title: QRS detection using new wavelets.
abstract: This paper deals with a new wavelet (WVT) which has been developed and very effectively and efficiently used for the detection of QRS segments from the ECG signal. After carrying out the detection using five existing wavelets (two symmetric--WT1 and WT2--and three asymmetric--WT3, WT4 and WT5), two new wavelets (WT6 and WT7) were constructed and used for QRS detection. WT6 is a symmetric wavelet and has been constructed by a trial-and-error method. WT7 is an adaptive symmetric wavelet and adjusts its threshold as per the amplitude of the ECG signal. The accuracy of QRS detection obtained from WT6 is 99.8 % and from WT7 100%. The CSE DS-3 database has been used for tests. Both WT6 and WT7 have been proved to be superior in performance to the existing wavelets. Out of WT6 and WT7, WT7 holds high promise for error-free reliable QRS detection in computer-aided feature extraction and disease diagnostics.
authors.affiliation: Electrical Engineering Department, University of Roorkee, UA, India.
authors.forename: S C
authors.initials: SC
authors.lastname: Saxena
authors.forename: V
authors.initials: V
authors.lastname: Kumar
authors.forename: S T
authors.initials: ST
authors.lastname: Hamde
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D004562:Electrocardiography / Q000379:methods* / Q000706:statistics & numerical data*; D006801:Humans; D008955:Models, Cardiovascular; D015233:Models, Statistical; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes