Phonocardiogram Segmentation and Abnormal Phonocardiogram Screening Algorithm Based on Cardiac Cycle Estimation

ZHAO Zhan; ZHANG Xuru; FANG Zhen; CHEN Xianxiang; DU Lidong; LI Tianchang

doi:10.11999/JEIT170108

Volume 39 Issue 11

Nov. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(11): 2677-2683

ZHAO Zhan, ZHANG Xuru, FANG Zhen, CHEN Xianxiang, DU Lidong, LI Tianchang. Phonocardiogram Segmentation and Abnormal Phonocardiogram Screening Algorithm Based on Cardiac Cycle Estimation[J]. Journal of Electronics & Information Technology, 2017, 39(11): 2677-2683. doi: 10.11999/JEIT170108

Citation:

ZHAO Zhan, ZHANG Xuru, FANG Zhen, CHEN Xianxiang, DU Lidong, LI Tianchang. Phonocardiogram Segmentation and Abnormal Phonocardiogram Screening Algorithm Based on Cardiac Cycle Estimation[J]. Journal of Electronics & Information Technology, 2017, 39(11): 2677-2683. doi: 10.11999/JEIT170108

Citation:

ZHAO Zhan, ZHANG Xuru, FANG Zhen, CHEN Xianxiang, DU Lidong, LI Tianchang. Phonocardiogram Segmentation and Abnormal Phonocardiogram Screening Algorithm Based on Cardiac Cycle Estimation[J]. Journal of Electronics & Information Technology, 2017, 39(11): 2677-2683. doi: 10.11999/JEIT170108

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Phonocardiogram Segmentation and Abnormal Phonocardiogram Screening Algorithm Based on Cardiac Cycle Estimation

doi: 10.11999/JEIT170108

1.
2.
(Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China)

Funds:

The National Natural Science Foundation of China (61302033), The Beijing Municipal Natural Science Foundation (Z160003), The National Key Research and Development Project (2016YFC1304302, 2016YFC0206502, 2016YFC1303900)

Received Date: 2017-02-10
Rev Recd Date: 2017-04-20
Publish Date: 2017-11-19

Abstract

Abstract

Heart disease is of highest morbidity and mortality. The cardiac structure and mechanical characteristics can be reflected by auscultation. Compared with echocardiography and nuclear magnetic resonance, auscultation gets the advantages of fast, low cost and easy to use. The composition of phonocardiogram is complex, and the auscultation is easy to be affected by the subjectivity of the doctor, various noise and disturbances, which limits the application of auscultation. The algorithm of phonocardiogram segmentation and abnormal phonocardiogram screening is presented. For the reason that the heart cycle is estimated in advance, 80% cardiac cycle can be recognition correctly when random disturbances exist. The diagnostic indexes of time and frequency domain with high discrimination are also presented, and the abnormal heart sounds are recognized by Support Vector Machine (SVM) with the accuracy about 92%. The algorithm can be used for assisting doctors or portable phonocardiogram monitoring device.
- Phonocardiogram segment,
- Abnormal PCG screening,
- Support Vector Machine (SVM)

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References(25)

References

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