Biomedical signal processing using SVM

This paper presents a novel approach for biomedical signal processing using support vector machine (SVM). Bioelectrical signals express the electrical functionality of different organs in the human body. The electrocardiogram, also called ECG signal, is one important signal among all bioelectrical signals. ECG is characterized by a recurrent wave sequence of P, QRS and T- wave associated with each beat. The automatic detection of ECG waves is important to cardiac disease diagnosis. SVM is used as a classifier for the automatic detection of ECG waves. The performance of the algorithm is evaluated using original simultaneously recorded 12-lead ECG recordings from the standard CSE ECG database. Significant detection rate is achieved.