G. Mijatović, Chiara Barà, T. Lončar-Turukalo, L. Faes
{"title":"A method to Quantify Memory Utilization of Heartbeat Dynamics in Continuous Time","authors":"G. Mijatović, Chiara Barà, T. Lončar-Turukalo, L. Faes","doi":"10.1109/ESGCO55423.2022.9931391","DOIUrl":null,"url":null,"abstract":"We present an approach to quantify the predictive capacity of point processes analyzed in continuous time. An index of the so-called memory utilization rate (MUR) is defined as a model-free measure of the amount of predictive information stored in a point process. A strategy for the data-efficient, model-free estimation of MUR is proposed and validated in simulations of independent and history-dependent heartbeat intervals. Our results document the ability of the proposed MUR estimator to detect the absence and quantify the extent of predictable information in heart rate variability signals.","PeriodicalId":199691,"journal":{"name":"2022 12th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 12th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESGCO55423.2022.9931391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We present an approach to quantify the predictive capacity of point processes analyzed in continuous time. An index of the so-called memory utilization rate (MUR) is defined as a model-free measure of the amount of predictive information stored in a point process. A strategy for the data-efficient, model-free estimation of MUR is proposed and validated in simulations of independent and history-dependent heartbeat intervals. Our results document the ability of the proposed MUR estimator to detect the absence and quantify the extent of predictable information in heart rate variability signals.