Heart Murmur Recognition Based on Hidden Markov Model ()
Lisha Zhong,
Jiangzhong Wan,
Zhiwei Huang,
Gaofei Cao,
Bo Xiao
Department of Biomedical Engineering, Luzhou Medical College, Luzhou, China.
Department of Biomedical Engineering, Luzhou Medical College, Luzhou, China..
DOI: 10.4236/jsip.2013.42020
PDF
HTML
5,127
Downloads
7,823
Views
Citations
Abstract
Heart murmur recognition and classification play an important role in the auscultative diagnosis. The method based on hidden markov model (HMM) was presented to recognize the heart murmur. The murmur was isolated on basis of the principle of wavelet analysis considering the time-frequency characteristics of the heart murmur. This method uses Mel frequency cepstral coefficient (MFCC) to extract representative features and develops hidden Markov model (HMM) for signal classification. The result shows that this method is able to recognize the murmur efficiently and superior to BP neural network (94.2% vs 82.8%). And the findings suggest that the method may have the potential to be used to assist doctors for a more objective diagnosis.
Share and Cite:
L. Zhong, J. Wan, Z. Huang, G. Cao and B. Xiao, "Heart Murmur Recognition Based on Hidden Markov Model,"
Journal of Signal and Information Processing, Vol. 4 No. 2, 2013, pp. 140-144. doi:
10.4236/jsip.2013.42020.
Conflicts of Interest
The authors declare no conflicts of interest.
References
|
[1]
|
C. Jian, G. Xingming and X. Shouzhong, “Study on the Signification and Method of Heart Sound Recognition,” Foreign Medical Biomedical Engineering Fascicle, Vol. 27, No. 2, 2004, pp. 87-89.
|
|
[2]
|
P. Norton and R. O’Rourke, “Approach to the Patient with a Heart Murmur,” In: G. L. Braunwald, Ed., Primary Cardiology, Elsevier, 2003, pp. 308-428.
|
|
[3]
|
Z. Lisha, G. Xingming and D. Xiaorong, “A Robust Envelope Extraction Algorithm for Cardiac Sound Signal Segmentation,” Conference of the IEEE, 2010, pp. 1-5.
|
|
[4]
|
S. Molau, M. Pitz, R. Schluter and H. Ney, “Computing Mel-Frequency Cepstral Coeffcients on the Power Spectrum,” IEEE International Conference on Acoustics, Speech, and Signal Processing, Utah, 7-11 May 2001, pp. 73-76.
|
|
[5]
|
L. R. Rabiner, “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition,” Proceedings of the IEEE, 1989, pp. 257-286
|
|
[6]
|
T. Olmez and Z. Dokur, “Classification of Heart Sounds Using an Artificial Neural Network,” Pattern Recognition Letters, Vol. 24, No. 1, 2003, pp. 617-629.
|