姓名 |
陳佑榮(You-Rong Chen)
查詢紙本館藏 |
畢業系所 |
機械工程學系 |
論文名稱 |
應用希爾伯特黃轉換以C語言環境開發腦機介面訊號處理
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相關論文 | |
檔案 |
[Endnote RIS 格式]
[Bibtex 格式]
[相關文章] [文章引用] [完整記錄] [館藏目錄] 至系統瀏覽論文 ( 永不開放)
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摘要(中) |
本研究為開發即時運算以及可攜帶式的腦機介面裝置,以希爾伯特-黃轉換(Hilbert-Huang transform, HHT)為腦波分析的演算法,並且改善其運算速度的問題,將HHT演算法中的經驗模態分解法(empirical mode decomposition, EMD) 中Cubic Spline 改良成演算法計算較快的Hermite Spline,其中兩種不同形式的包絡線分別為二次及一次微分連續曲線。
並以556筆病人腦波資料進行分析,分為清醒及麻醉資料,並以希爾伯特黃平均區域性頻率(Hilbert-Huang average regional frequency, HHARF)作為判斷兩種曲線演算法相關係數之依據,其中以EMD分解出的本質模態函數(intrinsic mode functions, IMF),IMF1至IMF6皆能以HHARF判斷麻醉及清醒,其中以IMF1更為明顯。我們再以兩種曲線演算法所計算的IMF1之HHARF,兩者之間的相關係數清醒為0.97,麻醉為0.92。 |
摘要(英) |
In this papper, we developed a portable and real time brain-computer interface device using Hilbert-Huang Transform (HHT) to analyze brain waves. In order to improve the speed of the calculation, the cubic spline of the empirical mode deposition (EMD) method in the algorithms of HHT is changed into Hermite spline. The two different forms of the envelope are quadratic differential continuous curve and a differential continuous curve, respectively.
With 556 strokes of EEG data of patient were analyzed, divided awake and anesthesia information. The correlation coefficients of two kinds of algorithms are judged by using Hilbert-Huang average regional frequency (HHARF). For the intrinsic mode functions (IMF) decomposed by EMD, we can use HHARF to judge awake and anesthesia from IMF1 to IMF6. Furthermore, the result is more apparent in IMF1. Using two curves algorithm to calculate HHARF of IMF1, the correlation coefficient of awake is 0.97, and the correlation coefficient in anesthesia is 0.92. |
關鍵字(中) |
★ 腦機介面 ★ 希爾伯特黃轉換 |
關鍵字(英) |
★ BCI ★ HHT |
論文目次 |
目錄
摘要 ................................................................................................................. I
Abstract ........................................................................................................ II
致謝 ............................................................................................................. III
目錄 ............................................................................................................... V
符號說明 ................................................................................................... VIII
圖目錄 ........................................................................................................... X
表目錄 ........................................................................................................ XII
第一章 緒論 .................................................................................................. 1
1-1前言 ................................ ................................ ................................ .. 1
1-2研究動機與目的 研究動機與目的 研究動機與目的 ................................ ................................ .............. 1
1-3論文架構 論文架構 ................................ ................................ .......................... 2
第二章 腦波與腦機介面 .............................................................................. 3
2-1腦波 ................................ ................................ ................................ .. 3
2-1-1腦波產生 ............................................................................................................. 3
2-1-2腦波種類 ............................................................................................................. 5
2-1-3腦波量測 ............................................................................................................. 6
2-1-4腦波干擾 ............................................................................................................. 7
2-2腦機介面 腦機介面 ................................ ................................ .......................... 7
2-2-1 線性方法 ............................................................................................................ 8
2-2-2非線性方法 ....................................................................................................... 10
VI
第三章 希爾伯特-黃轉換........................................................................... 13
3-1希爾伯特轉換 希爾伯特轉換 (Hilbert Transform, HT) (Hilbert Transform, HT)(Hilbert Transform, HT)(Hilbert Transform, HT)(Hilbert Transform, HT) (Hilbert Transform, HT)(Hilbert Transform, HT)(Hilbert Transform, HT)(Hilbert Transform, HT) (Hilbert Transform, HT)(Hilbert Transform, HT)(Hilbert Transform, HT)(Hilbert Transform, HT)(Hilbert Transform, HT) (Hilbert Transform, HT) (Hilbert Transform, HT)(Hilbert Transform, HT)(Hilbert Transform, HT) ................................ ........ 13
3-2本質模態函數 本質模態函數 (Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF) (Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF) (Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF) (Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF) (Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF)(Intrinsic Mode Functions, IMF) (Intrinsic Mode Functions, IMF) (Intrinsic Mode Functions, IMF) ........................... 15
3-3經驗模態分解法 經驗模態分解法 經驗模態分解法 (Empirical Mode Decomposition, EMD) (Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD) (Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD) (Empirical Mode Decomposition, EMD) (Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD) (Empirical Mode Decomposition, EMD) (Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD) (Empirical Mode Decomposition, EMD)(Empirical Mode Decomposition, EMD) (Empirical Mode Decomposition, EMD) .......... 15
3-4瞬時頻率 瞬時頻率 (Instantaneous Frequency, IF) (Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF) (Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF) (Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF)(Instantaneous Frequency, IF) (Instantaneous Frequency, IF) (Instantaneous Frequency, IF) (Instantaneous Frequency, IF)................................ ........ 19
第四章 三次曲線插值法 ............................................................................ 23
4-1 Cubic Spline1 Cubic Spline 1 Cubic Spline1 Cubic Spline1 Cubic Spline1 Cubic Spline 1 Cubic Spline1 Cubic Spline1 Cubic Spline1 Cubic Spline ................................ ................................ ................... 24
4-1-1 Natural Cubic Spline.......................................................................................... 28
4-1-2 Clamped Cubic Spline ....................................................................................... 28
4-1-3 Not a Knot Cubic Spline .................................................................................... 30
4-2 Hermite Spline2 Hermite Spline 2 Hermite Spline 2 Hermite Spline2 Hermite Spline2 Hermite Spline 2 Hermite Spline2 Hermite Spline2 Hermite Spline2 Hermite Spline2 Hermite Spline ................................ ................................ ............... 31
4-2-1 Hermite Spline .......................................................................................... 32
4-2-2 Hermite Spline ( )........................................................................................... 35
4-3 包絡線連續性及效能討論 包絡線連續性及效能討論 包絡線連續性及效能討論 包絡線連續性及效能討論 ................................ .......................... 38
第五章 實驗分析方法 ................................................................................ 40
5-1腦波數據與分析軟體 腦波數據與分析軟體 腦波數據與分析軟體 腦波數據與分析軟體 ................................ ................................ .... 40
5-2分析方法 I-HHWRFHHWRFHHWRFHHWRF ................................ ................................ ..... 41
5-3分析方法 II -HHARFHHARFHHARFHHARF ................................ ................................ ..... 41
5-4實驗分析 實驗分析 ................................ ................................ ........................ 42
5-5實驗結果討論 實驗結果討論 ................................ ................................ ................ 47
VII
5-5-1負頻率的產生 ................................................................................................... 47
5-5-2分析方法I-HHWRF之結果 ............................................................................ 51
5-5-3分析方法II-HHARF之結果 ............................................................................ 53
5-5-4包絡線與取樣視窗時間之討論 ....................................................................... 55
第六章 結論與未來展望應用 .................................................................... 61
參考文獻 ...................................................................................................... 63 |
參考文獻 |
參考文獻
[1]M. Teplan, “Fundamentals of EEG measurement,” Measurement Science
Review, Vol.2, No.2, 2002.
[2]小小整理網站SMALLCOLLATION。2016年7月1日,取自https://smallcollation.blogspot.tw。
[3]N. Schaul, “The fundamental neural mechanism of electroencephalography,” Electroencephalography and Clinical Neurophysiology, Vol. 106, pp. 101-107, 1998.
[4]G.C. Sih, K.K. Tang, “Dwelling time of normal and abnormal brain waves connected with their transformability and sustainability,” Theoretical and Applied Fracture Mechanics, Vol. 65, pp.34-46, Elsevier Science, 2013.
[5]關尚勇,林吉和,破解腦電波,藝軒圖書出版社,民國九十一年。
[6]S. Ganesh, “Human thought controlled electrical switching using fast Fourier transform,” International Journal of Advanced Research in Computer and Communication Engineering, Vol. 3, Issue 12, pp.8762-8765, 2014.
[7]M. Shaker, “EEG waves classifier using Wavelet transform and Fourier transform,” International Journal of Medical, Health, Pharmaceutical and Biomedical Engineering, Vol. 1, No.3, pp.169-174, 2007.
[8]K.S. Ahmed, “Wheelchair movement control VIA human eye blinks,” American Journal of Biomedical Engineering, Vol.1, No.1, pp. 58-58, 2011.
[9]Li. Zhao, “Research on SSVEP feature extraction based on HHT,” Fuzzy Systems and Knowledge Discovery, Vol. 5, pp.2220-2223, 2010.
[10]F.L. Yuan, Z.Z. Luo, “The EEG de-noising research based on Wavelet and Hilbert transform method,” International Conference on Computer Science and Electronics Engineering, Vol. 3, pp.361-365, 2012.
[11]N.E. Huang, et al. “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proceedings of Royal Society London, A, No. 454, pp.903-995, 1998.
[12]A.V. Oppenheim, R.W. Schafer, Discrete-Time Signal Processing, Prentice-Hall, pp.775-801, 1989.
[13]馬語者: 三次樣條插植(Cubic Spline Interpolation)及代碼實驗 (C語言)。2016年6月26日,取自http://www.cnblogs.com/xpvincent/archive/2013/01/26/2878092.html。
[14]E. Catmull, R. Rom, “A class of local interpolating splines,” In Computer Aided Geometric Design, pp. 317–326, 1974.
[15]洪子倫:Chapter 4 Cubic Spline。2016年6月26日,取自http://math.fcu.edu.tw/~tlhorng/old/Pdf/Chap04.PDF。
[16]R. Shalbaf, H. Behnam, JW. Sleigh, LJ. Voss, “Using the Hilbert–Huang transform to measure the electroencephalographic effect of propofol,” Physiological Measurement, Vol. 33, pp.271-285, 2012. |
指導教授 |
陳世叡
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審核日期 |
2016-8-29 |
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