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研究生: 聶族剛
Tsu-Gang Nie
論文名稱: 肺音聽診系統之可行性研究
A Feasibility Study of Lung Sound Auscultation Systems
指導教授: 蔡章仁
Jang-Zern Tsai
口試委員:
學位類別: 碩士
Master
系所名稱: 資訊電機學院 - 電機工程學系
Department of Electrical Engineering
畢業學年度: 93
語文別: 中文
論文頁數: 83
中文關鍵詞: 肺音類神經網路呼吸相位
外文關鍵詞: artificial neural network, respiratory phase, lung sound
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  • 本研究建構一個電腦化的肺音聽診系統。由於傳統的聽診法由醫師聽診完畢後,無法記錄肺音以及呼吸狀態等參數,因而無法重覆利用這些資訊。為改善傳統聽診法的缺點,因此建立一套透過電腦化的分析方式分析聽診的肺音。此系統除了保留傳統聽診方式的優點,並可記錄聽診位置、病歷資料並可將肺音保存,進而偵測異常呼吸音並以演算法將其異常呼吸音量化,提供醫師更多樣的診斷數據。此系統是以LabVIEW 程式與Matlab 程式撰寫,並以麥克風電路以及呼吸相位電路分別記錄肺音與呼吸狀態,透過個人電腦的音效卡擷取並存檔,供後續的分析與處理。也可透過此方式進行肺音收集等工,建立肺音資料庫。此外,本系統的硬體為架構於個人電腦之上,透過音效卡取代資料擷取裝置,因此本系統易於廣泛運用。


    The aim of this thesis is to propose a computerized lung sound auscultation system. The lung sound auscultation system in order to improve the drawback of the traditional auscultation, used computer to analysis lung sound signal. This system can record the auscultative position and lung sound. Abnormal lung sound can be quantified by using algorithm, propose more diagnosis data to a doctor.
    It includes many sensors in this system, such as microphone and thermistor. The system is programmed by adopting matlab and LabVIEW. Use PC sound card is it acquisition and save file, support analysis of follow-up. The hardware of this system is structured on the PC, replaced
    by sound card of data acquisition device, so this system is easy to use extensively.

    目 錄 中文摘要 英文摘要 誌 謝 目 錄 Ⅰ 圖 目 錄 Ⅳ 表 目 錄 Ⅷ 第一章 緒論 1 1-1 研究動機與方法 1 1-2 肺音產生的機制 2 1-3 文獻回顧 3 1-4 論文架構 4 第二章 異常呼吸音的模型 5 2-1 肺音的分類 5 2-2 異常呼吸音與疾病之關聯 6 2-3 異常呼吸音的特性 7 2-3.1 喘鳴音 7 2-3.2 乾囉音 9 2-3.3 爆裂音 10 2-4 異常呼吸音的合成 13 2-4.1 喘鳴音的合成 13 2-4.2 乾囉音的合成 16 2-4.3 爆裂音的合成 19 第三章 系統硬體架構 24 3-1 麥克風電路 24 3-2 呼吸相位偵測電路 29 3-3 音效卡頻率響應量測 32 第四章 系統軟體架構 46 4-1 傅立葉轉換 46 4-2 短時傅立葉轉換 47 4-3 小波轉換 48 4-4 呼吸相位偵測 49 4-5 特徵值抽取 56 4-6 倒傳遞類神經網路 58 4-7 爆裂音偵測 60 4-8 喘鳴音與乾囉音偵測 62 4-9 使用者介面 64 第五章 結論與討論 67 5-1 實驗結果 67 5-1.1 異常呼吸音辨識結果 67 5-1.2 爆裂音偵測結果 69 5-1.3 喘鳴音與乾囉音真測結果 74 5-2 結論 79 5-3 未來展望 80 參考文獻 81

    [1] 許世昌, “新編解剖生理學,” 永大書局, 2000.
    [2] 廖偉舜, “使用轉換域可適性環境雜訊濾除器之肺音量測系統” 國
    立台灣大學電機工程學研究所碩士論文, 中華民國九十年六月.
    [3] M.Du, F.H.Y. Chan, F.K. Lam, J. Sun, “Crackle detection and
    classification based on matched wavelet analysis,” Proceedings of the
    Annual International Conference of the IEEE EMBS, 1638-1641,
    1997.
    [4] Leontios J. Hadjileontiadis, Stavros M. Panas, “Separation of
    Discontinuous Adventitious Sounds from Vesicular Sounds Using a
    Wavelet-Based Filter,” IEEE Transactions on biomedical engineering,
    vol. 44, 1269-1281, 1997.
    [5] Leontios J. Hadjileontiadis, Ioannis T. Rekanos, “Enhancement of
    explosive bowel sounds using Kurtosis-based filtering,” Proceedings
    of the Annual International Conference of the IEEE EMBS, vol. 3,
    2479-2482, 2003.
    [6] Leontios J. Hadjileontiadis, Ioannis T. Rekanos, “Detection of
    Explosive Lung and Bowel Sounds by Means of Fractal Dimension,”
    IEEE Signal processing letters, vol. 10, 311-314, 2003.
    [7] Paris A. Mastorocostas, Yannis A. Tolias, John B. Theocharis,
    Leontios J. Hadjileontiadis, Stavros M. Panas, “An Orthogonal Lest
    Squares-Based Fuzzy Filter for Real-Time Analysis of Lung Sounds,”
    IEEE Transactions on biomedical engineering, vol. 47, 1165-1176,
    2000.
    [8] R.J. Riella, P. Nohama, R.F. Borges, A.L. Stelle, “Automatic
    Wheezing Recognition in Recorded Lung Sounds,” Proceedings of
    the Annual International Conference of the IEEE EMBS, 2535-2538,
    2003.
    [9] S.A. Taplidou, L.J. Hadjileontiadis, T. Penzel, V. Gross, S.M. Panas,
    “WED:An Efficient Wheezing-Episode Detector Based on Breath
    Sounds Spectrogram Analysis,” Proceedings of the Annual
    International Conference of the IEEE EMBS, 17-21, 2003.
    [10] Styliani A. Taplidou, Leontios J. Hadjileontiadis, Ilias K. Kitsas,
    Konstantinos I. Panoulas, Thomas Penzel, Volker Gross, Stavros M.
    Panas, “On Applying Continuous Wavelet Transform in Wheeze
    Analysis,” Proceedings of the Annual International Conference of
    the IEEE EMBS, 3832-3835, 2004.
    [11] V. Gross, Th. Penzel, L. Hadjileontiadis, U. Koehler, C. Vogelmeier,
    “Electronic auscultation based on wavelet transformation in clinical
    use,” Proceedings of the Annual International Conference of the
    IEEE EMBS, 1531-1532, 2002.
    [12] 顧潔修, “理學檢查與健康評估,” 藝軒出版社, 2003.
    [13] G. Charbonneau, E. Ademovic, B.M.G. Cheetham, L.P. Malnberg, J.
    Vanderschoot, A.R.A. Sovijarvi, “Basic techniques for respiratory
    sound analysis,” Eur. Respir. Rev., 10:77, 625-635, 2000.
    [14] A.R.A. Sovijarvi, L.P. Malmberg, G. Charbonneau, J. Vanderschoot,
    F. Dalmasso, C. Sacco, M. Rossi, J.E. Earis, “Characteristics of
    breath sounds and adventitious respiratory sounds,” Eur. Respir. Rev.,
    10:77, 591-596, 2000.
    [15] Hasse Melbye, “Auscultation of the lungs, still a useful
    examination?,” Tidsskr Nor Laegeforen, 121, 451-4, 2001.
    [16] Hans Pasterkamp, Steve S. Kraman, George R. Wodicka,
    “Respiratory Sounds Advances Beyond the Stethoscope,” Am. J.
    Respir. Crit. Care Med., vol. 156, 974-987, 1997.
    [17] A. Kandaswamy, C. Sathish Kumar, Rm. Pl. Ramanathan, S.
    Jayaraman, N. Malmurugan, “Neural classification of lung sounds
    using wavelet coefficients,” Computers in Biology and Medicine 34,
    523-537, 2004.
    [18] J.E. Earis, B.M.G. Cheetham, “Future perspectives for respiratory
    sound research,” Eur. Respir. Rev., 10:77, 641-646, 2000.
    [19] A. Cohen, “Signal processing methods for upper airway and
    pulmonary dysfunction diagnosis,” IEEE Eng. Med. Biol. Mag., pp.
    72-75, 1990.
    [20] 葉怡成, “類神經網路模式應用與實作,” 台北:儒林, 2003.

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