簡易檢索 / 詳目顯示

研究生: 林昆宏
Lin, Kun-Hung
論文名稱: 針對用於遠距醫療的量測裝置之心電圖特徵描繪演算法開發
Development of ECG delineation algorithm for measurement devices used in telemedicine
指導教授: 吳順德
Wu, Shuen-De
學位類別: 碩士
Master
系所名稱: 機電工程學系
Department of Mechatronic Engineering
論文出版年: 2016
畢業學年度: 104
語文別: 中文
論文頁數: 72
中文關鍵詞: 遠距醫療心電圖特徵描繪演算法
英文關鍵詞: Telemedicine, Electrocardiogram, Delineation algorithm
DOI URL: https://doi.org/10.6345/NTNU202203629
論文種類: 學術論文
相關次數: 點閱:143下載:5
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 隨著遠距醫療的發展,在過去的幾十年中,已有許多用於心電圖量測的可攜式裝置被研發出來。這些科技進步的成果使我們能夠在居家環境中進行心電圖量測,甚至讓操作變得更方便。然而,在這種模式下,我們無法保證訊號品質的良好。因為透過可攜式裝置量測而得的心電訊號,容易因為電極黏貼不穩造成嚴重的電極接觸雜訊干擾。此外,遠距醫療模式也使得資料可能蒐集自不同的國家,因而造成資料受到不同的電力線干擾。這些問題將導致許多心電圖特徵描繪演算法無法正常運作甚至失效。因此,本研究針對上述問題提出了一套新的特徵描繪演算法,其中包含:
    1. 提出短時Goertzel演算法來偵測電力線頻率,並以零相位延遲的Butterworth陷波濾波器來處理電力線干擾。
    2. 使用截止頻率為0.8Hz的零相位延遲Butterworth高通濾波器來處理心電訊號的基準線飄移。
    3. 提出一個基於粗粒化流程,並配合微分、平方與移動平均的方法來處理電極接觸雜訊。
    4. 改良Pan-Tompkins演算法並將其用於偵測心電訊號中的R波。
    5. 改良Elgendi演算法並將其用來偵測心電訊號中的P、T波。
    最後,本研究提出的這套特徵描繪演算法已被用於偵測CMATE®心電圖量測裝置所量測的資料中的心電訊號特徵。而實驗結果也證明了本研究提出的演算法的可行性與不錯的表現。

    With the growth of telemedicine, kinds of portable devices for ECG measurement have been developed over the past few decades. It makes in-home ECG measurements possible and convenient. However, a good signal quality could not be always guaranteed. ECG signals measured by a portable device may be contaminated by serious electrode contact noise (ECN) due to misconnection of electrode. Besides, for ECG signals collecting from different countries, signals could be contaminated by power line interferences with different frequencies. These drawbacks make lots of conventional delineation algorithms fail to work. In this study, we propose a new delineation algorithm to overcome this difficulty. This algorithm consists of the following parts:
    1. A short-time Goertzel algorithm was proposed to detect the frequency of the power line interference, and then a zero phase Butterworth notch filter is designed to attenuate the power line interference.
    2. The baseline wandering is filtered by using a zero phase Butterworth high pass filter with cutoff frequency at 0.8 Hz.
    3. A novel algorithm based on coarse grain, derivative, squaring and moving averaging is developed to handle the electrode contact noise.
    4. A modified Pan-Tompkins’ algorithm is used to detect R peaks of ECG signals
    5. Finally, P and T waves are detected by modified Elgendi’s algorithm.
    The proposed algorithm has been implemented to delineate ECG signals measured by CMATE® ECG devices successfully. Experimental results showed the feasibility and superiority of the proposed algorithm.

    摘要 i Abstract ii 誌謝 iii 目錄 iv 表目錄 vi 圖目錄 vii 第一章 緒論 1 1-1 前言 1 1-2 研究動機與目的 2 1-3 論文架構 4 1-4 文獻回顧 5 1-4-1 電力線干擾處理 5 1-4-2 電極接觸雜訊處理 6 1-4-3 QRS波群偵測 6 1-4-4 P、T波偵測 7 第二章 演算法設計-前處理 8 2-1 電力線干擾頻率偵測 8 2-1-1 Goertzel演算法 9 2-1-2 短時Goertzel演算法(Short-time Goertzel algorithm) 14 2-2 電極接觸雜訊處理 17 2-2-1 電極接觸雜訊的特徵 18 2-2-2 前處理 19 2-2-3 粗粒化(Coarse-graining approach) 20 2-2-4 切入點偵測(Cut-in point detection) 22 2-2-5 正常訊號片段選擇 25 2-3 濾波 26 第三章 演算法設計-特徵偵測 27 3-1 QRS波群偵測 27 3-1-1 R波偵測 28 3-1-2 誤判R波的處理 43 3-1-3 Q、S波偵測 45 3-2 P、T波偵測 46 3-2-1 Elgendi演算法 46 3-2-2 P、T波檢驗 53 第四章 效能分析與偵測結果討論 56 4-1 效能分析:短時Goertzel演算法 56 4-2 結果討論:QRS波群偵測 59 4-3 結果討論:P、T波偵測 63 第五章 結論 66 5-1 結論 66 5-2 本研究之具體貢獻 67 5-3 未來展望 67 5-3-1 短時Goertzel演算法 67 5-3-2 誤判R波的處理 68 5-3-3 P、T波檢驗 68 參考文獻 69

    [1] J. Malmivo and R. Plonsey, "Bioelectromagnetism," [Online], Available: http://www.bem.fi/book/.
    [2] "Physionet – Physiobank ATM," [Online], Available: http://www.physionet.org/cgi-bin/atm/ATM.
    [3] M. Blanco-Velasco, B. Weng, and K.E. Barner, "ECG signal denoising and baseline wander correction based on the empirical mode decomposition," Computers in Biology and Medicine, 2008.
    [4] A.K. Ziarani and A. Konrad, "A nonlinear adaptive method of elimination of power line interference in ECG signals," IEEE Transactions on Biomedical Engineering, vol. 49, no. 6, pp. 540-547, 2002.
    [5] D.A. Tong, K.A. Bartels, and K.S. Honeyager, "Adaptive reduction of motion artifact in the electrocardiogram," Engineering in Medicine and Biology, vol. 2, pp. 1403-2, 2002.
    [6] J.S. Paul, M.R. Reddy, and V.J. Kumar, "A transform domain SVD filter for suppression of muscle noise artefacts in exercise ECG's," IEEE Transaction on Biomedical Engineering, vol. 47, no. 5, pp. 654-663, 2002.
    [7] F.S. Tyner and J.R. Knott, "Fundamental of EEG Technology: Basic concepts and methods," Lippincott Williams & Wilkins, vol. 1, pp. 108, 1983.
    [8] P.S. Hamilton, "A comparison of Adaptive and Nonadaptive Filters for Reduction of Power Line Interference in the ECG," IEEE Transaction on Biomedical Engineering, vol. 43, pp. 105-109, 1996.
    [9] C. Levkov, G. Mihov, R. Ivanov, I. Daskalov, I. Christov, and I. Dotsinsky, "Removal of power-line interference from the ECG: a review of the subtraction procedure," BioMedical Eng. Online, 2005.
    [10] M. Fernández and R. Pallás-Areny, "Electrode contact noise in surface biopotential measurements," Engineering in Medicine and Biology Society, vol. 1, pp. 123-124, 1992.
    [11] E. Huigen, "Noise in biopotential recording using surface electrodes," Delft Technical University, MSc thesis, 2000.
    [12] J. Pan and W.J. Tompkins, "A real-time QRS detection algorithm," IEEE Transaction on Biomedical Engineering, vol. BME-32, no. 3, pp. 230-236, 1985.
    [13] H.A.N. Dinh, D.K. Kumar, N.D. Pah, and P. Burton, "Wavelets for QRS detection," Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE. Vol. 2. IEEE, 2001.
    [14] "Daubechies 3 wavelet," [Online]. Available: http://wavelets.pybytes.com/wavelet/db3/.
    [15] S.S. Mehta and N.S. Lingayat, "Detection of P and T-waves in Electrocardiogram," World Congress on Engineering and Computer Science, vol. 4, pp. 978-984, 2008.
    [16] C. Lin, C. Mailhes, and J.Y. Tourneret, "P- and T-Wave delineation in ECG signals using a Bayesian approach and a partially collapsed Gibbs sampler," IEEE transcation on Biomedical engineering, vol. 57, pp. 2840-2849, 2010.
    [17] D.G. Manolokis and V.K. Ingle, "Applied Digital Signal Processing," Cambridge University Press, ch. 8, pp.460, 2011.
    [18] "Discrete-time Signal Processing – Lecture 20: The Goertzel Algorithm and the Chirp Transform," [Online]. Available: http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-341-discrete-time-signal-processing-fall-2005/lecture-notes/lec20.pdf. Accessed: Mar. 18, 2016.
    [19] C. Zhao, U. Topcu, and S.H. Low, "Frequency-based load control in power systems," 2012 American Control Conference (ACC), IEEE, pp. 4423-4430, 2012.
    [20] "Electricity transmission operational data," 2015. [Online]. Available: http://www2.nationalgrid.com/uk/Industry-information/electricity-transmission-operational-data/. Accessed: May 1, 2016.
    [21] R.S. Khandpur, "Patient Monitoring Systems," Handbook of Biomedical Instrumentation, 2nd ed. Tata McGraw-Hill Education, 2003, ch. 6, pp. 190.
    [22] L.D. Liao, Y.H. Chen, C.P. Chao, C.T. Lin, A. Sun, S.C. Chen, and M.H. Chung, "Biosensor and electrode structure thereof," Patent US20110074396, 2011.
    [23] Y.M. Chi, T.P. Jung, and G. Cauwenberghs, "Dry-contact and noncontact biopotential electrodes: Methodological review," IEEE Reviews in Biomedical Engineering, vol. 3, pp. 106-119, 2010.
    [24] I. Amidror, "The theory of the Moiré phenomenon: Volume I: Periodic layers," Springer Science & Business Media, 2009
    [25] S.D. Wu, C.W. Wu, S.G. Lin, C.C. Wan, and K.Y. Lee, "Feature extraction for bearing fault diagnosis using composite multiscale entropy," Advanced Intelligent Mechatronics (AIM), 2013 IEEE/ASME International Conference on. IEEE, 2013.
    [26] V.X. Afonso, "ECG QRS Detection," Biomedical Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1993. [Online]. Available: http://www.ejwoo.com/uploads/2/5/4/0/25400517/ecg_qrs_detection.pdf
    [27] H. Sedghamiz, "Complete Pan Tompkins implementation ECG QRS detector," [Online]. Available: http://www.mathworks.com/matlabcentral/fileexchange/45840-complete-pan-tompkins-implementation-ecg-qrs-detector. Accessed: Feb. 4, 2015.
    [28] B. Surawicz, R. Childers, B. J. Deal, and L. S. Gettes, "AHA/ACCF/HRS recommendations for the Standardization and interpretation of the electrocardiogram," Circulation, vol. 119, no. 10, pp. 235–240, 2009.
    [29] R.G. Hiss, Capt. USAF, and L.E. Lamb, "Electrocardiographic Findings in 122,043 Individuals," Circulation, vol. 25, no. 6, pp. 947-961, 1962.
    [30] J.A. Hartigan and M.A. Wong, "A K-Means Clustering Algorithm," Journal of the Royal Statistical Society, Applied Statistics, vol. 28, no. 1, pp. 100-108, 1979.
    [31] D.J.C. MacKay, "Information Theory, Inference and Learning Algorithms," Cambridge University Press, pp. 284-292, 2003. ISBN 0-521-64298-1.
    [32] M. Elgendi, "P and T waves annotations and detection in MIT-BIH arrhythmia database," rxiv.org, 2014. [Online]. Available: http://www.rxiv.org/pdf/1301.0056v1.pdf.

    下載圖示
    QR CODE