{"title":"局部Hölder基于规则的RR区间建模","authors":"J. L. Véhel, O. Barrière","doi":"10.1109/CBMS.2008.65","DOIUrl":null,"url":null,"abstract":"We analyze the local regularity of RR traces from ECG through the computation of the so-called Holder exponents. These exponents are at the basis of multifractal analysis, which has been shown to be relevant in the study of RR data. While multifractal analysis yields a global picture of the (statistical) distribution of regularity, we focus here on its time evolution. We show that this evolution is strongly correlated with the signal itself, a feature that seems to have remained unnoticed so far. We use this fact to build realistic synthetic RR traces.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"699 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Local Hölder Regularity-Based Modeling of RR Intervals\",\"authors\":\"J. L. Véhel, O. Barrière\",\"doi\":\"10.1109/CBMS.2008.65\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We analyze the local regularity of RR traces from ECG through the computation of the so-called Holder exponents. These exponents are at the basis of multifractal analysis, which has been shown to be relevant in the study of RR data. While multifractal analysis yields a global picture of the (statistical) distribution of regularity, we focus here on its time evolution. We show that this evolution is strongly correlated with the signal itself, a feature that seems to have remained unnoticed so far. We use this fact to build realistic synthetic RR traces.\",\"PeriodicalId\":377855,\"journal\":{\"name\":\"2008 21st IEEE International Symposium on Computer-Based Medical Systems\",\"volume\":\"699 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 21st IEEE International Symposium on Computer-Based Medical Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMS.2008.65\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2008.65","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Local Hölder Regularity-Based Modeling of RR Intervals
We analyze the local regularity of RR traces from ECG through the computation of the so-called Holder exponents. These exponents are at the basis of multifractal analysis, which has been shown to be relevant in the study of RR data. While multifractal analysis yields a global picture of the (statistical) distribution of regularity, we focus here on its time evolution. We show that this evolution is strongly correlated with the signal itself, a feature that seems to have remained unnoticed so far. We use this fact to build realistic synthetic RR traces.