(3.238.186.43) 您好!臺灣時間:2021/03/05 21:09
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:蔡佩勳
研究生(外文):TSAI PEI-HSUN
論文名稱:以數學模型技術應用於膝關節振動訊號分析
論文名稱(外文):Application of the mathematical modeling technology in Knee Joint vibration signals analysis
指導教授:李枝宏李枝宏引用關係
指導教授(外文):Ju-Hong Lee
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:電信工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:171
中文關鍵詞:關節振動測量術自回歸時譜可適性區段主極點功率比均方根值內部群組距離單方變異數分析
外文關鍵詞:vibration arthrometryVAMAutoregressive (AR)CepstralAdaptive segmentationspectral power ratio of dominant polesRoot Mean Square (RMS)intraclass distanceone-way ANOVA
相關次數:
  • 被引用被引用:10
  • 點閱點閱:241
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:46
  • 收藏至我的研究室書目清單書目收藏:0
在骨科的臨床上,發現當膝關節發生病變時,其活動時會產生異常的聲音,即膝關節在擺動下所產生的振動訊號,vibration arthrometry(VAM)即是藉由分析此一振動訊號來診斷膝關節的病變。而本研究即是針對內、外側半月板的振動訊號來分析。由於VAM是一種非侵襲性的檢查工具,因此極具發展潛力。
因此本研究即應用VAM在內、外側半月板振動訊號上,利用自回歸(AR)和時譜(Cepstral)經由可適性區段後建立訊號的數學模型,在與臨床發現對照後找出上述疾病的特徵參數。我們發現膝關節於快速擺動下所產生的振動訊號可以用來區分正常者與內、外側半月板破裂患者。
在內、外側半月板破裂患者與正常者的對照組中,本研究在主極點功率比的頻帶搜尋中,找出了最佳的頻帶。在這個最佳頻帶中,內、外側半月板破裂患者與正常者之間對主極點功率比的單方變異數分析(one-way ANOVA),最具有統計上的意義(亦即具有最大的F值),也就是說,在這個最佳頻帶中,內、外側半月板破裂患者與正常者具有最大的差異性。
關節振動測量術是一種非侵襲性且簡單方便低成本的膝關節病變診斷工具。本項技術的持續發展,將可成為醫生診斷時另一種重要的工具,藉由選用適當的治療方式,不僅解除了病患的痛苦,也可以避免醫療資源的浪費。
A phenomenon can be found which abnormal joint sound arises from knee joint disorder during knee motion in the clinical diagnosis. The knee joint could produce vibration signals during normal flexion extension motion, and the vibration arthrometry(VAM)could diagnose the disorders of the knee joint by analyzing these vibration signals. In this study we will apply VAM to the patients of the medial and lateral meniscus tear. Because VAM is a noninvasive diagnostic tool, it has great potential.
The main methods in the thesis we apply VAM to the vibration signals of the medial and lateral meniscus tear, utilizing autoregressive and cepstral to establish the mathematical model after adaptive segmentation, and try to find out the characteristic parameters of the vibration signals in these diseases. we have found that the vibration signal emitted by the knee joint under rapid motion can be used to separate the normal volunteers from the patients of the normal and medial、lateral meniscus.
In the contrast of medial、lateral meniscus tear and normal patients, we use the best frequency band search of the power spectral ratio of dominant poles. In this best frequency band, the one-way ANOVA between normal and medial、lateral meniscus tear patients has the most “F value”. In other words, the most difference of the normal and medial、lateral meniscus tear patients in this best frequency band.
Vibration arthrometry (VAM) provided a noninvasive, simple, and cheap clinic tool for diagnosing knee joints. Appropriate therapy can be given to the patients with correct diagnosis.
第一章 緒論 1
1.1本論文之研究背景  1
1.2相關研究文獻之回顧  3
1.3本論文之研究動機  5
1.4本論文之組織架構  6
第二章 人體膝關節之解剖構造以及內、外側半月板病變 8
2.1人體膝關節之解剖構造  8
2.2內、外側半月板  10
第三章 膝關節於快速擺動下所產生的振動信號(VAM訊號)之分析研究 17
3.1 導論  17
3.2 材料與方法  19
3.2.1 儀器設備  19
3.2.2 訊號量測  22
3.2.3 演算法  24
1.自回歸(AR)模型  26
2.時譜(Cepstral)分析  34
3.可適性區段  36
3.2.4特徵參數 38
1.均方根值  38
2.內部群組距離  39
3.主極點功率比  39
3.2.5單方變異數分析  40
3.2.6最佳頻帶的找尋法 42
第四章 應用自回歸(AR)模型及時譜(Cepstral)於膝關節外側半月板病變之分析研究 47
4.1導論   47
4.2 自回歸(AR)模型實驗結果  49
4.2.1 均方根值  49
4.2.2內部群組距離 50
4.2.3主極點功率比   51
4.3 時譜(Cepstral)分析實驗結果  54
4.3.1 均方根值  54
4.3.2內部群組距離 55
4.3.3主極點功率比 56
4.4討論與結論  57
第五章 應用自回歸(AR)模型及時譜(Cepstral)於膝關節內側病變之分析研究 80
5.1導論  80
5.2 自回歸(AR)模型實驗結果    82
5.2.1 均方根值  82
5.2.2內部群組距離 83
5.2.3主極點功率比  84
1.正常者、半月板正常者與半月板破損者三  84
2.正常者與半月板正常者二群  86
3.正常者與半月板破損者二群  87
4.半月板正常者與半月板破損者二群   89
5.3 時譜(Cepstral)分析實驗結果  90
5.3.1 均方根值  90
5.3.2內部群組距離 92
5.3.3主極點功率比  93
1.正常者、半月板正常者與半月板破損者三群  93
2.正常者與半月板正常者二群  94
3.正常者與半月板破損者二群  96
4.半月板正常者與半月板破損者二群  97
5.4討論與結論 99
第六章 綜合討論與未來展望159
參考文獻 163
附錄:關節量測儀的儀器規格
[1] K.L. Moore, Clinically Oriented Anatomy. Baltimore, MD: Williams/Wilkins, 1984.
[2] R.W. Jackson and I. Abe,“The role of arthroscopy in t-he management of disorders of the knee: An analysis of 200 consecutive examinations,”J. Bone Surg. (Brit.), vol.54-B, pp.310-322,1972.
[3] S. Tavathia, R.M. Rangayyan, C.B. Frank, G.D. Bell, K.O.Ladly, and Y.T. Zhang, ”Analysis of knee vibration si-gnals using linear prediction," IEEE Trans. Biomed. E-ng., vol. 39, no.9, pp.959-970, 1992.
[4] W.G. Kernohan, and R.A.B. Mollan,”Processing of sound signals n orthopaedic sugery," in Proc. 2nd. European Signal Processing Conf. (EUSIPCO-83)}, H.W. Schussler,Ed. North Holland: Elsevier, pp. 581, 1983.
[5] C. Heuter, Grundhiss der chirurgie. Leipzig: F.C.W. Vo-gel,3rd ed.,1885
[6] W.E. Blodgett,”Auscultation of the knee joint,”Boston Med.Surg.J.,vol.146,no.3,pp. 63-66,Jan,1902
[7] E.Bircher,”Zur Diagnose der Meniscusluxation und des Meniscusabrisses,”Zentralbl.Chir.,vol.40,pp.1852-1857,1913
[8] C.F.Walters,”The value of joint auscultation,” Lancet, Vol. 1, pp. 920-921, May,1929.
[9] K.H. Erb,”Uber die Moeglichkeit der Registrierung von Gelenkgeraeuschen,” Deutsche Z. Chir., vol.241, pp.237-245, 1933
[10] A.Steinder,”Auscultation of joint,”J. Bone Joint Surg., vol.19, pp. 121-124, 1937
[11] A. Peylan, ”Direct auscultation of the joints (preliminary clinical observations),” Rheumatism, vol.9,pp.77-81,1953.
[12] H. Fischer and E.W.Johnson, ”Analysis of sounds from normal and pathologic knee joints, ” in 3rd Int. Congr. Phys. Med., pp.50-57,1960.
[13] Z. Szabo, L. Danis, and Z. Torok, “Examination of the acoustic phenomena observed in the knee,” Traunatologia, vol.15,no.2,pp.118-127,1972.
[14] M.L. Chu, I.A. Gradisar, M.R. Railey, and G.F. Bowli-ng,”Detection of the knee joint diseases using acous-tical pattern recognition technique," J.Biomechan., vol. 9, pp. 111-114 , 1976.
[15] M.L. Chu, I.A. Gradisar, M.R. Railey, and G.F. Bowli- ng,”Computer aided acoustical correlation of patholo-gical cartilage generated noise,” in 30th Ann. Conf. Med. Biol., vol. 5, pp. 175,1997.
[16] M.L. Chu, I.A. Gradisar, M.R. Railey, and G.F. Bowling,”An electroacoustical technique for the detection of knee joint noise ," Med. Res. Eng., vol.12, no.1, pp. 18-20 , 1976.
[17] M.L. Chu, I.A. Gradisar, R. Mostardi,”A noninvasive electroacoustical evalution technique of cartilage damage in pathological knee joints,"Med. Biol.Eng. Comput., vol.16, pp. 437-442,July, 1978.
[18] R.A.B. Mollan, G.C. McCullagh, and R.I. Wilson,” A critical apprasial of auscultation of human joints ,"Clin. Orthopaed. Related Res., no.170, pp.231-237,Oct.1982.
[19] W.G. Kernohan and R.A.B. Mollan, ”Microcomputer analysis of joint vibration,”J. Microcomputer Appl., vol.5, pp. 287-296,19-82
[20] W.G. Kernohan, D.E. Beverland,G.F. McCoy, S.N. Shaw, R.G.H.Wallace, G.C. McCullagh, and R.A.B. Mollan,”The diagnostic potential of vibration arthrography,"Clin. Orthopaed.Related Res.,pp. 106-112, Sept. 1986.
[21] C.B. Frank, R.M. Rangayyan, and G.D. Bell, ”Analysis of knee joint sound signals for noninvasive diagnosis of cartilage pathology," IEEE Eng. Med. Biol. Mag., pp. 65-68, 1990.
[22] Z.M.K. Moussavi, R.M. Rangayyan, G.D. Bell, C.B. Frank,K.O.Ladly, and Y.T. Zhang,” Screening of vi- broarthrographic signalsvia adaptive segmentation and linear prediction modeling,"IEEE Trans. Biomed. Eng., vol. 43, pp. 15-23, 1996.
[23] S. Krishnan, R.M. Rangayyan, G.D. Bell, C.B. Frank, and K.O.Ladly,”Recursive least squares-lattice based adaptive segmentation, and autoregressive modeling of nonstationary vibroarthrography signals," in Proc. Canadian conf. Electrical and Computer Engineering, Calgary, Alta., Canada, pp. 339-342, May 1996.
[24] Y.T. Zhang, C.B. Frank, R.M. Rangayyan, and G.D. Bell,” Mathematical modeling and spectrum analysis of the physiological patello-femoral Pulse train produced by slow knee movement,"IEEE Trans. Biomed. Eng., Vol. 39, no. 9, pp. 971-979, 1992.
[25] Y.T. Zhang, R.M. Rangayyan, C.B. Frank, and G.D. Bell ,”Adaptive cancellation of muscle contraction inter-ference from knee joint vibration signals,"IEEE Trans. Biomed. Eng., Vol.41 , no.2,pp.181-191,1994.
[26] R.M. Rangayyan, S. Krishnan, G.D. Bell, C.B. Frank,andK.O.ladly, ”Impact on muscle contraction interferemcecancellation on vibroarthrographic screening,"in Proc. Int. Conf. Biomed. Eng., Kowloon, Hong Kong, pp.16-19 , June 1996.
[27] R.M. Rangayyan, S. Krishnan, G.D. Bell, C.B. Frank,andK.O.Ladly,”Parametric representation and screening ofknee joint vibroarthrographic signals," IEEE Trans. Biomed. Eng.,vol.44,no. 11, pp.1068-1074, 1997.
[28] C.C. Jiang, Y.J. Liu, K.M. Yip and E. Wu,"Physiol- ogical patellofemoral crepitus in the joint disor- ders " Bulletin Hospital for Joint Disease, vol. 53, no. 4, pp. 22-26, 1995.
[29] Ching-Chuan Jiang, Ju-Hong Lee, and Tung-Tai Yuan, “Vibration Arthrometry in the Patients with Failed Total Knee Replacement,” IEEE Trans. Biomed. Eng., VOL.47, NO.2, January 2000.
[30] Ju-Hong Lee, Ching-Chuan Jiang, and Tung-Tai Yuan, “Vibration Arthrometry in Patients with Knee Joint Disorders,” IEEE Trans. Biomed. Eng., VOL.47, NO.8, August 2000.
[31] 劉益瑞著, Vibration Arthrography : Signals analysis andMechanism in degenerative osteoarthritis of the knee,master''s thesis, 私立中原大學, 1994.
[32] 袁同台著, Analysis of the vibration signals arising from knee joints with degenerative osteoarthritis and worn-out prostheses, master''s thesis,國立臺灣大學, 1998.
[33]蓋隆祥著, The mathematical modeling of the patellofemoral vibration signals, master''s thesis, 國立臺灣大學, 1999.
[34] 鄭俊達、傅宇輝等合譯,骨科學原理及應用(上),pp. 536 大中國圖書公司, 台北, 1987.
[35] 林春輝發行, 醫學保健百科全書 IV, 骨、關節與肌肉, 光復書局, 1987.
[36] 林春輝發行, 家庭醫學圖書館 16, 骨骼、肌肉與關節, 光復書局, 1996.
[37] Marple, Jr., “Digital Spectral Analysis With Applica-tions”, Prentice-Hall, 1987.
[38] S. Haykin, “Adaptive Filter Theory”, 3rd ed., Prentice-Hall International, 1996.
[39] S.M. Kay, “Modern Spectral Estimation”, Prentice-Hall, 1988.
[40] J. Makhoul, “Linear prediction: A tutorial review,” Proc. IEEE, vol. 63, No. 4, pp 561-580, Apr. 1975.
[41] W.J. Kang, J.R. Shiu, C.K. Cheng, J.S. Lai, H.W. Tsao,and T.S. Kuo. “The application of cepstral coefficients and maximum likelihood method in EMG pattern recognition,” IEEE Trans. On Biomedical Eng. Vol. 42, No. 8, pp 777-785, Aug. 1995.
[42] S.C. Chapra and R.P. Canale, Numerical Method for En-gineers, McGraw-Hill, 1989.
[43] 楊志良編著,生物統計學新論,巨流圖書公司,台北,1983.
[44] 蕭如英譯,生物統計學導論,五南圖書出版公司,台北,1984.
[45] 郭英調編著,臨床研究手冊,合慶國際圖書,台北,2000.
[46] A.V. Oppenheim and R.W. Schafer, “Digital signal Proc-essing”. Englewood Cliffs, NJ: Prentice-Hall, 1975
[47] J.D. Markel and A.H. Gray, “Linear Prediction of Speech.” Berlin: Springer-Verlag, 1976
[48] B.S. Atal, “Effectiveness of linear prediction chara-cteristics of the speech wave for automatic speaker i-dentification and verification,”J. Acoust. Soc. Amer.,vol. 55,no. 6, pp. 1304-1312, June 1974.
[49] Ching-Chuan Jiang, Yi-Jui Liu, Kin-Man Yip, Shin-En Fu and Jenn-Lung Su, “Vibration Arthrometry of the Knee with Torn Meniscus: A Preliminary Report,” J Formos Med Assoc 1994; VOL.93:622-625.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊
 
系統版面圖檔 系統版面圖檔