{"title":"利用传递熵检测心电st段变化","authors":"I. Potapov, Esa Räsänen","doi":"10.22489/CinC.2018.085","DOIUrl":null,"url":null,"abstract":"Many severe heart dysfunctions cause changes in the ST-segment of ECG. We hypothesize that the change in ST affects the degree of coupling between the QT time intervals and the heart rate (HR, inverse of the inter-beat interval RR). Therefore, we analyze the informational transfer between the coupled dynamics of QT and RR to detect the ST segment variation. We use the transfer entropy method allowing for a quantitative and uni-directional measure of coupling between two temporal processes. We analyze the data from ST variation patients and normal individuals. We show that the RR-to-QT information transfer for the ST group is larger than the corresponding transfer for the normal group. This indicates a larger degree of uncertainty in QT dependence on RR. Moreover, on average the segments of ST-episodes have the associated RR-to-QT transfer larger than the non-ST episodes. Finally, we demonstrate that the ratio between intra- and inter-subject diversity of the QT-RR relationship can have a characteristic value for the segments of ST episodes. We conclude that the degree of inter-dependence between QT and RR can be a marker of the ST variation pathology.","PeriodicalId":215521,"journal":{"name":"2018 Computing in Cardiology Conference (CinC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detection of ST-Segment Variation in ECG Using Transfer Entropy\",\"authors\":\"I. Potapov, Esa Räsänen\",\"doi\":\"10.22489/CinC.2018.085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many severe heart dysfunctions cause changes in the ST-segment of ECG. We hypothesize that the change in ST affects the degree of coupling between the QT time intervals and the heart rate (HR, inverse of the inter-beat interval RR). Therefore, we analyze the informational transfer between the coupled dynamics of QT and RR to detect the ST segment variation. We use the transfer entropy method allowing for a quantitative and uni-directional measure of coupling between two temporal processes. We analyze the data from ST variation patients and normal individuals. We show that the RR-to-QT information transfer for the ST group is larger than the corresponding transfer for the normal group. This indicates a larger degree of uncertainty in QT dependence on RR. Moreover, on average the segments of ST-episodes have the associated RR-to-QT transfer larger than the non-ST episodes. Finally, we demonstrate that the ratio between intra- and inter-subject diversity of the QT-RR relationship can have a characteristic value for the segments of ST episodes. We conclude that the degree of inter-dependence between QT and RR can be a marker of the ST variation pathology.\",\"PeriodicalId\":215521,\"journal\":{\"name\":\"2018 Computing in Cardiology Conference (CinC)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Computing in Cardiology Conference (CinC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22489/CinC.2018.085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Computing in Cardiology Conference (CinC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22489/CinC.2018.085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of ST-Segment Variation in ECG Using Transfer Entropy
Many severe heart dysfunctions cause changes in the ST-segment of ECG. We hypothesize that the change in ST affects the degree of coupling between the QT time intervals and the heart rate (HR, inverse of the inter-beat interval RR). Therefore, we analyze the informational transfer between the coupled dynamics of QT and RR to detect the ST segment variation. We use the transfer entropy method allowing for a quantitative and uni-directional measure of coupling between two temporal processes. We analyze the data from ST variation patients and normal individuals. We show that the RR-to-QT information transfer for the ST group is larger than the corresponding transfer for the normal group. This indicates a larger degree of uncertainty in QT dependence on RR. Moreover, on average the segments of ST-episodes have the associated RR-to-QT transfer larger than the non-ST episodes. Finally, we demonstrate that the ratio between intra- and inter-subject diversity of the QT-RR relationship can have a characteristic value for the segments of ST episodes. We conclude that the degree of inter-dependence between QT and RR can be a marker of the ST variation pathology.