{"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}
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.