Application of support vector machine for the detection of P- and T-waves in 12-lead electrocardiogram.
Electrocardiogram (ECG) is characterized by a recurrent wave sequence of P, QRS and T-wave associated with each beat. The performance of the computer-aided ECG analysis systems depends heavily upon the accurate and reliable detection of these component waves. This paper presents an efficient method for the detection of P- and T-waves in 12-lead ECG using support vector machine (SVM). Digital filtering techniques are used to remove power line interference and base line wander. SVM is used as a classifier for the detection of P- and T-waves. The algorithm is validated using original simultaneously recorded 12-lead ECG recordings from the standard CSE ECG database. Significant detection rate of 95.43% is achieved for P-wave detection and 96.89% for T-wave detection. The method successfully detects all kind of morphologies of P- and T-waves. The on-sets and off-sets of the detected P- and T-waves are found to be within the tolerance limits given in CSE library.
Department of Electrical Engineering, J. N. Vyas University, MBM Engineering College, Jodhpur 342001, Rajasthan, India. ssmehta_58@rediffmail.com
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D000465:Algorithms; D001185:Artificial Intelligence; D001699:Biometry; D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted; D004562:Electrocardiography / Q000706:statistics & numerical data*; D006801:Humans; D012815:Signal Processing, Computer-Assisted