohen, DJ, "The Yale Global Tic Severity Scale: initial testing of a clinician-rated scale of tic severity.", Journal of the American Academy of Child and Adolescent Psychiatry, 28 (4), PP.566– 73, 1989.
[9] 楊嘉玲、孫惠玲,「「照顧者負荷」概念分析」,馬偕護理專科學校學報 ,3 期,15 - 27 頁,2003。
[10] Hunt, C. K., “Concepts in caregiver research. “, Journal of Nursing Scholarship, volume 35,issue 1, PP. 27-32, 2003.
[11]謝玉玲、王煇雄,「影響妥瑞兒生活品質因素之剖析。」,台灣醫界,45(8), PP.16-20,2002。
[12] Diamond, Ellen.A, “Gene Defect May BeLinked to Tourette′s Syndrome.” Psychiatric Times, 20(12), PP.28-30, 2003.
[13]李美銀,「妥瑞症患童父母親職壓力、因應方式及其相關因素之探討」,台灣博碩 士論文,2003。
[14]刘智胜、王慧燕、林庆、左启华,「Tourette 综合征的神经心理综合研究」,中国

57
心理卫生杂志,第 12 卷 第 3 期,1998 年
[15] Daniel A. Gorman, Hongtu Zhu, George M. Anderson, Mark Davies, Bradley S., Peterson, “Ferritin Levels and Their Association With Regional Brain Volumes in Tourette’s Syndrome”, Am J Psychiatry, 163(7), PP.1264-1272, 2006.
[16] 衛生福利部屏東醫院 醫療部:腦波檢查, 2008 年 5 月 7 日,取自 http://www.pntn.mohw.gov.tw/?aid=509&pid=0&page_name=detail&iid=13。
[17] Niedermeyer E., da Silva F.L., Electroencephalography: Basic Principles, Clinical Applications, and Related Fields., Lippincot Williams & Wilkins, 2005.
[18] Benbadis S.R., “The EEG in nonepileptic seizures.”, J. Clin. Neurophysiol, 23(4), PP.340–352, 2006.
[19] Rami J Oweis, Enas W Abdulhay, “Seizure classification in EEG signals utilizing Hilbert-Huang transform”, BioMedical Engineering OnLine, 10:38, 2011.
[20] Jerald Yoo, Long Yan, Dina El-Damak, Muhammad Awais Bin Altaf, Ali H. Shoeb, Anantha P. Chandrakasan, “An 8-Channel Scalable EEG Acquisition SoC With Patient- Specific Seizure Classification and Recording Processor”, IEEE JOURNAL OF SOLID- STATE CIRCUITS, VOL. 48, NO. 1, JANUARY 2013.
[21] Chong, Derek J., Hirsch Lawrence J., “Which EEG Patterns Warrant Treatment in the Critically Ill? Reviewing the Evidence for Treatment of Periodic Epileptiform Discharges and Related Patterns”, Journal of Clinical Neurophysiology, 22 (2), PP.79-91, April 2005.
[22] 马仁飞、金恩凤,「366 例脑肿瘤脑电图和超声波检查的比较研究」,安徽医学院学 报,04 期,1985 年。
[23] JG Yu, Y Wei, SY Zhao, CC Zou, Q Shu, “Aseptic Meningoencephalitis in Children with Kawasaki Disease”, HK J Paediatr, 15, PP.270-275, 2010.
[24] Ian H. Gotlib, “EEG Alpha Asymmetry, Depression, and Cognitive Functioning”, Cognition and Emotion, 12(3), PP.449-478, 1998.
[25] Allan Krumholz, Harvey S. Singer, Ernest Niedetmeyer, Rose Burnite, Kenneth Harris, “Electrophysiological Studies in Tourette’s Syndrome.”, Ann Neurol, 14(6), 638-41, 1983.
[26] Heideman M. T., Johnson D. H., Burrus C. S., “Gauss and the history of the fast Fourier transform.”, IEEE ASSP Magazine., 1 (4, PP.14–21., 1984.
[27] Sunao Uchida, Irwin Feinberg, Jonathan D March, Yoshikata Atsumi, Tom Maloney, “A 58

Comparison of Period Amplitude Analysis and FFT Power Spectral Analysis of All- Night Human Sleep EEG.”, Physiol Behav, Volume 67, Issue 1, PP. 121-131, August 1999.
[28] Bruce A., Donoho D., and Gao H.Y., “Wavelet analysis.”, IEEE Spectrum, 33(10), PP.26-35, 1996.
[29] Akin M., Kiymik, M.K., “Application of periodogram and AR spectral analysis to EEG signals.” J. Med. Syst., 24(4), 247-56, 2000.
[30] Norden E. Huang, et al., "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis.", Proc. R. Soc. Lond. A, 454(1971), PP. 903–995, 1998.
[31] J-R Yeh, C-K Peng, NE. Huang, “Scale-dependent intrinsic entropies of complex time series.”, Philos Trans A Math Phys Eng Sci., 374(2065), 20150204, Apr. 2016
[32] Akshaya R. Mane, Prof. Rajveer K. Shastri, Prof. Shashank D. “EMPIRICAL MODE DECOMPOSITION FOR EEG SIGNAL ANALYSIS”, International journal of current engineering and scientific research(IJCESR), volume 2, ISSUE 4, PP.33-38, 2015.
[33] Varun Bajaj, Ram Bilas Pachori, “Classification of Seizure and Nonseizure EEG Signals Using Empirical Mode Decomposition”, IEEE transactions on information technology in biomedicine, VOL. 16, NO. 6, PP.1135-1142, NOVEMBER 2012.
[34] Grassberger P, “Information and complexity measures in dynamical systems”, Information Dynamics., 256, PP.15-33, 1991.
[35] Junichiro Hayano, Fumiyasu Yamasaki, Seiichiro Sakata, Akiyoshi Okada, Seiji Mukai, Takao Fujinami, “Spectral characteristics of ventricular response to atrial fibrillation.” American Physiological Society, Volume 273, Issue 6, H2811-H2816, December 1997
[36] Madalena Costa, Ary L. Goldberger, C.-K. Peng, “Multiscale Entropy Analysis of Complex Physiologic Time Series”, Phys. Rev. Lett., 89(6), PP. 068102-1-4, July 2002.
[37] Raichle, M.E., MacLeod A.M., Snyder A.Z., Powers W.J., Gusnard D.A., Shulman G.L., “A default mode of brain function.”, Proc. Natl. Acad.Sci. U. S. A., 98(2), PP.676–682, 2001.
[38] Raichle M.E., Snyder A.Z., “A default mode of brain function: a brief history of an evolving idea.”, NeuroImage, 37(4), PP.1083–1090., 2007.
[39] Zhaohua Wu, Norden E. Huang, Steven R. Long, and Chung-Kang Peng, “On the trend, detrending, and variability of nonlinear and nonstationary time series”, PNAS, 104 (38), PP.14889-14894, September 18, 2007.
[40] 楊福生,廖旺才,「近似熵:一種適用於短數據的複雜性度量」,中國醫療器械雜 59

誌,21 卷 05 期,1997 年。
[41] Juliana Yordanova, Hartmut Heinrich, Vasil Kolev, Aribert Rothenberger, “Increased event-related theta activity as a psychophysiological marker of comorbidity in children with tics and attention-deficit/hyperactivity disorders”, NeuroImage, 32(2), PP.940-955, 2006.
指導教授 黃衍任(Yean-ren Hwang) 審核日期 2018-7-10
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