title: Combined entropy based method for detection of QRS complexes in 12-lead electrocardiogram using SVM.
abstract: A method based on signal entropy is proposed for the detection of QRS complexes in the 12-lead electrocardiogram (ECG) using support vector machine (SVM). Digital filtering techniques are used to remove power line interference and base line wander in the ECG signal. Combined Entropy criterion was used to enhance the QRS complexes. SVM is used as a classifier to delineate QRS and non-QRS regions. The performance of the proposed algorithm was tested using 12-lead real ECG recordings from the standard CSE ECG database. The numerical results indicated that the algorithm achieved 99.93% of detection rate. The percentage of false positive and false negative is 0.54% and 0.06%, respectively. The proposed algorithm performs better as compared with published results of other QRS detectors tested on the same database.
authors: Department of Electrical Engineering, J.N. Vyas University, MBM Engineering College, Jodhpur 342001, Rajasthan, India. ssmetha_58@rediffmail.com
authors: S S
authors: SS
authors: Mehta
authors: N S
authors: NS
authors: Lingayat
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004562:Electrocardiography / Q000145:classification / Q000379:methods*; D005188:False Negative Reactions; D005189:False Positive Reactions; D006331:Heart Diseases / Q000175:diagnosis / Q000503:physiopathology; D006801:Humans; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted