基于WB-MFA分形分解的心音信号精确分割

K. Hakkoum, L. Cherif
{"title":"基于WB-MFA分形分解的心音信号精确分割","authors":"K. Hakkoum, L. Cherif","doi":"10.59287/icpis.800","DOIUrl":null,"url":null,"abstract":"This work describes a unique method for segmenting phonocardiogram (PCG) signals inMATLAB 2022 utilizing fractal decomposition. Fractal decomposition is an effective technique forbreaking down a PCG signal into simpler components based on their fractal features. The suggested methodfor fractal decomposition employs the wavelet-based multifractal analysis (WB-MFA) method, which hasalready been proved to be successful for PCG segmentation. The proposed method was tested on a datasetof PCG signals and found to be highly accurate in segmenting the signals into separate heart sounds.","PeriodicalId":292916,"journal":{"name":"International Conference on Pioneer and Innovative Studies","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accurate Segmentation of Phonocardiogram Signals using Fractal Decomposition with WB-MFA in MATLAB 2022\",\"authors\":\"K. Hakkoum, L. Cherif\",\"doi\":\"10.59287/icpis.800\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work describes a unique method for segmenting phonocardiogram (PCG) signals inMATLAB 2022 utilizing fractal decomposition. Fractal decomposition is an effective technique forbreaking down a PCG signal into simpler components based on their fractal features. The suggested methodfor fractal decomposition employs the wavelet-based multifractal analysis (WB-MFA) method, which hasalready been proved to be successful for PCG segmentation. The proposed method was tested on a datasetof PCG signals and found to be highly accurate in segmenting the signals into separate heart sounds.\",\"PeriodicalId\":292916,\"journal\":{\"name\":\"International Conference on Pioneer and Innovative Studies\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Pioneer and Innovative Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.59287/icpis.800\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Pioneer and Innovative Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59287/icpis.800","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

这项工作描述了一种在matlab 2022中利用分形分解分割心音图(PCG)信号的独特方法。分形分解是一种基于分形特征将PCG信号分解成更简单分量的有效方法。本文提出的分形分解方法采用基于小波的多重分形分析(WB-MFA)方法,该方法已被证明是成功的PCG分割方法。在心电信号数据集上进行了测试,发现该方法在分割心音信号方面具有很高的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accurate Segmentation of Phonocardiogram Signals using Fractal Decomposition with WB-MFA in MATLAB 2022
This work describes a unique method for segmenting phonocardiogram (PCG) signals inMATLAB 2022 utilizing fractal decomposition. Fractal decomposition is an effective technique forbreaking down a PCG signal into simpler components based on their fractal features. The suggested methodfor fractal decomposition employs the wavelet-based multifractal analysis (WB-MFA) method, which hasalready been proved to be successful for PCG segmentation. The proposed method was tested on a datasetof PCG signals and found to be highly accurate in segmenting the signals into separate heart sounds.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信