A wavelet-transform-based search algorithm using signal energy in different scales successfully isolated baseline wander from ECG signals in the MIT/BIH database.
A novel wavelet packet algorithm effectively eliminates baseline drift in ECG signals, which may improve the accurate diagnosis of ischemia and arrhythmias.
Baseline wander elimination is considered a classical problem. In electrocardiography (ECG) signals, baseline drift can influence the accurate diagnosis of heart disease such as ischemia and arrhythmia. We present a wavelet-transform- (WT-) based search algorithm using the energy of the signal in different scales to isolate baseline wander from the ECG signal. The algorithm computes wavelet packet coefficients and then in each scale the energy of the signal is calculated. Comparison is made and the branch of the wavelet binary tree corresponding to higher energy wavelet spaces is chosen. This algorithm is tested using the data record from MIT/BIH database and excellent results are obtained.
Tinati et al. (2006) studied Baseline drift in electrocardiography (ECG) signals. Wavelet-transform-based search algorithm was evaluated on Baseline wander elimination. A wavelet-transform-based search algorithm using signal energy in different scales successfully isolated baseline wander from ECG signals in the MIT/BIH database.