P- and T-wave Delineation in ECG Signals using Support Vector Machine

Abstract

Detection and delineation of QRS-complexes, P and T-waves, are important issues in the analysis and interpretation of Electrocardiogram (ECG) signals. In this paper, a classifier motivated from statistical learning theory, i.e., Support Vector Machine (SVM), has been explored for detection and delineation of these wave components. Digital filtering techniques are used to remove interference present in ECG signal. The feature extraction is done using a modified definition of slope of the ECG signals. The performance of the proposed algorithm is validated using ECG recordings from dataset-3 of the CSE multi-lead measurement library. The results in terms of accuracy, i.e., 94.4%, obtained clearly indicate a high degree of agreement with the manual annotations made by the referees of CSE dataset-3.

Keywords:

• Classifier
• Fiducial points
• Gradient
• P and T waves
• QRS-complex
• Support vector machine

Additional information

Notes on contributors

Indu Saini

Indu Saini was born in Ferozepur, India, in 1971. She received her B.Tech degree in Electronics and Communication Engineering from Guru Nanak Dev University, India in 1994 and then obtained her M. Tech (by Research) degree in Electronics and Communication Engineering from National Institute of Technology Jalandhar. Presently, she is pursuing her Ph.D. in the area of Biomedical Signal Processing from Dr B R Ambedkar National Institute of Technology Jalandhar, where she is also serving as Assistant Professor in Electronics and Communication Engineering Department since 2002. E-mail: [email protected]

Dilbag Singh

Dilbag Singh was born in Adyana (Panipat), on February 26, 1969. He received the Ph.D. degree in Engineering from the Indian Institute of Technology Roorkee 2004. The Ph.D. thesis was developed at the Instrumentation and Signal Processing Laboratory of the Electrical Engineering Department under the direction of Vinod Kumar, S. C. Saxena and K. K. Deepak (AIIMS). After a brief stint at Goodyear India Limited, Faridabad, in September 1994, he joined the Department of Instrumentation and Control Engineering at of the Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, and since 2005 has been an Associate Professor of Instrumentation and Control Engineering there, where he is teaching UG/PG courses related to biomedical signal processing and instrumentation. His professional research interests are in signal processing, in particular applied to biomedical applications. E-mail: [email protected]

Arun Khosla

Arun Khosla received his PhD degree from Indraprastha University, Delhi in the field of Information Technology. He is presently working as Associate Professor in the Department of Electronics and Communication Engineering, National Institute of Technology, Jalandhar. India. His areas of interest are fuzzy modeling, biologically inspired computing and high-performance computing and their applications to engineering and business. He is a reviewer for various IEEE and other National and International conferences and journals. He also serves on the editorial board of International Journal of Swarm Intelligence Research. He has conducted a number of tutorials in the domain of soft computing at various national and international conferences. E-mail: [email protected]