A wavelet transform-based algorithm achieves >99.8% accuracy in detecting QRS complexes and effectively identifies P and T waves in ECG signals, even in the presence of noise and baseline drift.
An algorithm based on wavelet transforms (WT's) has been developed for detecting ECG characteristic points. With the multiscale feature of WT's, the QRS complex can be distinguished from high P or T waves, noise, baseline drift, and artifacts. The relation between the characteristic points of ECG signal and those of modulus maximum pairs of its WT's is illustrated. By using this method, the detection rate of QRS complexes is above 99.8% for the MIT/BIH database and the P and T waves can also be detected, even with serious baseline drift and noise.
Li et al. (Sun,) studied this question.