{"title":"筛选阵发性心房颤动使用心房早搏和频谱措施","authors":"Brian Hickey, Conor Heneghan","doi":"10.1109/CIC.2002.1166746","DOIUrl":null,"url":null,"abstract":"We present a technique for screening for imminent onset of paroxysmal atrial fibrillation (PAF) through automated assessment of 30-minute segments of electrocardiogram (ECG), which do not contain any episodes of atrial fibrillation. Algorithmic development was carried out using a training database of 75 half-hour records drawn from two subject groups. Subjects in the first group provided segments with PAF in the five minutes after the 30-minute recording; the second group do not have PAF (control subjects or subjects with non-PAF cardiac pathology). To differentiate between pre-PAF segments and non-PAF segments a linear discriminant classifier was developed, using the number of Atrial Premature Contractions (APCs) and two spectral measures as features. An independent test set of 72 recordings (28 pre-PAF and 44 non-PAF) was then classified, with an accuracy of 75% (sensitivity 79%, specificity 72%). When tested against a second database of subjects with no known cardiac pathology, the specificity rose to 95%.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"217-220"},"PeriodicalIF":0.0000,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166746","citationCount":"24","resultStr":"{\"title\":\"Screening for paroxysmal atrial fibrillation using atrial premature contractions and spectral measures\",\"authors\":\"Brian Hickey, Conor Heneghan\",\"doi\":\"10.1109/CIC.2002.1166746\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a technique for screening for imminent onset of paroxysmal atrial fibrillation (PAF) through automated assessment of 30-minute segments of electrocardiogram (ECG), which do not contain any episodes of atrial fibrillation. Algorithmic development was carried out using a training database of 75 half-hour records drawn from two subject groups. Subjects in the first group provided segments with PAF in the five minutes after the 30-minute recording; the second group do not have PAF (control subjects or subjects with non-PAF cardiac pathology). To differentiate between pre-PAF segments and non-PAF segments a linear discriminant classifier was developed, using the number of Atrial Premature Contractions (APCs) and two spectral measures as features. An independent test set of 72 recordings (28 pre-PAF and 44 non-PAF) was then classified, with an accuracy of 75% (sensitivity 79%, specificity 72%). When tested against a second database of subjects with no known cardiac pathology, the specificity rose to 95%.\",\"PeriodicalId\":80984,\"journal\":{\"name\":\"Computers in cardiology\",\"volume\":\"1 1\",\"pages\":\"217-220\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/CIC.2002.1166746\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in cardiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIC.2002.1166746\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.2002.1166746","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Screening for paroxysmal atrial fibrillation using atrial premature contractions and spectral measures
We present a technique for screening for imminent onset of paroxysmal atrial fibrillation (PAF) through automated assessment of 30-minute segments of electrocardiogram (ECG), which do not contain any episodes of atrial fibrillation. Algorithmic development was carried out using a training database of 75 half-hour records drawn from two subject groups. Subjects in the first group provided segments with PAF in the five minutes after the 30-minute recording; the second group do not have PAF (control subjects or subjects with non-PAF cardiac pathology). To differentiate between pre-PAF segments and non-PAF segments a linear discriminant classifier was developed, using the number of Atrial Premature Contractions (APCs) and two spectral measures as features. An independent test set of 72 recordings (28 pre-PAF and 44 non-PAF) was then classified, with an accuracy of 75% (sensitivity 79%, specificity 72%). When tested against a second database of subjects with no known cardiac pathology, the specificity rose to 95%.