進階搜尋


   電子論文尚未授權公開,紙本請查館藏目錄
(※如查詢不到或館藏狀況顯示「閉架不公開」,表示該本論文不在書庫,無法取用。)
系統識別號 U0026-2108201310464800
論文名稱(中文) 應用於不同年資靜坐者的情緒穩定度之腦波分類器研究
論文名稱(英文) Study on EEG Classifier in Meditators of Differing Experience Levels as a Predictor of Emotional Stability
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 101
學期 2
出版年 102
研究生(中文) 林郁惠
研究生(英文) Yu-Huei Lin
學號 n26000274
學位類別 碩士
語文別 中文
論文頁數 51頁
口試委員 指導教授-林志隆
口試委員-戴政祺
口試委員-余松年
口試委員-林宗志
中文關鍵字 腦波  靜坐  情緒刺激  分類器 
英文關鍵字 EEG  meditation  emotional stimulus  classification 
學科別分類
中文摘要 本研究的目的在於分析不同靜坐經驗者的靜坐表現差異以及情緒受外在刺激時的影響程度,同時使用自動分類器探討靜坐表現與年資之關聯。實驗中將受測者依照經驗分為多靜坐經驗者、少靜坐經驗者以及無靜坐經驗者,量測靜坐與受情緒刺激時之腦波圖以做為輸入參數。
實驗結果顯示靜坐時Alpha波、Theta波能量上升,而有靜坐經驗組變化比無靜坐經驗組明顯,說明靜坐表現與靜坐經驗呈正相關;在情緒刺激實驗中,有經驗者表現亦較平穩、不受外在影響,由實驗結果可知有靜坐經驗者較無經驗者能保持身心穩定。
研究中提出自動分類器,欲讓靜坐練習者了解自己靜坐的程度及是否於情緒穩定狀態,結果顯示分類器判別所有受測者是否達靜坐狀態之正確分類率約為64%,特別在有經驗者之分類率為68%,較無經驗者高之分類率58%高;情緒刺激實驗中,分類器判別是否於受刺激之情緒不穩定狀態的正確分類率約為60%,而受刺激時各經驗族群間正確分類率約為65%。
英文摘要 The aim of this work is to investigate the performance of meditation practice and the response of emotional stimulation for meditators of varying levels of experience. This work also applies classification algorithms to implement the estimation of meditation experience levels. For this purpose, EEG data are collected during both meditation and emotional stimulation from meditators grouped into three categories (experienced, intermediate, and those having no previous meditation experience).
The results show that the power of EEG Alpha and Theta waves increases during meditation, and the improvement in the power of EEG positive during the meditation process correlates to the experience of meditators. In addition, the changes in physiological response of meditators during emotional stimulation are less than those of the participants having no previous experience with meditation. It demonstrates that experienced meditation can improve emotional stability as well as steady brain activity.
The proposed classification indicates that the correct rate in evaluating experience level is 64% in classification between baseline and meditation for all subjects, where experienced and intermediate meditators exhibit 68%, as opposed to participants with no previous meditation experience who weigh in at 58%. For the estimation of meditation experience under emotional stimulation, the correct rate is 60% during emotional states, and 65% between groups of different experience levels.
論文目次 摘 要 I
Abstract II
致謝 IV
目錄 V
圖目錄 VII
表目錄 IX
第一章 緒論 1
1-1 研究動機與目的 1
1-2 文獻探討 2
1-2-1 靜坐與腦波文獻探討 2
1-2-2 IAPS文獻探討 3
1-2-3 腦波與情緒刺激 4
1-3 論文架構 5
第二章 生理訊號量測原理與分析方法 6
2-1 腦波圖(EEG)量測原理 6
2-2 腦波圖(EEG)訊號分析方法 8
2-2-1 腦波圖頻帶分析方法 8
2-1-2 腦波圖訊號轉換處理 8
第三章 實驗設計 9
3-1 實驗系統架構 9
3-1-1 靜坐實驗 9
3-1-2 情緒刺激實驗 9
3-2 受測者與實驗場所 10
3-3 實驗研究工具 11
3-3-1 IAPS 11
3-3-2 播放軟體E-PRIME 12
3-3-3 靜坐數息法 12
3-4 實驗流程 13
第四章 系統設計 15
4-1 系統架構 15
4-2 生理訊號擷取系統 15
4-3 軟體系統設計 16
4-3-1 系統取樣頻率 16
4-3-2 訊號轉換處理 17
4-3-3 分類器介紹 17
4-3-4 分類器架構 20
第五章 實驗結果與分析 22
5-1 靜坐實驗結果與分析 22
5-1-1 靜坐實驗統計分析 22
5-1-2 靜坐實驗狀態間分類器分析 27
5-1-3 靜坐實驗群組間分類器分析 29
5-2 情緒刺激實驗結果與分析 32
5-2-1 情緒刺激實驗統計分析 32
5-2-2 情緒刺激實驗狀態間分類器分析 37
5-2-3情緒刺激實驗群駔間分類器分析 39
5-3 靜坐實驗與情緒刺激實驗之決策樹分析 42
第六章 實驗結果討論與未來展望 44
6-1 實驗結果討論 44
6-2 結論與未來展望 48
參考文獻 49
參考文獻 [1] 張素珠,“不同身體活動量與靜坐者睡眠品質之比較研究”,國立臺灣師範大學體育學系碩士論文,民國九十一年。
[2] F. Travis, J. Hagelin, M. Tanner, S. Nidich, C. Gaylord-King, S. Grosswald, and M. Rainforth, “Effects of transcendental meditation practice on brain functioning and stress reactivity in college students,” International Journal of Psychophysiology, vol. 71, no. 2, pp. 170-176, Feb. 2009.
[3] R. M. Kaushika, R. Kaushika, S. K. Mahajan, and V. Rajesh, “Effects of mental relaxation and slow breathing in essential hypertension,” Complementary Therapies in Medicine, vol. 14, no. 2, pp. 120-126, Jun. 2006.
[4] S. J. Kilner, P. D. Zelazo, and N. M. Catherine, “Mindfulness meditation and reduced emotional interference on a cognitive task,” Motivation and Emotion, vol. 31, no. 4, pp. 271-283, Nov. 2007.
[5] R. K. Wallace, “Physiological effects of transcendental meditation,” Science, vol. 167, no. 3926, pp. 1751-1754, Mar. 1976.
[6] R. Wallace and F. Travis, “Autonomic and EEG patterns during eyes-closed rest and transcendental meditation (TM) practice: The basis for a neural model of TM practice,” Consciousness and Cognition , vol. 8, no. 3, pp. 302-318, Oct. 1999.
[7] T. Takahashi, T. Murata, T. Hamada, M. Omori, H. Kosaka, M. Kikuchi, H. Yoshida, and Y. Wada, “Changes in EEG and autonomic nervous activity during meditation and their association with personality traits,” International Journal of Psychophysiology, vol. 55, no. 2, pp. 199-207, Feb. 2005.
[8] P. J. Lang, M. M. Bradley, and B. N. Cuthber, “International affective picture system (IAPS): Technical manual and affective ratings,” Center for Research in Psychophysiology, University of Florida, 2005.
[9] D. Sabatinelli, M. M. Bradley, J. R. Fitzsimmons, and P. J. Lang, “Parallel amygdala and inferotemporal activation reflect emotional intensity and fear relevance,” Neuroimage, vol. 24, no. 4, pp. 1265-1270, Feb. 2005.
[10] Z. Shiliang, “Affective MTV analysis based on arousal and valence features,” Institute of Computing Technology , 2008.
[11] T. Costa, E. Rognoni, and D. Galati, “EEG phase synchronization during emotional response to positive and negative film stimuli,” Neuroscience Letters, vol. 406, no. 3, pp. 159-164, Aug. 2006.
[12] L. Aftanas and S. Golosheykin, “Impact of regular meditation practice on EEG activity at rest and during evoked negative emotions,” International Journal of Neuroscience, vol. 115, no. 6, pp. 893-909, Jun. 2005.
[13] A. Sobolewski, E. Holt, E. Kublik, and A. Wrobel, “Impact of meditation on emotional processing—a visual ERP study,” Neuroscience Research, vol. 71, no. 1, pp. 44-48, Sep. 2011.
[14] A. Lutz, J. Brefczynski-Lewis, T. Johnstone, and R. J. Davidson, “Regulation of the neural circuitry of emotion by compassion meditation: effects of meditative expertise,” PLoS ONE, vol. 3, no. 3, e1897, Mar. 2008.
[15] V. A. Taylor, J. Grant, and V. Daneault, “Impact of mindfulness on the neural responses to emotional pictures in experienced and beginner meditators,” NeuroImage, vol. 57, no. 4, pp. 1524-1533, Aug. 2011.
[16] R. Cooper and J. W. Osselton, “EEG technology,” 3rd Edition, pp. 1-2, 1980.
[17] J. Malmivuo and R. Plonsey, “Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields,” Chapter 13, 1969.
[18] 林三永,“何謂腦波? ”,科學人雜誌,民國一百年。
[19] 吳京一,“淺說「腦波」¬―腦波的常識”,科學月刊,0032期,民國六十一年。
[20] L. Chen a, X. Mao, Y. Xue, and L. L. Cheng , “Speech emotion recognition: Features and classification models,” Digital Signal Processing, vol. 22, pp. 1154-1160, May. 2012.
[21] M. Murugappan, N. Ramachandran, and Y. Sazali, “Classification of human emotion from EEG using discrete wavelet transform,” J. Biomedical Science and Engineering, vol. 3, No. 4, pp. 390-396, Feb. 2010.
[22] 張斐章、張麗秋,“類神經網路”, 東華書局,民國九十四年。
[23] M. Murugappan, “Electromyogram Signal Based Human Emotion Classification using KNN and LDA,” IEEE International Conference on System Engineering and Technology, pp. 106-110 , 2011.
論文全文使用權限
  • 同意授權校內瀏覽/列印電子全文服務,於2015-08-27起公開。


  • 如您有疑問,請聯絡圖書館
    聯絡電話:(06)2757575#65773
    聯絡E-mail:etds@email.ncku.edu.tw