%A Van Manh Hoang
%A Anh Viet Dang
%A Hong Quan Dang
%A Manh Thang Pham
%T Automated the QRS complex detection for monitoring the electrical activity of the heart
%X In this work, we present a novel QRS complex detection approach in noisy exercise ECG signals
based on a continuous wavelet transform (CWT) for a single-lead ECG signal. First, the adaptive filtering
algorithm is employed to remove the additive artifacts from the signals. The ECG signals are then
transformed by a CWT at a suitable scale. Finally, the QRS complex is detected in processed signals. The
performance of the proposed algorithm is evaluated on the MIT-BIH Noise Stress Test Database. The
recordings in this dataset are specially selected and characterized by baseline wander, muscle artifacts,
and electrode motion artifacts as noise sources. Obtained results show that the proposed method reached
the most satisfactory performance compared with several other QRS complex detection algorithms.
%D 2019
%L SisLab3864