L. Senhadji, Feng Wang, Alfredo I. Hernández, Guy Carrault
{"title":"Wavelets extrema representation for QRS-T cancellation and P wave detection","authors":"L. Senhadji, Feng Wang, Alfredo I. Hernández, Guy Carrault","doi":"10.1109/CIC.2002.1166701","DOIUrl":null,"url":null,"abstract":"P wave detection requires a robust QRS-T cancellation method. Interesting algorithms have been proposed for beat-to-beat QRS-T cancellation. Previous studies have shown that adaptive methods lead to good cancellation of the QRS-T interval which generally guarantees the performance of P wave detection. However, adaptive methods suffer from the nonstationary behavior of ECG signals and particularly beat-to-beat morphology changes of the QRS. We present a new approach for two ECG channel QRS-T cancellation based on the dyadic wavelet transform. The method is insensitive to QRS morphology changes and performs well in the presence of ectopic beats, transient artifacts, baseline drifts and isolated P waves. Our approach allows the P wave to be enhanced better than methods recently proposed.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"37-40"},"PeriodicalIF":0.0000,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166701","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.2002.1166701","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25
Abstract
P wave detection requires a robust QRS-T cancellation method. Interesting algorithms have been proposed for beat-to-beat QRS-T cancellation. Previous studies have shown that adaptive methods lead to good cancellation of the QRS-T interval which generally guarantees the performance of P wave detection. However, adaptive methods suffer from the nonstationary behavior of ECG signals and particularly beat-to-beat morphology changes of the QRS. We present a new approach for two ECG channel QRS-T cancellation based on the dyadic wavelet transform. The method is insensitive to QRS morphology changes and performs well in the presence of ectopic beats, transient artifacts, baseline drifts and isolated P waves. Our approach allows the P wave to be enhanced better than methods recently proposed.