博碩士論文 983211010 詳細資訊




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姓名 李開群(Kai-Chiun Li)  查詢紙本館藏   畢業系所 生物醫學工程研究所
論文名稱 使用虛擬實境系統誘發事件相關電位P300之研究
(A 3-D Virtual Reality Based Sensory Oddball Task for Eliciting P300)
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摘要(中) P300是由新異刺激程序誘發的事件相關電位,且它會受注意力影響。本研究的目的是使用3D虛擬實境技術建立一個能用來誘發體感覺P300的刺激程序。
本研究收錄了12位健康右撇子受試者,使用他們的慣用手在虛擬環境中進行接球實驗時之腦電波訊號。接球實驗有兩種刺激條件:標準刺激(有力回饋且經由力回饋系統傳遞)和靶刺激(無力回饋),發生率分別為80%和20% (各為479和121次)。本研究共收集32頻道腦電波,取樣頻率為250 Hz,分段長度為-500到+2500毫秒,觀測可能出現P300之時間區段為+248到+800毫秒,濾波使用截止頻率為0.1和59 Hz的帶通濾波器。腦波訊號先經平均處理後,再利用時空模板的雙重評定標準獨立成分分析法去移除眼動訊號。
結果顯示,所有受試者在Pz (P<0.001)、P3 (P<0.001)和P4 (P<0.001)頻道都有誘發P300,其平均振幅與平均潛伏期(±標準差)分別為8.1±3.4、7.2±3.8和6.5±3.2μV和549±108、617±125和563±129毫秒,而獨立成分分析法可移除眼動訊號,降低對腦波訊號的干擾。
本研究證實3D虛擬實境系統可用來誘發體感覺P300,而獨立成分分析法可使腦波訊號訊雜比提高,這表示虛擬實境技術能被用來進行腦功能的研究。虛擬實境技術可提供一個容易控制的虛擬環境,在未來,本研究之設計及參數可進行體感覺P300的研究,也可作為中風後運動功能復健之臨床研究的參考。
摘要(英) P300 is elicited in an oddball paradigm and associated with attention. In this study, we aim to establish a novel protocol using 3-D Virtual Reality technique to elicit the somatosensory P300 components.
Twelve healthy, right-handed subjects were instructed to perform a ball catch task using their dominant hand under a 3-D Virtual Reality scheme. The ball catch task has two conditions: standard (with force feedback) and target (without force feedback), with the 479 and 121 trials (i.e. 80% and 20% occurring rate), respectively. The feedback force in the standard condition was delivered to the subjects via a haptic feedback system. 32 channels electroencephalogram (EEG) were recorded with 250 Hz sampling rate during the task. The data were epoched from -500 to +2500 ms, and filtered with 0.1-59 Hz band-pass filter. The window of interest was set to be between +248 to +800 ms after ball catch. Independent Component Analysis (ICA) was employed to remove the electrooculogram (EOG) interference according to spatial and temporal criteria.
There is strong evidence suggesting that P300 components were elicited at Pz (p<0.001), P3 (P<0.001) and P4 (P<0.001) in all subjects. The mean peak amplitudes are 8.1±3.4, 7.2±3.8, and 6.5±3.2μV, and the mean peak latencies are 549±108, 617±125, and 563±129ms at Pz, P3 and P4, respectively. In addition, ICA could remove the EOG contamination effectively.
In conclusion, we have shown that 3-D Virtual Reality technique can be used to elicit the somatosensory P300 components reliably and Independent Component Analysis could increase the Signal-to-Noise Ratio of brain signals by removing the unwanted EOG components. It provides direct evidence that Virtual Reality technique is feasible for studying brain function. As VR technique can provide a simulated environment which is easy to manipulate and control, we believe that the outcome of this study could serve as a reference point of sensory P300 study and could most benefit the studies of motor recovery during rehabilitation after stroke in the future as in those studies, the control of task parameters is crucial.
關鍵字(中) ★ 3D虛擬實境
★ 腦電波圖
★ 體感覺P300
關鍵字(英) ★ 3D VR
★ EEG
★ somatosensory P300
論文目次 目錄
摘要 I
Abstract II
目錄 III
附圖目錄 V
附表目錄 VII
第一章 緒論 1
1.1研究動機與目的 1
1.2文獻回顧 2
1.3神經電生理與腦波 5
1.4腦電波儀簡介 8
1.5事件相關電位誘發技術 9
1.6虛擬實境系統簡介 12
1.7論文架構 13
第二章 研究方法與流程 14
2.1實驗設計 14
2.2實驗流程 15
2.3實驗器材 17
2.4實驗參數 19
2.5資料分析 22
2.6獨立成分分析簡介 24
2.7偽跡移除的評定標準 26
2.8統計檢定 27
第三章 實驗結果 29
3.1接球準確率 29
3.2.1 Pz頻道資料 30
3.2.2 Cz頻道資料 32
3.2.3 CP1頻道資料 34
3.2.4 CP2頻道資料 36
3.2.5 FC1頻道資料 38
3.2.6 FC2頻道資料 40
3.2.7 P3頻道資料 42
3.2.8 P4頻道資料 44
3.3總平均 47
3.4雙側差異 50
3.5訊號分解和偽跡移除 52
3.6.1偽跡移除後Pz頻道資料 65
3.6.2偽跡移除後Cz頻道資料 66
3.6.3偽跡移除後CP1頻道資料 67
3.6.4偽跡移除後CP2頻道資料 68
3.6.5偽跡移除後P3頻道資料 69
3.6.6偽跡移除後P4頻道資料 70
3.6.7偽跡移除後FC1頻道資料 71
3.6.8偽跡移除後FC2頻道資料 72
3.7.1偽跡移除後Pz頻道相關係數之變化 75
3.7.2偽跡移除後Cz頻道相關係數之變化 76
3.7.3偽跡移除後CP1頻道相關係數之變化 77
3.7.4偽跡移除後CP2頻道相關係數之變化 78
3.7.5偽跡移除後FC1頻道相關係數之變化 79
3.7.6偽跡移除後FC2頻道相關係數之變化 80
3.7.7偽跡移除後P3頻道相關係數之變化 81
3.7.8偽跡移除後P4頻道相關係數之變化 82
3.8偽跡移除後拓樸圖之變化 83
3.9偽跡移除後波形之變化 83
第四章 討論與結論 99
4.1 P300振幅 99
4.2 P300潛伏期 101
4.3雙側差異 102
4.4認知功能 102
4.5偽跡移除後相關係數之變化 103
4.6偽跡移除結果 104
4.7造成偽跡移除不理想之可能原因 106
4.8結論 107
第五章 未來展望 108
參考文獻 109
附錄一:獨立成分取捨結果資料表 112
附錄二:受試者眼電訊號波形圖 118
參考文獻 參考文獻
1. Sanei, S. and J. Chambers, EEG signal processing. 2007, Chichester, England ; Hoboken, NJ: John Wiley & Sons. p. 1-2.
2. Duncan, C.C., et al., Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clin Neurophysiol, 2009. 120(11): p. 1883-908.
3. Polich, J., Updating P300: an integrative theory of P3a and P3b. Clin Neurophysiol, 2007. 118(10): p. 2128-48.
4. Verleger, R., P3b: towards some decision about memory. Clin Neurophysiol, 2008. 119(4): p. 968-70.
5. Kemner, C., et al., Auditory event-related brain potentials in autistic children and three different control groups. Biol Psychiatry, 1995. 38(3): p. 150-65.
6. Anokhin, A.P., et al., The P300 brain potential is reduced in smokers. Psychopharmacology (Berl), 2000. 149(4): p. 409-13.
7. O’’Donnell, B.F., et al., Auditory event-related potential abnormalities in bipolar disorder and schizophrenia. Int J Psychophysiol, 2004. 53(1): p. 45-55.
8. Porjesz, B., et al., The utility of neurophysiological markers in the study of alcoholism. Clin Neurophysiol, 2005. 116(5): p. 993-1018.
9. Caravaglios, G., et al., Decreased amplitude of auditory event-related delta responses in Alzheimer’’s disease. Int J Psychophysiol, 2008. 70(1): p. 23-32.
10. Klobassa, D.S., et al., Toward a high-throughput auditory P300-based brain-computer interface. Clin Neurophysiol, 2009. 120(7): p. 1252-61.
11. Brouwer, A.M. and J.B. van Erp, A tactile P300 brain-computer interface. Front Neurosci, 2010. 4: p. 19.
12. Sanei, S. and J. Chambers, EEG signal processing. 2007, Chichester, England ; Hoboken, NJ: John Wiley & Sons. p. 7-9.
13. Luck, S.J., An introduction to the event-related potential technique. Cognitive neuroscience. 2005, Cambridge, Mass.: MIT Press. p. 27-31.
14. Sanei, S. and J. Chambers, EEG signal processing. 2007, Chichester, England ; Hoboken, NJ: John Wiley & Sons. p. 10-13.
15. Tupayachi, P., et al. Design of an Electroencephalogram Module for Brain Computer Interface Oriented to People with Motor Disabilities. in Electrical and Electronics Engineering, 2006 3rd International Conference on. 2006.
16. 高材, 生物醫學工程導論. 初版 ed. 2008, 臺中市: 滄海. p. 112-166.
17. 郭高銘, 應用電激發光元件於穩態視覺誘發電位之腦波人機介面判斷, in 電機工程研究所碩士在職專班. 2011, 國立中央大學: 桃園縣.
18. 黃進強, 交流耦合平衡增益之腦波量測系統, in 電機工程研究所. 2007, 國立中央大學: 桃園縣.
19. 盧彥儒, 使用隱馬可夫模型於穩態視覺誘發之腦波人機介面判斷與其腦波控制遙控車應用, in 電機工程研究所. 2010, 國立中央大學: 桃園縣.
20. Sanei, S. and J. Chambers, EEG signal processing. 2007, Chichester, England ; Hoboken, NJ: John Wiley & Sons. p. 15-18.
21. 李柏磊, et al., 醫學影像與認知神經科學. 二版 ed. 2009, 桃園縣: 國立中央大學電機工程學系. p. 7-9.
22. Jurcak, V., D. Tsuzuki, and I. Dan, 10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems. Neuroimage, 2007. 34(4): p. 1600-1611.
23. 唐孝威, 腦功能成像. 第一版 ed. 1999, 合肥市: 中國科學技術大學出版社. p. 151-159.
24. Sanei, S. and J. Chambers, EEG signal processing. 2007, Chichester, England ; Hoboken, NJ: John Wiley & Sons. p. 127-131.
25. Luck, S.J., An introduction to the event-related potential technique. Cognitive neuroscience. 2005, Cambridge, Mass.: MIT Press. p. 17-26.
26. Luck, S.J., G.F. Woodman, and E.K. Vogel, Event-related potential studies of attention. Trends Cogn Sci, 2000. 4(11): p. 432-440.
27. Luck, S.J., An introduction to the event-related potential technique. Cognitive neuroscience. 2005, Cambridge, Mass.: MIT Press. p. 131-151.
28. Tseng, D.C., Virtual Reality. 8th ed. 2011, Chungli City: Institute of Computer Science and Information Engineering, National Central University. p. 3-46.
29. Burdea, G. and P. Coiffet, Virtual reality technology. 2nd ed. 2003, Hoboken, N.J.: J. Wiley-Interscience. p. 1-15.
30. Kalawsky, R.S., The science of virtual reality and virtual environments : a technical, scientific and engineering reference on virtual environments. 1993, Wokingham, England ; Reading, Mass.: Addison-Wesley. p. 1-15.
31. Vince, J., Virtual reality systems. SIGGRAPH series. 1995, Wokingham, England ; Reading, Mass.: Addison-Wesley Pub. Co. p. 1-16.
32. Comon, P., Handbook of blind source separation : independent component analysis and blind deconvolution. 1st ed. 2010, Boston, MA: Elsevier. p. 155-221.
33. Hyvarinen, A., J. Karhunen, and E. Oja, Independent component analysis. 2001, New York: J. Wiley. p. 140-202.
34. Lee, P.L., et al., ICA-based spatiotemporal approach for single-trial analysis of postmovement MEG beta synchronization. Neuroimage, 2003. 20(4): p. 2010-30.
35. 楊福生, 獨立分量分析的原理與應用. 第1版 ed. 2006, 北京市: 清華大學. p. 1-46.
36. 吳維軒, 獨立成份分析法於即時心電訊號萃取應用, in 電機工程研究所. 2008, 國立中央大學: 桃園縣.
37. Comon, P., Handbook of blind source separation : independent component analysis and blind deconvolution. 1st ed. 2010, Boston, MA: Elsevier. p. 1-19.
38. Hyvarinen, A., J. Karhunen, and E. Oja, Independent component analysis. 2001, New York: J. Wiley. p. 1-12.
39. 楊福生, 獨立分量分析的原理與應用. 第1版 ed. 2006, 北京市: 清華大學. p. 92-101.
40. Hyvarinen, A. and E. Oja, Independent component analysis: algorithms and applications. Neural Netw, 2000. 13(4-5): p. 411-30.
41. Makeig, S., et al., Blind separation of auditory event-related brain responses into independent components. Proc Natl Acad Sci U S A, 1997. 94(20): p. 10979-84.
42. Makeig, S., et al., Functionally independent components of the late positive event-related potential during visual spatial attention. Journal of Neuroscience, 1999. 19(7): p. 2665-2680.
43. Kekoni, J., et al., Rate effect and mismatch responses in the somatosensory system: ERP-recordings in humans. Biol Psychol, 1997. 46(2): p. 125-42.
44. Polich, J., Detection of change : event-related potential and fMRI findings. 2003, Boston: Kluwer Academic Publishers. p. 83-98.
45. Moore, N.C. and M.K. Arikan, Brainwaves and mind : recent advances : a report from Istanbul. 2004, Wheaton, Ill.: Kjellberg. p. 15-24.
46. Polich, J. and M.D. Comerchero, P3a from visual stimuli: typicality, task, and topography. Brain Topogr, 2003. 15(3): p. 141-52.
指導教授 陳純娟(Chun-Chuan Chen) 審核日期 2012-1-13
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