{"title":"一种后处理算法的发展,以区分由植入式心律转复除颤器检测到的室性心动过速","authors":"B. Gunderson, A.S. Patel, M.L. Brown, C. Swerdlow","doi":"10.1109/CIC.2007.4745606","DOIUrl":null,"url":null,"abstract":"Implantable Cardioverter-Defibrillators (ICD) detect ventricular tachycardia /fibrillation (VT/VF) using atrial (A) and ventricular (V) electrograms (EGMs). ICD algorithms discriminate VT/VF from supraventricular tachycardias (SVTs), but misclassify some SVTs as VT/VF. Clinicians review detected episodes to identify true SVT episodes and guide appropriate clinical action. A post-processing, expert-system algorithm was developed to classify tachyarrhythmias detected and stored in ICD memory. The algorithm was designed to diagnose rhythms with V EGM and/or timing of A/ V events. Rhythms that did not fulfill the criteria were classified as Unknown. The algorithm was tested using a dataset of 469 episodes. The algorithm correctly classified 80% of the episodes with 99% accuracy. This accuracy may be sufficient that physician review may be required only for Unknown episodes.","PeriodicalId":406683,"journal":{"name":"2007 Computers in Cardiology","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Development of a post-processing algorithm to classify rhythms detected as ventricular tachyarrhythmias by Implantable Cardioverter Defibrillators\",\"authors\":\"B. Gunderson, A.S. Patel, M.L. Brown, C. Swerdlow\",\"doi\":\"10.1109/CIC.2007.4745606\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Implantable Cardioverter-Defibrillators (ICD) detect ventricular tachycardia /fibrillation (VT/VF) using atrial (A) and ventricular (V) electrograms (EGMs). ICD algorithms discriminate VT/VF from supraventricular tachycardias (SVTs), but misclassify some SVTs as VT/VF. Clinicians review detected episodes to identify true SVT episodes and guide appropriate clinical action. A post-processing, expert-system algorithm was developed to classify tachyarrhythmias detected and stored in ICD memory. The algorithm was designed to diagnose rhythms with V EGM and/or timing of A/ V events. Rhythms that did not fulfill the criteria were classified as Unknown. The algorithm was tested using a dataset of 469 episodes. The algorithm correctly classified 80% of the episodes with 99% accuracy. This accuracy may be sufficient that physician review may be required only for Unknown episodes.\",\"PeriodicalId\":406683,\"journal\":{\"name\":\"2007 Computers in Cardiology\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 Computers in Cardiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIC.2007.4745606\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 Computers in Cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.2007.4745606","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of a post-processing algorithm to classify rhythms detected as ventricular tachyarrhythmias by Implantable Cardioverter Defibrillators
Implantable Cardioverter-Defibrillators (ICD) detect ventricular tachycardia /fibrillation (VT/VF) using atrial (A) and ventricular (V) electrograms (EGMs). ICD algorithms discriminate VT/VF from supraventricular tachycardias (SVTs), but misclassify some SVTs as VT/VF. Clinicians review detected episodes to identify true SVT episodes and guide appropriate clinical action. A post-processing, expert-system algorithm was developed to classify tachyarrhythmias detected and stored in ICD memory. The algorithm was designed to diagnose rhythms with V EGM and/or timing of A/ V events. Rhythms that did not fulfill the criteria were classified as Unknown. The algorithm was tested using a dataset of 469 episodes. The algorithm correctly classified 80% of the episodes with 99% accuracy. This accuracy may be sufficient that physician review may be required only for Unknown episodes.