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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張璞曾 | |
| dc.contributor.author | Ming-Chuan Huang | en |
| dc.contributor.author | 黃銘川 | zh_TW |
| dc.date.accessioned | 2021-06-13T05:45:04Z | - |
| dc.date.available | 2006-07-21 | |
| dc.date.copyright | 2006-07-21 | |
| dc.date.issued | 2006 | |
| dc.date.submitted | 2006-07-12 | |
| dc.identifier.citation | [1] John F. Murray, Jay A. Nadel, “Textbook of respiratory medicine”, Philadelphia: W. B. Saunders, 1994.
[2] Hans Pasterkamp et al, “Respiratory Sound-Advance Beyond the Stethoscope”, Am. J. Respir. Crit. Care Med., vol. 156. pp. 974-987, 1997. [3] F. Dalmay et al, “Acoustic properties of the normal chest”, Eur. Respir. J.; 8: 1761-1769, UK, 1995. [4] 李旺祚, “新編Guyton生理學”第七版,合記圖書出版社,1991 [5] MARIKO ONO, et al, “ Separation of Fine Crackles from Vesicular Sounds by a Nonlinear Digital Filter’’, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING VOL. 36. NO. 2, FEBRUARY 1989 [6] Jie Huang, Member, et al, “A Biomimetic System for Localization andSeparation of Multiple Sound Sources”IEEF, TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 44, NO. 3, JUNE 1995 [7] S. Amari and A. Cichocki et al, “Adaptive blind signal processing—Neuralnetwork approaches” Proc. IEEE, vol. 86, pp. 2026–2048, Oct. 1998. [8] Aapo hyvarinen, “INDEPENDENT COMPONENT ANALYSIS”, John Wiley & Sons, Inc.,2001 [9] Tomoya TAKATANI, et al “BLIND SEPARATION OF BINAURAL SOUND MIXTURES USING SIMO-MODEL-BASED INDEPENDENT COMPONENT ANALYSIS”, ICASSP'2004，pp.IV-113—IV-116 2004 [10] Hiroshi Saruwatari,et al “Two-Stage Blind Source Separation Based on ICA and Binary Masking for Real-Time Robot Audition System” , Proc. of International Conference on Intelligent Robots and Systems (IROS2005), pp.215-220, August 2005 [11] Tomoya TAKATANI,et al“ HIGH-FIDELITY BLIND SEPARATION FOR CONVOLUTIVE MIXTURE OF ACOUSTIC SIGNALS USING SIMO-MODEL-BASED INDEPENDENT COMPONENT ANALYSIS”, IEICE Trans. Fundamentals, vol.E87-A, no.8, pp.2063–2072, Aug. 2004. [12] Tuomas Virtanen,Anssi Klapuri, “separation of harmonic sounds using multipitch analysis and iterative parameter estimation”IEEE Workshop on Applications of signal processing to audio and acoustics 2001. [13] Tuomas Virtanen, Anssi Klapuri, “SEPARATION OF HARMONIC SOUND SOURCES USING SINUSOIDAL MODELING”, Proc. IEEE International Conf. on Acoust., Speech, and Signal Processing,Istanbul, Turkey. [14] Hiroshi Saruwatari, “BLIND SEPARATION AND DECONVOLUTION OF MIMO-FIR SYSTEM WITH COLORED SOUND INPUTS USING SIMO-MODEL-BASED ICA” 2005 IEEE/URSI AP-S International Symposium, July 2005. [15] 胡志明, “肺音擷取系統及氣喘之哮鳴分析,”國立台灣大學電機工程研究所碩士論文, 中華民國八十七年六月. [16] 林峻毅, “肺音擷取裝置研製與環境雜訊濾除,”國立台灣大學電機工程研究所碩士論文, 中華民國九十年六月. [17] Koredianto Usman, et al. “A Study of Heartbeat Sound Separation Using Independent Component Analysis Technique”, 2004 IEEE [18] Roger L.berger, George Casella ,“Statistical Inference ”second edition ,DUXBURY 2002. [19] Stephen Roberts,Richard Everson, “INDEPENDENT COMPONENT ANALYSIS:Principles and Practice”,CAMBRIDGE UNIVERSITY PRESS ,2001 [20] Thomas L.Floyd, “ELECTRONIC DEVICE CONVENTIONAL CURRENT VERSON”SEVSNTH EDITION,PEARSON Prentice Hall,2005 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/33722 | - |
| dc.description.abstract | 在醫院，聽診是內科醫生看診最常使用的行為。 最近， 為了發展遠端醫療和居家看護系統並且幫助內科醫生能有更正確診斷，電子聽診器和電腦軟體分析已經成為一個不可避免的趨勢。 不過，心音和肺音的兩信號不僅從同時由胸腔傳出而且有一些重疊範圍。 因此，為了避免這兩個聲音在分析計算時受到影響；分離心音與肺音變得必要而重要。獨立成分分析(ICA)是從1990發展起來的算法； 它高效率的能分開兩個聲音。 在這篇文章裡，我們使用兩個聽筒從左和右胸收集信號。 我們以ICA 算法成功分離模擬的心音和肺音。 它能幫助內科醫生檢查以及在遠距醫療和居家看護上使用。 | zh_TW |
| dc.description.abstract | In hospital, physician examine emphasizes with percussion and auscultations; and auscultation is the most common way for physical exam. Recently, in order to develop Tele-medicine and Home care system and to assist physician can have more correct diagnose by auscultation; electric stethoscope and computer analysis have become an inevitable trend. However, two physical signals which include with Heart sound and lung sound are both appear from chest and also have some overlapped spectrum diagram. So, in order avoid to users misplace or untrained of stethoscope using and makes these two sounds will effect each other during with computer analysis; to separate heart sound and lung sound become necessary and important. Independent component analysis (also called ICA) is an algorithm which developed from 1990; it can separate two sounds even above efficiency. In this paper, we use two microphones to collect signals from left and right chest. And we have successfully divide heart and lung sounds by Fast ICA algorithm. And it can assist physician examine and also using on Tele-medicine and Home care by this way. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T05:45:04Z (GMT). No. of bitstreams: 1 ntu-95-P93921010-1.pdf: 2007832 bytes, checksum: 65f4a99ffdd3aa75fcfbdc462d3317ec (MD5) Previous issue date: 2006 | en |
| dc.description.tableofcontents | 第一章 緒論 1
1.1心音與肺音的基本特性 1 1.1.1 心音與肺音的發生 1 1.1.2 心音與肺音的頻率概述 2 1.2相關研究文獻回顧 4 1.3研究動機 5 1.4研究目的 6 1.5研究方法 7 1.6 論文架構 8 第二章 研究原理與方法 9 2.1獨立成份分析演算法架構與原理介紹 9 2.2獨立成份分析演算法架構與原理（Independent Component Analysis，ICA） 10 2.2.1獨立成份分析的定義 10 2.2.2 訊號重建的原理 12 2.2.3峰態(Kurtosis) 12 2.2.4熵(entropy)與負熵(negentropy) 13 2.3 獨立成份分析演算法 16 2.3.1 資料前置處理 17 2.3.2 使用負熵的固定點演算法（fixed-point algorithm using negentropy） 18 2.3.3 評估多個獨立成份分析演算法流程 21 第三章 心肺音分離系統架構 24 3.1心肺音分離系統概述 24 3.2硬體架構 26 3.2.1硬體系統概述 26 3.2.2 系統電路架構 26 3.3軟體架構 30 3.3.1 軟體系統概述 30 3.3.2 軟體系統架構 31 第四章 實驗方式與實驗結果 37 4.1模擬訊號的分離效果 37 4.1.1 模擬訊號的來源 37 4.1.2 混合的模擬訊號 38 4.1.3 模擬訊號分離的結果 41 4.2實際訊號分離重建的效果 48 第五章 結論與討論 58 5.1討論與改進方向 58 5.2結論 61 第六章 未來工作 62 參考文獻 64 | |
| dc.language.iso | zh-TW | |
| dc.title | 以獨立成份分析技術應用在心肺音分離之探討 | zh_TW |
| dc.title | A Study of Heart Sound and Lung Sound Separation by Independent Component Analysis Technique | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 94-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 林育德 | |
| dc.contributor.oralexamcommittee | 余松年,林耀任,詹曉隆,林志隆 | |
| dc.subject.keyword | 獨立成分分析(ICA),心音,肺音, | zh_TW |
| dc.subject.keyword | Independent Component Analysis,Auscultation,Heart sound,Lung sound, | en |
| dc.relation.page | 66 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2006-07-14 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
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