{"title":"利用李亚普诺夫指数分析微伏t波交流电","authors":"Roozbeh Rajabi, H. Ghassemian","doi":"10.1109/ISIEA.2009.5356488","DOIUrl":null,"url":null,"abstract":"T-wave alternans (TWA) is a marker of cardiac instability and high risk of sudden cardiac death. In this paper we propose a new approach for the TWA detection. For this purpose Lyapunov spectrum was calculated from T-wave time series. To evaluate the detector performance, simulated T-waves based on the real ECG signals were used. Detected and simulated episodes were compared, in terms of sensitivity and positive predictivity. The results show that this method can reliably detect T-wave alternans episodes.","PeriodicalId":6447,"journal":{"name":"2009 IEEE Symposium on Industrial Electronics & Applications","volume":"11 1","pages":"156-159"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Microvolt T-wave alternans analysis using Lyapunov exponents\",\"authors\":\"Roozbeh Rajabi, H. Ghassemian\",\"doi\":\"10.1109/ISIEA.2009.5356488\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"T-wave alternans (TWA) is a marker of cardiac instability and high risk of sudden cardiac death. In this paper we propose a new approach for the TWA detection. For this purpose Lyapunov spectrum was calculated from T-wave time series. To evaluate the detector performance, simulated T-waves based on the real ECG signals were used. Detected and simulated episodes were compared, in terms of sensitivity and positive predictivity. The results show that this method can reliably detect T-wave alternans episodes.\",\"PeriodicalId\":6447,\"journal\":{\"name\":\"2009 IEEE Symposium on Industrial Electronics & Applications\",\"volume\":\"11 1\",\"pages\":\"156-159\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Symposium on Industrial Electronics & Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIEA.2009.5356488\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Symposium on Industrial Electronics & Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIEA.2009.5356488","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Microvolt T-wave alternans analysis using Lyapunov exponents
T-wave alternans (TWA) is a marker of cardiac instability and high risk of sudden cardiac death. In this paper we propose a new approach for the TWA detection. For this purpose Lyapunov spectrum was calculated from T-wave time series. To evaluate the detector performance, simulated T-waves based on the real ECG signals were used. Detected and simulated episodes were compared, in terms of sensitivity and positive predictivity. The results show that this method can reliably detect T-wave alternans episodes.