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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Computer Methods and...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Computer Methods and Programs in Biomedicine
Article . 2010 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2010
Data sources: DBLP
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The moment segmentation analysis of heart sound pattern

Authors: Zhonghong Yan; Zhongwei Jiang; Ayaho Miyamoto; Yunlong Wei;

The moment segmentation analysis of heart sound pattern

Abstract

This paper presents two new ideas. The first one is to apply the Viola integral waveform method to analyze the heart sounds recorded by an electric stethoscope, and the multi-scale moment analysis is proposed to locate each cycle of heart sounds. A fast algorithm for calculating characteristic waveform (CW) and characteristic moment waveform (CMW) of heart sound can be expressed by the Viola integral method, and their calculation time has nothing to do with their scales. The second idea is easier to segment the heart sound based on its approximate cyclical characteristic than the ordinary methods. Each heart sound cycle can be quickly found by CMW's Local Extreme Points (LEPs). Based on the information of LEPs and CW, a high accurate search algorithm to segment S1 and S2 sounds is submitted. By numerical experiments, the important parameters of time scale delta=0.05s for CW and l=0.45s for CMW are obtained and validated for segmentation of heart sound.More exact segmentation boundaries of the heart sound signal could be located fast in an automated way, and a further performance analysis is presented. Owing to the use of the rhythm of CMW curves, the proposed method not only gives a higher success segmentation rate, but also it is actually simpler and faster than the wavelet method.

Related Organizations
Keywords

Heart Sounds, Fourier Analysis, Artificial Intelligence, Phonocardiography, Humans, Signal Processing, Computer-Assisted, Algorithms

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
60
Top 10%
Top 10%
Top 10%
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