Research on Feature Extraction and Recognition of CHD Heart Sound Signal Based on S Transform
Asia-Pacific Journal of Computer Science and Technology
Volume 1, Issue 1, March 2019, Pages: 1-7
Received: Oct. 28, 2018;
Accepted: Nov. 30, 2018;
Published: Dec. 20, 2018
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Zeng Zheng, School of Information, Yunnan University, Kunming, China
Pan Jiahua, Yunnan Fuwai Cardiovascular Disease Hospital, Kunming, China
Cai Guanghui, School of Information, Yunnan University, Kunming, China
Yang Hongbo, Yunnan Fuwai Cardiovascular Disease Hospital, Kunming, China
Wang Weilian, School of Information, Yunnan University, Kunming, China
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Auscultation is the main means in the early diagnosis of congenital heart disease. The research on analysis and classification of CHD heart sound has important significant and can be used in clinical diagnosis of CHD. It will be helpful for machine auxiliary diagnosis. In this work, a feature extraction and recognition algorithm based on S transform was put forward, including the heart sound signal preprocessing, feature extraction and classification recognition. In heart sound preprocessing, denoising, envelope extracting, and segmenting were done to obtain the each cycle of the heart sound. Some of time-frequency analysis methods such as STFT, Wigner-Ville, wavelet transform, and S transform were discussed and analyzed. Then S transform and wavelet transform were used for feature extraction of each cycle. Finally, the BP neural network was used as classifier to recognize the normal and the abnormal heart sound signal. All cases of CHD heart sound used in this experiment came from heart sound data base sampled in clinic at Yunnan Fuwai Cardiovascular Disease Hospital. 361cases heart sounds including CHD and healthy heart sound were selected randomly for analysis. The result showed that recognition rates of S transform method and wavelet transform method were 80.4% and 76% respectively. S transform has a better recognition than wavelet transform.
Congenital Heart Disease (CHD), Heart Sound, S Transform, Wavelet Transform, BP Neural Net
To cite this article
Research on Feature Extraction and Recognition of CHD Heart Sound Signal Based on S Transform, Asia-Pacific Journal of Computer Science and Technology.
Vol. 1, No. 1,
2019, pp. 1-7.
Copyright © 2018 Authors retain the copyright of this article.
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