{"title":"QT dispersion monitoring as a coronary disturbance prediction tool","authors":"R. Gonzalez, A. Rodriguez, R. Almeida","doi":"10.1109/CIC.2005.1588149","DOIUrl":null,"url":null,"abstract":"The goal of this paper is to discuss a method to study the QT interval dispersion continuously. This parameter is computed for each ten-second-signal strip studied. The relationship between the QT dispersion variations and the appearance of cardiac disturbances was analyzed. Forty fifteen-minute healthy ECG and five thirty-minute pathologic stress tests were studied. The QRS complexes were detected and classified as normal or premature according to simple rules, the QRS onset was detected using a nine-point derivative function and the T wave offset was identified with an algorithm that follows the shape of the ECG. The QT dispersion graphic was flat and the mean value was less than 60 ms for every healthy person. However, for each pathologic ECG the QT interval dispersion was over 74 ms before a pathological stage and the graphic was not flat in the minutes previous to the induced cardiac disturbances","PeriodicalId":239491,"journal":{"name":"Computers in Cardiology, 2005","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in Cardiology, 2005","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.2005.1588149","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
The goal of this paper is to discuss a method to study the QT interval dispersion continuously. This parameter is computed for each ten-second-signal strip studied. The relationship between the QT dispersion variations and the appearance of cardiac disturbances was analyzed. Forty fifteen-minute healthy ECG and five thirty-minute pathologic stress tests were studied. The QRS complexes were detected and classified as normal or premature according to simple rules, the QRS onset was detected using a nine-point derivative function and the T wave offset was identified with an algorithm that follows the shape of the ECG. The QT dispersion graphic was flat and the mean value was less than 60 ms for every healthy person. However, for each pathologic ECG the QT interval dispersion was over 74 ms before a pathological stage and the graphic was not flat in the minutes previous to the induced cardiac disturbances