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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 生醫電子與資訊學研究所
Please use this identifier to cite or link to this item: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22392
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???org.dspace.app.webui.jsptag.ItemTag.dcfield???ValueLanguage
dc.contributor.advisor張璞曾
dc.contributor.authorYu-Cheng Wuen
dc.contributor.author吳育誠zh_TW
dc.date.accessioned2021-06-08T04:16:49Z-
dc.date.copyright2010-08-05
dc.date.issued2010
dc.date.submitted2010-07-30
dc.identifier.citation[1] J.F. Murray, J.A. Nadel , Textbook of Respiratory Medicine, Philadelphia: Saunders, 1994
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[5] V. K. Iyer, P. A. Ramamoorthy, H. Fan, and Y. Ploysongsang, “Reduction of heart sounds from lung sounds by adaptive filtering” , IEEE Trans. Biomed. Eng., vol. BME-33, no. 12, pp. 1141-1148, 1986.
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[8] L. J. Hadjileonyiadis and S. M. Panas, “Adaptive reduction of heart sounds from lung sounds using fourth-order statistics,” IEEE Transactions on Biomedical Engineering, vol..44 , Issue.7, pp. 642-648, July 1997.
[9] K. E. Forkheim, D. Scuse, H . Pasterkamp, “A comparison of neural network models for wheeze detection”, IEEE Communications, Power, and Computing Conference Proceedings, vol. 1, pp.214 - 219, 1995.
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[12] A.R.A. Sovijärvi, J. Vanderschoot, L. P. Malmerg, G. Righini, and S. A. T. Stoneman “Definition of terms for applications of respiratory sounds,” European Respiratory Review, vol. 10 no. 77, pp. 597 – 610, 2000.
[13] A. Oppenheim, A. S. Willsky, and S. H. Nawab, Signals and Systems, Upper Sadde River, NJ:, Prentice-Hall, 1996.
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[15] A. Styliani, T. Leontios, and J. Hadjileontiadis, “Wheeze detection based on time-frequency analysis of breath sounds,” Computer in Biology and Medicine, vol. 37, pp. 1073 – 1083, 2007.
[16] A. R. A. Sovijarvi, J. Vanderschoot, and J. R. Eavis, “Standard of computerized respiratory sound analysis”, European Respiratory Review, vol. 10, no. 77, pp. 585 - 649, 2000.
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[18] M. L. Chugani, A. R. Samant and M. Cerna, LabVIEW Signal Processing, NJ: Prentice Hall, 1998.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22392-
dc.description.abstract本研究旨在架構一可靠的音效卡擷取訊號之肺音錄製系統,其中的關鍵在於針對肺音發生的頻段進行嚴謹的可靠度分析,可靠度分析可略分為頻譜分析與相關係數演算法兩個過程,其步驟為:(1) 傅立葉轉換;(2) 頻譜平均;(3) 頻譜正規化;(4) 對齊峰值;(5) 相關係數;以及(6) 雙側相關係數演算法。本研究提出雙側相關係數演算法作為音效卡與類比對數位轉換器的相關程度比較,藉此驗證以音效卡作為肺音擷取裝置的可行性。肺音錄製系統分為硬體與軟體部份,硬體部份以指向性電容式麥克風(Beta 54, Shure, USA)接收肺音訊號,經由前置放大器傳輸到電腦。在軟體部份,以LabVIEW撰寫訊號儲存與訊號分析的功能。實驗結果可以發現,每個頻率訊號的頻譜之雙側相關係數均在 0.95 以上,顯示音效卡與多數研究群所使用的類比對數位轉換器所擷取的訊號有高度的相關性,因此以音效卡作為肺音訊號的擷取裝置是可行的。zh_TW
dc.description.abstractThis study is to setup a reliable recorder for lung sound. The acquisition device that most research groups employ is the analog-to-digital converters. However, sound card present in the personal computer or notebook is used in this study.. Therefore, the reliability analysis of sound card has to be examined seriously. The analysis includes two processes. One is spectrum analysis, the other is correlation. The steps are as follows: (1) Fourier transform; (2) average spectrum; (3) normalization; (4) peak regulation; (5) correlation coefficient; and (6) bilateral analysis. Bilateral analysis for correlation coefficient of spectrums from the measurements of lung sound by analog-to-digital converters and by sound card were also conducted.. The system hardware is constructed by series connection of a high directionality microphone (Beta 54, Shure, USA), a preamplifier (MIC200, Behringer, Germany), and a sound card of a personal computer (ASUS, Taiwan). The platform software for data storage and analysis is coded in LabVIEW (National Instrumentation, USA). The findings indicate that the bilateral correlation coefficients for the test frequencies of the two devices are all over 0.95. In conclusion, the sound card is feasible to be an acquisition device for lung sound.en
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Previous issue date: 2010
en
dc.description.tableofcontents口試委員會審定書……………………………………………… i
誌謝……………………………………………………………… ii
中文摘要…………………………………..…………………….. iv
英文摘要………………………………………………….……… v
第一章 緒論……………………………….……........................ 1
1.1 肺音的基本特性………………………......................... 1
1.1.1 肺音的形成……………….……………………... 1
1.1.2 肺音的頻率概述………………………………… 2
1.2 肺音常見的診斷方法………………………………….. 2
1.3 文獻回顧……………………………………………….. 3
1.4 研究動機與方法……………………………………….. 4
1.5 論文架構……………………………………….………. 5
第二章 肺音相關理論…………………………………….......... 7
2.1 肺的組織結構及其功能………………………….......... 7
2.1.1 呼吸作用………………………………................ 8
2.2 肺音分類……………………………………………….. 9
2.2.1 哮鳴音…………………………………………… 11
2.2.2 乾囉音…………………………………………… 12
2.2.3 爆裂音…………………………………………… 12
2.3 量測方式與量測位置……………………...…………... 12
第三章 肺音錄製系統架構……………………………….......... 14
3.1 硬體架構……………………………….......................... 14
3.1.1 感測器-電容式麥克風…………………………... 14
3.1.2 前級放大器………………………………............ 17
3.2 弦波輸入之可靠度分析系統硬體架………………….. 18
3.2.1 數位電路………………………………................ 19
3.3 肺音錄製之可靠度分析系統硬體架構……………….. 21
3.3.1 混音器(Mixer)……………………………….. 22
3.4 軟體架構……………………………….......................... 25
3.4.1 軟體系統概述………………………………........ 25
3.4.2 軟體系統架構………………………………......... 26
3.5 肺音錄製系統可靠度分析…………............................... 30
3.5.1 可靠度分析實驗方式……………………………. 30
3.5.2 雙側相關係數演算法…………………………… 33
第四章 結果與討論…………………………………………….. 37
4.1 可靠度分析實驗結果…………………………………... 37
4.1.1 頻域分析實驗結果………………………………. 37
4.1.2 雙側相關係數演算法實驗結果…………………. 44
4.1.3 肺音錄製之可靠度分析實驗結果………………. 50
4.2 實驗結果討論…………………………………………... 51
第五章 結論與未來工作……………………………………….. 54
5.1 結論…………………………………………………….. 54
5.2 未來工作……………………………………………….. 55
參考文獻………………………………………………………….. 57
附錄……………………………………………………………...... 60
dc.language.isozh-TW
dc.subject音效卡zh_TW
dc.subject肺音zh_TW
dc.subject可靠度zh_TW
dc.subject相關係數zh_TW
dc.subjectReliabilityen
dc.subjectSound carden
dc.subjectCorrelation coefficienten
dc.subjectLung sounden
dc.title音效卡肺音錄製系統可行性分析zh_TW
dc.titleFeasibility Study of Sound Card Based Lung Sound Recorderen
dc.typeThesis
dc.date.schoolyear98-2
dc.description.degree碩士
dc.contributor.coadvisor吳惠東,盧並裕
dc.contributor.oralexamcommittee林育德,余松年,陸哲駒
dc.subject.keyword肺音,相關係數,可靠度,音效卡,zh_TW
dc.subject.keywordLung sound,Correlation coefficient,Reliability,Sound card,en
dc.relation.page61
dc.rights.note未授權
dc.date.accepted2010-07-30
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept生醫電子與資訊學研究所zh_TW
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