運用多變數經驗模態分解法於中風與腦白質病變病人之腦波 Mu rhythm 分析

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林芳禎(Fang-jhen Lin) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

運用多變數經驗模態分解法於中風與腦白質病變病人之腦波 Mu rhythm 分析
(Analysis of EEG Mu Rhythms in Stroke and Leukoaraiosis Patients Using Multivariate Empirical Mode Decomposition)

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摘要(中)

本研究目的在於使用腦電波量測腦白質疏鬆症病人及單側中風偏癱病人進行手部運動時，感覺運動區腦波律動的變化情形，並探討這類病人與正常人之間的差異。腦白質疏鬆症被認為是因為腦血液灌流不足所形成，常見於頸動脈狹窄的患者，並且合併較為顯著的認知和行為障礙，如表情淡漠及判斷力、反應能力與記憶力的下降。與腦白質病人類似的是，我們發現中風偏癱病人的感覺運動皮質Mu波 (sensorimotor Mu rhythm) 也會受到影響，且這些訊號難以使用一般的數位濾波器進行有效的萃取，故本研究採用多變數經驗模態分解法 (Multivariate empirical mode decomposition, MEMD) 進行受試者運動時的腦波萃取。
多變數經驗模態分解法能夠將不同腦波通道間，具有相同頻率性質的訊號，萃取在同一個內部模態函數 (Intrinsic mode function, IMF) 中，每一個內部模態函數具有可解析、有限帶寬、自我組成的特性，非常適合於進行隨機訊號的分析。本研究募集十位中風偏癱及十位腦白質病變患者，中風病患的受試者被要求執行每一秒、兩秒及三秒一次的自主默數穩態食指上抬運動，腦白質病變病患則是七秒一次食指上抬運動。研究成果發現，在中風病人與腦白質病變病患執行食指上抬運動時，都有運動後beta band事件相關同步律動（post-movement beta ERS）能量低下的狀況，因此可以推測運動後beta band事件相關同步律動將來或許可以作為評估病人運動功能的依據。

摘要(英)

This study aims to analyze movement-related sensorimotor Mu rhythm when leukoaraiosis patients and semi-paralyzed stroke patients were performing self-paced finger movement task. The investigation of differences between patients and normal subjects were also performed. Leukoaraiosis is a descriptive term used to describe neuroimaging findings of diffuse hemispheric white matter abnormalities mainly characterized by loss of myelin and/or ischemic injury. Leukoaraiosis is a major risk factor and prognostic factor for stroke. Similar to leukoaraiosis, we found the sensorimotor Mu rhythm in stroke patients are also affected in performing finger movement task. Since EEG signals are weak (μv) and stochastic, the use of traditional digital filter may be unable to well extract the stochastic sensorimotor rhythms which could result in the pitfall of underestimating subject’s responses. Accordingly, a novel tool, multivariate empirical mode decomposition (MEMD), was adopted in this study to exact the sensorimotor Mu rhythm in human brain.
The MEMD decomposes multi-channel EEG into sets of multi-channel intrinsic mode functions (IMF). Each set contains IMFs with similar frequency range across different channels, and each IMF is analytic, band-limited, and self-organized. The superiority of MEMD enables its capability in extracting stochastic signals. This study recruited ten stroke patients and ten leukoaraiosis patients. The stroke patients were asked to continuously perform the self-paced index finger tapping tasks, and the leukoaraiosis patients were asked to perform the movement once seven seconds. Our results demonstrated that the suppressed post-movement beta event-related desynchronizations (post-movement beta ERS) were found both in stroke and leukoaraiosis patients while performing finger movement tasks. It might be expected the measure of post-movement beta ERS could be a plausible index for evaluating patients’ motor function in future clinical applications.

關鍵字(中)

★ 腦電波
★ 中風
★ 腦白質疏鬆症
★ 多變數經驗模態分解法

關鍵字(英)

論文目次

目錄
中文摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VI
表目錄 VIII
第一章、緒論 1
1-1 前言 1
1-2 研究動機與目的 2
1-3 文獻探討 3
1-4 論文架構 4
第二章、理論簡介 5
2-1 大腦結構與功能 5
2-1-1 大腦與運動系統 7
2-1-2 腦電波 9
2-1-3 事件相關非同步/同步腦波律動 11
2-2 經驗模態分解法 13
2-3 多變數經驗模態分解法 16
第三章、實驗材料與研究方法 18
3-1 系統架構 18
3-2 研究對象 19
3-3 儀器設備 20
3-3-1 腦電波儀 20
3-3-2 電極配置 21
3-3-3 光閘電路板 23
3-4 分析方法 24
3-4-1 資料前處理 24
3-4-2 多變數經驗模態分解法 25
3-4-3 訊號重建 29
第四章、實驗結果與討論 30
4-1 中風偏癱受試者 30
4-1-1 中風病患與正常受試者比較 30
4-1-2 中風病患好側手與患側手比較 36
4-2 腦白質病變受試者 41
第五章、結論與未來展望 44
參考文獻 46

參考文獻

參考文獻
[1] 行政院衛生署統計公佈欄：100年度死因統計, http://www.doh.gov.tw/CHT2006/DM/DM2_2.aspx?now_fod_list_no=12335&class_no=440&level_no=3
[2] WHO: The top 10 causes of death, http://who.int/mediacentre/factsheets/fs310/en/
[3] Liou LM, Chen CF, Guo YC, Cheng HL, Lee HL, Hsu JS, Lin RT, and Lin HF, “Cerebral white matter hyperintensities predict functional stroke outcome”, Cerebrovascular Diseases, Vol. 29, pp. 22-27, 2010.
[4] Lee SJ, Kim JS, Lee KS, An JY, Kim WJ, Kim YI, Kim BS and Jung SL, “The leukoaraiosis is more prevalent in the large artery atherosclerosis stroke subtype among Korean Patients with ischemic stroke”, BMC Neurology, Vol. 8, pp. 31-36, 2008.
[5] Patankar T, Widjaja E. Chant H, McCollum C, Baldwin R, Jeffries S, Sutcliffe C, Burns A, and Jackson A., “Relationship of deep white matter hyperintensities and cerebral blood flow in severe carotid artery stenosis”, European Journal of Neurology, Vol. 13, pp. 10-16, 2006.
[6] Hakan AY, Arsava E M, Rosand J, Karen L., “Severity of leukoaraiosis and susceptibility to infarct growth in acute stroke”, Stroke, Vol. 39, pp. 1409-1413, 2008.
[7] Tashiro K, Ogata K, Goto Y, Taniwaki T, Okayama A, Kira J, and Tobimatsu S, “EEG findings in early-stage corticobasal degeneration and progressive supranuclear palsy: a retrospective study and literature review”, Clinical Neurophysiology, Vol. 117, pp. 2236-2242, 2006.
[8] Accolla EA, Kaplan PW, Maeder-Ingvar M, Jukopila S, Rossetti AO, “Clinical correlates of frontal intermittent rhythmic delta activity (FIRDA), Clinical Neurophysiology, Vol. 122, pp. 27-31, 2011.
[9] Yamada T, Okamura S,, Okazaki T, Ushiroyama T, Yanagawa Y, Ueki M, sugimoto O, Yamazaki H, Sugino M, Masui Y, “Leukoencephalopathy following treatment with carmofur: a case report and review of the Japanese literature”, Asia & Oceania J Obstet Gynaecol, Vol. 15, pp. 161-168, 1989.
[10] Harding BN, Alsanjari N, Smith SJ, Wiles CM, Thrush D, Miller DH, Scaravilli F, Harding AE, “Progressive neuronal degeneration of childhood with liver disease (Alpers’ disease) presenting in young adults”, Journal of Neurology Neurosurgery & Psychiatry, Vol. 58, pp. 320-325, 1995.
[11] Kuzuhara S, Ohkoshi N, Kanemaru K, Hashimoto H, Nakanishi T, and Toyokura Y, “Subacute leucoencephalopathy induced by carmofur, a 5-fluorouracil derivative”, Journal of Neurology, Vol. 234, pp. 365-370, 1987.
[12] Sakai N, Kawasaki Y, Imnaizumi T, Kanno S, Go H, Mitomo M, Ushijima Y, Suyama K, Ito M, Hashimoto K, and Hosoya M, “Two patients with focal segmental glomerulosclerosis complicated by cyclosporine-induced reversible posterior leukoencephalopathy syndrome”, Clinical Nephrology, Vol. 73, pp. 482-486, 2010.
[13] Pfurscheller G., “Event-related cortical desynchronization detected by power measurements of scalp EEG”, Electroencephalography and Clinical Neurophysiology, Vol. 42, pp. 817-826, 1977.
[14] Pfurtscheller G., “Quantification of ERD and ERS in the time domain”, Hand book of electroencephalography and clinical neurophysiology, Vol. 6, pp. 89-105, 1999.
[15] Pfurtscheller G., Aranibar A., “Evaluation of event-related desynchronization (ERD) preceding and following voluntary self-paced movement”, Electroencephalography and clinical neurophysiology, Vol. 46, pp. 138-146, 1979.
[16] Pfurtscheller G., Berghold A., “Patterns of cortical activation during planning of voluntary movement”, Electroencephalography and clinical neurophysiology, Vol. 72, pp. 250-258, 1989.
[17] Pfurtscheller G., Woertz M., Krausz G., Neuper C., “Distinction of different fingers by the frequency of stimulus induced beta oscillations in the human EEG”, Neuroscience letters, Vol. 307, pp. 48-52, 2001.
[18] Pfurtscheller G., “Event-related synchronization (ERS): an electrophysiological correlated of cortical areas at rest”, Electroencephalography and clinical neurophysiology, Vol. 83, pp. 62-69, 1992.
[19] Pfurtscheller G., “Central beta rhythm during sensorimotor activities in man”, Electroencephalography and clinical neurophysiology, Vol. 51, pp. 253-264, 1981.
[20] Salmelin R., Forss N., Knuutila J., Hari R., “Bilateral activation of the human somatomotor cortex by distal hand movements”, Electroencephalography and clinical Neurophysiology, Vol. 95, pp. 444-452, 1995.
[21] Antranik: The cerebral Hemispheres, http://antranik.org/the-cerebral-hemispheres/
[22] R.R.Seeley, P.Tate, and T.D.Stephens, Essentials of Anatomy and Physiology, 6/e, Boston: McGraw-Hill, 2007.
[23] Bear M F, Connors B W, Paradiso M A, Neuroscience: Exploring the Brain, 3rd Ed., Lippincott Williams & Wilkins, Baltimore, USA, 2007.
[24] Penfield W. and Rasmussen T., The cerebral cortex of man: A clinical study of localization of function, Macmillan, New York, 1990.
[25] Pfurtscheller G. , “Event-related EEG/MEG synchronization and desynchronization: basic principles”, Clinical Neurophysiology, Vol. 110, pp. 1842-1857, 1999.
[26] Chia-Lung Yeh , Hsiang-Chih Chang, Chi-Hsun Wu, and Po-Lei Lee, “Extraction of single-trial cortical beta oscillatory activities in EEG signals using empirical mode decomposition “, BioMedical Engineering OnLine, Vol 9, June 2010.
[27] E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N. C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis”, Proceeding of Royal Society A, Vol. 454, pp. 903-995, 1998.
[28] N. Rehman and D. P. Mandic, "Multivariate Empirical Mode Decomposition", Proceedings of the Royal Society A, Vol. 466, no. 2117, pp. 1291-1302, 2010.
[29] Instrument: V-Amp, http://www.brainproducts.com/productdetails.php?id=15&tab=5
[30] J. Malmivuo and R. Plonsey, Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagentic Fields, Oxford University Press, USA, 1955.
[31] 科學人：窺探大腦特刊, 遠流, 2011
[32] 台灣腦中風協會, http://www.stroke.org.tw/index.asp
[33] 台灣榮民總醫院教學研究部整合性腦功能研究小組：腦電波儀, http://ibru.vghtpe.gov.tw/eeg.htm
[34] 鄧華婷，「應用獨立成份分析法於大腦運動區近紅外光譜分析」，中央大學，碩士論文，2012。
[35] 林良達，「應用獨立成份分析法於大腦運動區近紅外光譜分析」，陽明大學，碩士論文，2010。

指導教授

李柏磊(Po-lei Lee)

審核日期

2013-8-8

推文