A biomedical system based on hidden Markov model for diagnosis of the heart valve diseases

Pattern Recognition Letters

Volumn 28, Issue 4, 2007, Pages 395-404

  Uǧuz, Harun ^a   Arslan, Ahmet ^a   Türkoǧlu, Ibrahim ^b  

^a SELCUK UNIVERSITY   (Turkey)

^b FIRAT UNIVERSITY   (Turkey)

Author keywords

Doppler heart sounds; Hidden Markov model; Pattern recognition; Wavelet decomposition

Indexed keywords

DATABASE SYSTEMS; FEATURE EXTRACTION; MARKOV PROCESSES; MATHEMATICAL MODELS; PATTERN RECOGNITION; ULTRASONICS;

DOPPLER HEART SOUNDS; HIDDEN MARKOV MODEL; WAVELET DECOMPOSITION;

BIOMEDICAL ENGINEERING;

EID: 33845505999     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2006.08.009     Document Type: Article

References (38)

1. Akay, M., Akay, Y.M., Welkowitz, W., 1992. Neural networks for the diagnosis of coronary artery disease. International Joint Conference on Neural Networks, IJCNN, vol. 2. pp. 419-424.
2. Bakhtazad A., Palazoglu A., and Romagnoli J.A. Process data de-noising using wavelet transform. Intelligent Data Analysis 3 (1999) 267-285
3. Baum L.E. An inequality and associated maximization technique in a statistical estimation for probabilistic functions of Markov processes. Inequalities 3 (1972) 1-8
4. Baum L.E., and Egon J.A. An inequality with applications to statistical estimation for probabilistic functions of Markov process and to a model ecology. Bulletin of the American Meteorological Society 73 (1967) 360-363
5. Baum L.E., and Petrie T. A maximization technique occurring in the statistical analysis of probabilistic function of Markov chain. Annals of Mathematical Statistics 41 1 (1970) 164-171
6. Baykal N., Reggia J.A., Yalabik N., Erkmen A., and Beksac M.S. Feature discovery and classification of Doppler umbilical artery blood How velocity waveforms. Computers in Biology and Medicine 26 6 (1996) 451-462
7. Bezdek J., Ehrlich R., and Full W. FCM: Fuzzy C-means clustering algorithm. Computers and Geosciences 10 (1984) 191-203
8. Bunks C., McCarthy D., and Al-Ani T. Condition-based maintenance of machines using hidden Markov models. Mechanical Systems and Signal Processing 14 4 (2000) 597-612
9. Burrus C.S., Gopinath R.A., and Guo H. Introduction to Wavelet and Wavelet Transforms (1998), Prentice Hall, New Jersey, USA
10. Centor R.M. Signal detectability: Use of ROC curves and their analysis. Medical Decision Making (1991) 102-106
11. Chan B.C.B., Chan F.H.Y., Lam F.K., Lui P.W., and Poon P.W.F. Fast detection of venous air embolism is Doppler heart sound using the wavelet transform. IEEE Transactions on Biomedical Engineering 44 4 (1997) 237-245
12. Coifman R.R., and Wickerhauser M.V. Entropy-based algorithms for best basis selection. IEEE Transactions on Information Theory 38 2 (1992) 713-718
13. Dehghan M., Faez K., Ahmadi M., and Shridhar M. Handwritten Farsi (Arabic) word recognition: A holistic approach using discrete HMM. Pattern Recognition 34 (2000) 1057-1065
14. Devasahayam S.R. Signals and Systems in Biomedical Engineering (2000), Kluwer Academic publishers, Dordrecht
15. Ge M., Du R., and Xu Y. Hidden Markov model based fault diagnosis for stamping processes. Mechanical Systems and Signal Processing 18 (2000) 391-408
16. Guler I., and Kara S. Detection of mitral stenosis by a pulsed Doppler How meter and autoregressive spectral analysis method. 14th Conference of the Biomedical Engineering Society of India, An International Meeting, Proceedings of the First Regional Conference (1995), IEEE, New York 91-92
17. Jing, F., Xuemin, W., Mingshi, W., Wie, L., 1997. Noninvasive acoustical analysis system of coronary heart disease. In: Biomedical Engineering Conference, Proceedings of the 1997 Sixteenth Southern. pp. 239-241.
18. Karabetsos E., Papaodysseus C., and Koutsouris D. Design and development of a new ultrasonic Doppler technique for estimation of the aggregation of red blood cells. Measurement 24 (1998) 207-215
19. Keeton P.I.J., and Schlindwein F.S. Application of Wavelets in Doppler Ultrasound vol. 17 (1997), MCB University Press No. 1, pp. 38-45
20. Lia Z., Wub Z., Hea Y., and Fulei C. Hidden Markov model-based fault diagnostics method in speed-up and speed-down process for rotating machinery. Mechanical Systems and Signal Processing (2004) 1-11
21. Liang H., and Nartimo I. A feature extraction algorithm based on wavelet packet decomposition for heart sound signals. Proceedings of the IEEE-SP International Symposium (1998) 93-96
22. MacQueen J.B. Some Methods for classification and analysis of multivariate observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability vol. 1 (1967), University of California Press, Berkeley 281-297
23. Madeira M.M., Tokhi M.O., and Ruano M.G. Real-time implementation of a Doppler signal spectral estimator using sequential and parallel processing techniques. Microprocessors and Microsystems 24 (2000) 153-167
24. Nwe T.L., Foo S.W., and De Silva L.C. Speech emotion recognition using hidden Markov models. Speech Communication 41 (2003) 603-623
25. Obermaier B., Guger C., Neuper C.P., and Furtscheller G. Hidden Markov models for online classification of single trial EEG data. Pattern Recognition 22 (2000) 1299-1309
26. Plett, M. I., 2000. Ultrasonic arterial vibrometry with wavelet based detection and estimation. PhD Thesis, University of Washington, pp. 17-18.
27. Quiroga R.Q., Roso O.A., and Basar E. Wavelet entropy: A measure of order in evoked potentials. Evoked Potentials and Magnetic Fields 49 (1999) 298-302
28. Rabiner L.R. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 77 2 (1989) 257-286
29. Rabiner L.R. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 77 2 (1989) 257-286
30. Rabiner L.R., and Juang B.H. An introduction to hidden Markov models. IEEE ASSP Magazine 3 (1989) 4-16
31. Rabiner L., and Juang B.-H. Fundamentals of Speech Recognition (1993), Prentice-Hall, Englewood Cliffs, NJ
32. Rosti A.-V.I., and Gales M.J.F. Factor analysed hidden Markov models for speech recognition. Computer Speech and Language 18 (2003) 181-200
33. Saini V.D., Nanda N.C., and Maulik D. Basic Principles of Ultrasound and Doppler Effect. Doppler Echocardiography (1993), Lea & Febiger, Philadelphia, London
34. Seward A. A fast HMM match algorithm for very large vocabulary speech recognition. Speech Communication 42 (2004) 191-206
35. Thomson D.L., and Chengalvarayan R. Use of voicing features in HMM-based speech recognition. Speech Communication 37 (2002) 197-211
36. Turkoglu I., Arslan A., and Ilkay E. An expert system for diagnosis of the heart valve diseases. Expert Systems with Applications 23 (2002) 229-236
37. Viterbi A.J. Error bounds for convolutional codes and an asymptotically optimal decoding algorithm. IEEE Transaction on Information Theory 13 (1967) 260-269
38. Wright I.A., Gough N.A.J., Rakebrandt F., Wahab M., and Woodcock J.P. Neural network analysis of Doppler ultrasound blood flow signals: A pilot study. Ultrasound in Medicine and Biology 23 5 (1997) 683-690