9 January 2008 Wavelet packet-based insufficiency murmurs analysis method
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Proceedings Volume 6794, ICMIT 2007: Mechatronics, MEMS, and Smart Materials; 679417 (2008) https://doi.org/10.1117/12.784373
Event: ICMIT 2007: Mechatronics, MEMS, and Smart Materials, 2007, Gifu, Japan
Abstract
In this paper, the aortic and mitral insufficiency murmurs analysis method using the wavelet packet technique is proposed for classifying the valvular heart defects. Considering the different frequency distributions between the normal sound and insufficiency murmurs in frequency domain, we used two properties such as the relative wavelet energy and the Shannon wavelet entropy which described the energy information and the entropy information at the selected frequency band, respectively. Then, the signal to murmur ratio (SMR) measures which could mean the ratio between the frequency bands for normal heart sounds and for aortic and mitral insufficiency murmurs allocated to 15.62-187.50 Hz and 187.50-703.12 Hz respectively, were employed as a classification manner to identify insufficiency murmurs. The proposed measures were validated by some case studies. The 194 heart sound signals with 48 normal and 146 abnormal sound cases acquired from 6 healthy volunteers and 30 patients were tested. The normal sound signals recorded by applying a self-produced wireless electric stethoscope system to subjects with no history of other heart complications were used. Insufficiency murmurs were grouped into two valvular heart defects such as aortic insufficiency and mitral insufficiency. These murmur subjects included no other coexistent valvular defects. As a result, the proposed insufficiency murmurs detection method showed relatively very high classification efficiency. Therefore, the proposed heart sound classification method based on the wavelet packet was validated for the classification of valvular heart defects, especially insufficiency murmurs.
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Samjin Choi, Samjin Choi, Zhongwei Jiang, Zhongwei Jiang, } "Wavelet packet-based insufficiency murmurs analysis method", Proc. SPIE 6794, ICMIT 2007: Mechatronics, MEMS, and Smart Materials, 679417 (9 January 2008); doi: 10.1117/12.784373; https://doi.org/10.1117/12.784373
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