{"title":"心内心电图的神经网络分类","authors":"S. Farrugia, H. Yee, P. Nickolls","doi":"10.1109/IJCNN.1991.170573","DOIUrl":null,"url":null,"abstract":"An artificial neural network has been tested for the classification of cardiac rhythms from intracardiac electrocardiograms (ECGs). It uses as inputs a small number of waveform samples and extracted parameters. The network has been found to perform better than a rate-based scheme similar to those used in commercially available implantable cardioverter-defibrillators in its ability to distinguish normal rhythms from arrhythmias. It shows, in addition, a certain ability to discriminate between a larger number of rhythms: in particular, between sinus tachycardia and slow ventricular tachycardia and between slow and fast ventricular tachycardias.<<ETX>>","PeriodicalId":211135,"journal":{"name":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1991-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Neural network classification of intracardiac ECG's\",\"authors\":\"S. Farrugia, H. Yee, P. Nickolls\",\"doi\":\"10.1109/IJCNN.1991.170573\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An artificial neural network has been tested for the classification of cardiac rhythms from intracardiac electrocardiograms (ECGs). It uses as inputs a small number of waveform samples and extracted parameters. The network has been found to perform better than a rate-based scheme similar to those used in commercially available implantable cardioverter-defibrillators in its ability to distinguish normal rhythms from arrhythmias. It shows, in addition, a certain ability to discriminate between a larger number of rhythms: in particular, between sinus tachycardia and slow ventricular tachycardia and between slow and fast ventricular tachycardias.<<ETX>>\",\"PeriodicalId\":211135,\"journal\":{\"name\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.1991.170573\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1991.170573","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neural network classification of intracardiac ECG's
An artificial neural network has been tested for the classification of cardiac rhythms from intracardiac electrocardiograms (ECGs). It uses as inputs a small number of waveform samples and extracted parameters. The network has been found to perform better than a rate-based scheme similar to those used in commercially available implantable cardioverter-defibrillators in its ability to distinguish normal rhythms from arrhythmias. It shows, in addition, a certain ability to discriminate between a larger number of rhythms: in particular, between sinus tachycardia and slow ventricular tachycardia and between slow and fast ventricular tachycardias.<>