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姓名 余宗霖(Tsung-Lin Yu)  查詢紙本館藏   畢業系所 電機工程學系
論文名稱 氣喘肺音監測系統之可行性研究
(A Feasibility Study of Asthmatic Lung-sound Monitoring Systems)
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摘要(中) 氣喘病是一種慢性支氣管發炎,氣喘發生在臨床上有許多特徵,就肺音訊號而言,哮鳴音為最典型的氣喘發作特徵,另外肺音頻率的變化也是一個相當重要的參考指標。
本篇論文的研究目的,主要是發展一個氣喘肺音監測系統,系統硬體設計包含電容式麥克風的聽診頭、肺音放大濾波電路,資料擷取系統及dsPIC微處理器的警報系統;軟體設計則利用Matlab撰寫監測演算系統,利用C語言撰寫dsPIC微處理器,另外使用者介面使用Matlab圖控人機介面(GUI),分析方法利用快速傅立葉轉換(FFT)、時頻譜圖(Spectrogram)為基礎作為哮鳴音偵測方法。
氣喘肺音監測利用估算哮鳴音發生的時間及肺音中心能量的頻率來作為觀測氣喘病患的參數,我們設計以10秒擷取肺音一次,並即時計算出參數值,當有異常狀況時可即時發出警報,並可將各項參數及肺音儲存於電腦中,可全天候作偵測監控,監測的參數及肺音也可提供醫師作診斷的判斷。由現階段的發展我們可以正確的區分出正常肺音與哮鳴音,並利用評估參數值而判定氣喘病患的發病狀況。在未來若想由肺音去預警氣喘的發作則需作臨床氣喘肺音及流量值的收集分析,才能做進一步的研究。
摘要(英) Asthma is a chronic bronchus inflammation. In the clinical, there are many characteristics during asthmatic attack. As per lung sound, wheezing is a common clinical finding in patient with asthma. Also, the change of the frequency is an important index.
In this thesis, developing an asthma monitoring system based on auscultating lung sound is the principal purpose. The hardware and software are involved in the asthma monitoring system as follows. The hardware includes microphone with stethoscope bell、amplifier、filter、data acquisition device and microprocessor. The software includes Matlab for monitoring analysis、C language for microprocessor and graphical user interface (GUI) developed by Matlab. The power spectrum of lung sound is analyzed by FFT. Base on time-frequency transform by spectrogram is the analyzable method for the wheezing.
Proportion of the respiratory cycle occupied by wheeze (Tw/Ttot) and central frequency (Fc) are two index parameters in the asthma monitoring system. The lung sound is got ever ten minutes and parameters are saved in the computer. This system can automatically locate and identify the wheeze signal pattern form lung sound. For physician, they can diagnosis asthmatic patients by record of the parameters and lung sound from the system. For asthmatic patients, the system will give an monitoring alarm under the uncommon condition. The conclusion of the system in the thesis, it is useful for the dividing under uncommon wheeze then alerting from the system. However, pre-alerting for initial asthmatic attack based on lung sound should be furthered researching the relationship between flow and lung sound from asthmatic patient in the future.
關鍵字(中) ★ 氣喘
★ 哮鳴音
★ 時頻譜圖
★ 肺音
關鍵字(英) ★ Lung sound
★ Asthma
★ Wheeze
★ Spectrogram
論文目次 目錄
中文摘要
英文摘要
目錄 Ⅰ
圖目錄 Ⅲ
表目錄 Ⅴ
第一章 緒論 1
1.1研究動機 1
1.2 氣喘病概況 1
1.3 肺音 2
1.4文獻回顧 7
1.5論文架構 9
第二章 氣喘的模型 11
2.1氣喘的病理模型 11
2.2氣喘的特性 14
2.3氣喘的診斷 16
2.4氣喘的肺音模型 17
第三章 系統架構 22
3.1麥克風電路 22
3.2錄音設備 30
3.3類比/數位轉換電路 31
3.4資料傳輸介面 35
第四章 氣喘偵測演算程式 37
4.1 原理 37
4.2哮鳴(wheeze)偵測 41
4.3使用者介面 50
第五章 系統性能評估 51
5.1實驗結果 51
5.2未來方向 62
5.3結論 64
參考資料 65
參考文獻 [1] M. Mahagnah, and N. Gavriely, “Repeatability of Measurement of
Normal Lung Sound,” Am. J. Respir. Crit. Care Med. Vol. 149. pp. 477-481, 1994.
[2] L. J. Hadjileontiadis and I. T. Rekanos,“Detection of
Explosive Lung and Bowel Sounds by Means of Fractal Dimension” IEEE Signal Processing Letters, Vol. 10, NO. 10, pp. 311-314, 2003
[3] B. Sankur, E. C. Guler and Y. P. Kahya, “Multiresolution biological transient extraction applied to respiration crackles,” Comput. Biol. Med., Vol. 26, No. 1, pp. 25-39, 1996.
[4] M. Ono, K. Arakawa, M. Mori, Tsuneaki Sugimoto, and
Hiroshi Harashima, “Sparation of fine crackle from vesicular sounds
by a nonlinear digital filter,” IEEE Transactions on Biomedical
Engineering, Vol. 36, No. 2, 1989.
[5] J.E.Earis, B.M.G. Cheetham, “Current methods use for computerized
respiratory sound analysis,” Eur Respir Rev 10: 77, pp. 586 – 590, 2000.
[6] K.A.Kim, J.H.Lee, T.S.Lee,E.J.Cha, “Peak expiratory flow meter
capable of spirometric test for asthma,” Conference of the IEEE EMBS IEEE, October, pp. 254-255, 2003.
[7] 王柏力, 葉郁欣, “智慧型氣喘監視系統之研發,” 行政院國家科學委員會專題研究計畫成果報告, 2004.
[8] G. Mac. Cochrane, W. Jackson and P. John Rees, Asthma
(current perspective), 1996。
[9] 胡志明, “肺音節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.
[10] Jose´ A. Fiz, Raimon Jane´, Antonio Homs, Jose´ Izquierdo,
Maria A. Garcý´a, and Jose´ Morera, “Detection of Wheezing
During Maximal Forced Exhalation in Patients With Obstructed
Airways,”Chest, 122: 186-191, 2002.
[11] R. P. Baughman, and R. G. Loudon,“Quantitation of
Wheezeing in Acute Asthma,”Chest, 86/5: 718-722, 1984.
[12] T. R. Fenton, H. Pasterkamp, A. Tal, and Victor
Chernick,“Automated Spectral Characterization of Wheezing in
Asthmatic Children,”IEEE Transactions on Biomedical
Engineering Vol. BME-32, No.1, pp. 50-55, 1985.
[13] I. Hossain, and Z. Moussavi, “Finding the Lung sound-Flow
Relationship in Normal and Asthmatic Subjects,” International
Conference of the IEEE EMBS, September, pp. 3852-3855, 2004.
[14] R. Jane, D. Salvatella, J. A. Fiz, and J. Morera, “Spectral analysis of respiratory sounds to assess bronchodilator effect in asthmatic patients,” Conference of the IEEE EMBS, Vol. 20, No. 6, 1998.
[15]張西川、陳方祝翻譯,呼吸系統,光復書局,1995。
[16] R. L. Wilkins, J. E. Hodgkin, Brad Lopez, Lung Sounds A Practical Guide, Mosby, 1996.
[17] Y. H. Hiew, J. A. Smith, J. E. Earis, B. M. G. Cheetham and A. A. Woodcock, “DSP Algorithm Cough Identification and Counting,” Conference of the IEEE Acoustics, Speech, and Signal Processing,
IV3888-IV3891, 2002.
[18] “dsPIC30F Family Reference Manual,” Microchip.
[19] Nobuyuki Otsu, “A Threshold Selection Method from Gray-Level
Histograms,” Transactions on Systems, Man, and Cybernetics, Vol. SMC-9, No. 1, pp. 62-66, 1979.
[20] M. Waris, P. Helistö, S. Haltsonen, A. Saarinen, A.R.A. Sovijärvi, “A new method for automatic wheeze detection,” Technology and Health Care 6, pp. 33-40, 1998.
[21] S. A. Taplidou, L. j. Hadjileontiadis, T. penzel, V.Gross and S. M. Panas, “An Efficient Wheezing-Episode Detector Based on Breath Sounds Spectrogram Analysis,” Conference of the IEEE EMBS, September, pp. 17-21, 2003.
指導教授 蔡章仁(Jang-Zern Tsai) 審核日期 2005-7-19
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