The utility of wavelet packet transform in QRS complex detection - a comparative study of different mother wavelets

The Electrocardiogram (ECG) describes the electrical activity of the heart and is an important tool to study the functioning of heart. The QRS Complex is the most important characteristic in ECG signal. The correct detection of QRS complex in ECG signal is extremely important for its further processing with regard to cardiac health monitoring and for heart rate variability (HRV) studies. This paper presents a QRS complex detection algorithm for ECG signals using wavelet packet transform (WPT). The proposed beat detection algorithm was tested on different data records of Fantasia database and self recorded signals. Five wavelet families, namely, Daubichies, Coiflets, Symlets, Biorthogonal and reverse Biorthogonal for which DWT is possible are considered in wavelet packet decomposition structure. As shown in the simulation results, the db2 and db3 wavelets give the optimum results. The algorithm achieved a sensitivity of Se = 99.99% and positive predictivity of +P = 99.92% using db2 and Se= 99.96%, +P = 99.92% using db3.