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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47866完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳兆勛 | |
| dc.contributor.author | Tzu-Ming Chung | en |
| dc.contributor.author | 鐘子茗 | zh_TW |
| dc.date.accessioned | 2021-06-15T06:23:20Z | - |
| dc.date.available | 2012-08-12 | |
| dc.date.copyright | 2010-08-12 | |
| dc.date.issued | 2010 | |
| dc.date.submitted | 2010-08-09 | |
| dc.identifier.citation | [1] Nakatani, Y., ”Skin Electric Resistance and Ryodoraku, ” J Auton
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M., “ECG Data Compression Using Wavelets and Higher Order Statistics Methods”, IEEE Transactions on Information Technology in Biomedicine, vol. 5, pp.108-115, June, 2001. [16] Castro, B., Kogan, D. and Geva, A. B., “ECG Feature Extraction Using Optimal Mother Wavelet”, Electrical and Electronic Engineers in Israel, The IEEE 8 4 21st Convention Tel-Aviv, Israel, pp.346-350, April 11-12, 2000. [17] Huang, N. E., Shen, Z., Lomg, S. R., Wu, M. C., Shih, S. H., Zheng, Q., Tung, C. C., and Liu, H. H., “The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis”, Proceedings of the Royal Society A, Vol.454, No.1971/March 08, pp 903-955, 1998. [18] Weng, B.,Blanco-Velasco, M. and Barner, K. E.,“ECG Denoising Based on the Empirical Mode Decomposition', IEEE International Conference on Engineering in Medicine and Biology Society EMBS 2006, NY, USA, 30 Aug.-3 Sep. 2006. [19] Molla, K. I., Hirose, K., Minematsu, N. and Hasan, K.,“Voiced/Unvoiced Detection of Speech Signals Using Empirical Mode Decomposition Model', IEEE International Conference on Information and Communication Technology ICICT '07,Dhaka, Bangladesh, 7-9 Mar. 2007. [20] Khan, J. F., Adhami, R. R., Bhuiyan, S. M. and Barner, K. E.,“Empirical Mode Decomposition Based Interest Point Detector', IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP 2008, Las Vegas, Nevada, USA, 30 Mar.-4 Apr. 2008. [21] Kamath, V., Lai, Y. and Zhu, L.,“Empirical Mode Decomposition and Blind Source Separation Methods for Antijamming with GPS Signals', IEEE Position Location and Navigation Symposium PLANS 2006, San Diego, California, USA, 25-27 Apr. 2006. [22] Huang, Y. X., Schmitt, F. G., Lu, Z. M. and Liu, Y. L., “An Amplitude-Frequency Study of Turbulent Scaling Intermittency Using Empirical Mode Decomposition and Hilbert Spectral Analysis', A Letters Journal Exploring The Frontiers of Physics, vol. 84, 2008. [23] Agarwal, V. and Tsoukalas, L. H., “Denoising Electrical Signal via Empirical Mode Decomposition', 2007 iREP Symposium-Bulk Power System Dynamicsand Control-VII, Revitalizing Operational Reliability, South Carolina, USA, 19-24 Aug. 2007. [24] 樊海濤、何益斌與周緒紅，”基於Hilbert-Huang變換的結構損傷診斷方法研究”，建築結構學報，第27卷，第6期，頁114-122，民國95年12月。 [25] 王炎與朱善安，”基於經驗模態分解的軸承故障診斷”，機電工程，第24卷，第10期，頁77-79，民國96年10月。 [26] 皮紅梅、劉財與王典，”利用Hilbert-Huang變換提取地震信號瞬間參數”，石油地球物理勘探，第42卷，第4期，頁418-424，民國96年8月。 [27] C Ionescu-Tirgoviste., et al., ”Electric Skin Resistance in the Diagnosis of Neuroses,” Am J Acupunt, Vol. 2, pp. 247-252, 1974. [28] Zhu, Z. X., ”Research Advance in the Electrical Specificity of Meridians and Acupuncture Points,” Am J Acupunct, Vol. 9, pp. 203-216, 1981. [29] 張永賢，”電腦腧穴良導絡診療的原理及臨床應用”，一元醫訊， pp.16-20，1988。 [30] 李旺祚，“新編生理學”，合計圖書出版社，135-155 頁，民國80年。 [31] Webster, J. G., “Electroencephalography: Brain electrical activity”, Encyclopedia of medical devices and instrumentation, Vol.2, pp. 1084-1107, 1988. [32] 胡慕美，“Ganong 生理學”，合計圖書出版社，200-204 頁，民國80年。 [33] Aston, R., “Principle of Biomedical Instrumentation and Measurement”,Merrill Publishing Company, 1990. [34] TD1A操作手冊。 [35] Schaul, N., “The Fundamental Neural Mechanisms of Electroencephalography”,Electroencephalography and clinical Neurophysiology, Vol. 106, pp. 101-107,1998. [36] 丁建元，鄭智銘，”心電圖原理簡介”，元智大學， 2001 [37] 茅耀斌 ,”小波信號處理及其應用”,.2005年9月. [38] Valens, C., “A Really Friendly Guide to Wavelet”,June 2005. [39] Chamberlain, N. F., “Introduction to Wavelets Using the Haar Wavelet”, June ，2005. [40] Vegte, J. V. D., “Fundamentals of Digital Signal Processing”, Prentice Hall, 2002. [41] Guo, D. f.,”A Study of Wavelet Thresholding Denoising”[C]// IEEE Proceeding of ICSP, 2000. [42] ZHANG, W.Q. , SONG G.X.,”Signal De-noising in Wavelet Domain Based on a New Kind of Thresholding Function”April 2004. [43] LIU, J.,and ZHU, Q. B.,”Signal De-noising Research Based on New Threshold Function via Dyadic Wavelet Transform”May 2006. [44] YE, Y.L.,and DAI, W.Z.,”Signal De-noising in Wavelet Based on New Threshold Function”July 2006. [45] 于德介，楊宇，”機械故障診斷的Hilbert-Huang變換方法”科學出版社，2006。 [46] 張貨君，基於HHT的機電系統的滾動軸承故障診斷，太原理工大學碩士論文，2006年5月。 [47] Gabor,D.,”Theory of Communication”,Proceedings of the IEEE,Vol.93,pp.429-457,1946 [48] Tichmarsh,E.C.,”Introduction to the Theory of Fourier Integrals”,Oxford University Press,1948. [49] Newland, D.E.,”An Intriduction to Random Vibrations”,Spectral and Wavelet Analysis”,John Wiley and Sons,1993. [50] Chao, C.F.,” Wavelet-Based EEG Analysis and AutomaticClassification System of Long-Term Polysomnography”,NTU, 2005. [51] Percival and Walden,”Wavelet Methods for Time Series Analysis” , 2000. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47866 | - |
| dc.description.abstract | 從過去的文獻可知，當身體內臟腑產生病變時，會在體表反應出來，而這個反應機制是藉由量測各個穴位的皮膚電阻抗，依量測數值的大小，可以推測每個臟腑的運作情形，是否有病症的存在，這就是所謂的良導絡測定。對於傳統的良導絡量測儀，因為其測定導子的電解棉的濕潤度和參考電位導子的壓力不固定，讓所量測時容易造成誤差，使得良導絡的可信度降低。
本研究之目的首先為改善上述的幾個缺點，以改良的良導絡系統量測。在硬體方面，使用電極貼片來代替測定導子，使電解棉的濕潤度和測試壓力恆定，並利用NI(National Instrument)的DAQ卡來擷取訊號，來達到24點的同步量測，可即時的觀測到左右12經絡點共24經絡穴位點的良導絡值。在軟體設計方面，搭配Labview的人機操作介面，在DAQ卡擷取資料後，做一個自動即時偵測的量測功能。 在西方醫學的生理訊號，本研究考量非侵入性且操作容易，所以採用腦電圖和心電圖來後置處理。在腦電圖方面，使用小波轉換的多分辨分析的概念，將腦電訊號依照β、α、θ和δ的各個特徵頻帶來做多分辨分析的分解。在心電圖方面，比較小波轉換和希爾伯特黃轉換的處理效果，最後選擇希爾伯特黃轉換來處理心電訊號，因經處理完的心電訊號具有完整性，方便判讀波型特徵。 最後，將中醫上良導絡的理論和西醫上的生理訊號量測診斷，搭配著參考診斷，相輔相成，讓良導絡的病症判斷更準確，做一個治療上的輔助，若在身體有些微的病狀時做一個預防的保健醫療保養。 | zh_TW |
| dc.description.abstract | Some research reported that the internal organic condition will reflect to external body surface. This reaction could be measured by the skin electric impedance of acupuncture points, that is, Ryodoraku Measurements. However, experiment error of humidity of electrolytic cotton in conducts and the unsteady pressure of reference conduct in traditional acupuncture instrument decrease reliability.
My research improved traditional acupuncture instrument, and overcame the above-mentioned disadvantage. In the hardware, we replaced the conducts by electrode patch to steady the humidity of electrolytic cotton and pressure. Using the NI’s DAQ card, we could collect 24 Ryodoraku values from acupuncture points at once, each12 point of right and left side of body. In the software, the Ryodoraku values were analyzed by Labview which is Human Machine Interaction could automatically and instantaneously monitor the signals from NI’s DAQ card. In the biophysical signals of western medicine, my research takes account of non-invasive and easy-operated so I adopted EEG and ECG for the post processing. In the EEG, the decomposition of EEG depended on the feature of frequency band ofβ、α、θ and δ by using the multi-resolution analysis method. In the ECG, compared Wavelet transform with Hilbert-Huang transform, chose Hilbert-Huang transform to deal with ECG at last because the shape is complete and easy to analyze the feature of wave. Combined Ryodoraku Measurements in traditional Chinese medicine and biophysical signals analysis in western medicine, disease evaluation become instantaneously and more accurate. In the future, it can be better apply to preventive health care and home health care. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T06:23:20Z (GMT). No. of bitstreams: 1 ntu-99-R97543040-1.pdf: 24085946 bytes, checksum: dc2e7f70c6cda8ef0845f8ba2a903970 (MD5) Previous issue date: 2010 | en |
| dc.description.tableofcontents | 第一章 緒論 1
1-1研究動機與目的 1 1-2研究背景 2 1-3論文架構 4 第二章 小波轉換與生理訊號理論 5 2-1何謂經絡 5 2-1-1經絡學說 5 2-1-2經絡現象 6 2-1-3經絡系統 6 2-2良導絡理論 9 2-2-1良導絡起源 9 2-2-2良導絡與自律神經之關係 9 2-2-3從皮膚電性看經絡與良導絡 10 2-2-4良導絡測定法 11 2-3良導絡量測電路原理 12 2-4腦電與心電訊號 12 2-4-1 神經細胞電位 12 2-4-2腦波的產生與分類 13 2-4-3腦波電極記錄 16 2-4-4心電圖簡介 18 2-5小波理論 20 2-5-1小波發展的歷史 20 2-5-2小波轉換的概念 21 2-5-3多層次解析法 27 2-5-4小波函數的介紹 29 2-5-5小波基底的選擇 32 2-6小波閥值去噪理論 33 2-6-1硬閥值(Hard Threshold)和軟閥值(Soft Threshold)的算法 33 2-6-2新的閥值濾波方法 35 第三章 希爾伯特黃轉換(HILBERT-HUANG TRANSFORM) 37 3-1希爾伯特轉換(HILBERT TRANSFORM) 37 3-2經驗模態分解法(EMPIRICAL MODE DECOMPOSITION ,EMD) 42 3-3希爾伯特頻譜分析(THE HILBERT SPECTRAL ANALYSIS) 44 第四章 實驗系統架構設計與方法 46 4-1量測電路 46 4-1-1訊號的量測方式 46 4-1-2 硬體量測電路的架構 47 4-2腦電和心電圖量測 58 4-2-1腦電圖(EEG)量測 59 4-2-2心電圖(ECG)量測 59 4-3小波閥值去噪設計 59 4-3-1小波的分解方法 59 4-3-2小波基底選擇 60 4-3-3小波閥值濾波方法 65 4-3-4小波的重構方法 66 4-4 HILBERT程式設計流程 68 第五章 實驗結果與討論 71 5-1電路量測結果 71 5-1-1直流電(DC)和交流電(AC)量測比較 71 5-1-2自製量導絡電路實際量測 72 5-2 小波閥值濾波結果 73 5-2-1小波基底選擇 73 5-2-2小波閥值濾波比較 76 5-3小波處理腦電圖 80 5-4希爾伯特黃轉換分析(HILBERT-HUANG TRANSFORM) 84 5-4-1希爾伯特黃轉換模擬分析 84 5-4-2希爾伯特黃轉換在ECG濾波及分析 93 5-4-3希爾伯特黃轉換和小波轉換濾波比較 102 第六章 結論與未來展望 108 6-1 結論 108 6-2未來展望 109 參考文獻 111 | |
| dc.language.iso | zh-TW | |
| dc.subject | 腦電圖 | zh_TW |
| dc.subject | 小波轉換 | zh_TW |
| dc.subject | 心電圖 | zh_TW |
| dc.subject | Labview | zh_TW |
| dc.subject | DAQ卡 | zh_TW |
| dc.subject | 良導絡 | zh_TW |
| dc.subject | 皮膚電阻 | zh_TW |
| dc.subject | 希爾伯特黃轉換 | zh_TW |
| dc.subject | 電極貼片 | zh_TW |
| dc.subject | electrode patch | en |
| dc.subject | Hilbert-Huang transform | en |
| dc.subject | Wavelet transform | en |
| dc.subject | ECG | en |
| dc.subject | EEG | en |
| dc.subject | Labview | en |
| dc.subject | Ryodoraku | en |
| dc.subject | DAQ card | en |
| dc.subject | skin electric impedance | en |
| dc.title | 改善良導絡系統與小波轉換和希爾伯特黃轉換處理生理訊號 | zh_TW |
| dc.title | Improvement of Ryodoraku System and Analyses of Biophysical Signals Using the Wavelet Transform and Hilbert-Huang Transform | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蔡明義,鄭江河 | |
| dc.subject.keyword | 皮膚電阻,良導絡,電極貼片,DAQ卡,Labview,腦電圖,心電圖,小波轉換,希爾伯特黃轉換, | zh_TW |
| dc.subject.keyword | skin electric impedance,Ryodoraku,electrode patch,DAQ card,Labview,EEG,ECG,Wavelet transform,Hilbert-Huang transform, | en |
| dc.relation.page | 115 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2010-08-09 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 應用力學研究所 | zh_TW |
| 顯示於系所單位： | 應用力學研究所 | |
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