Trend removal of ecg signal with LMS algoritm

In this study, the LMS algorithm was applied to detect and track baseline introduced by involuntary movements during the acquisition of electrocardiogram signals, skin mismatch with electrode, or any movement caused by breathing or breathing of the patient (baseline wander). The baseline wander was removed from the signal and corrected. For this purpose, the baseline signal was described using two models: a varying constant and a line with a varying slope and constant. The latter is not found in the literature and is the contribution of this study. A fixed length window moved along the signal and the model parameters corresponding to the each segment were computed. The constant directly provided the baseline and the end of line of each window plotted the baseline wander. The results were reported by applying this approach to a simulated electrocardiogram signal and a real signal received from MIH-BIH database records. The outcome shows that modelling signal segment with a line adopts to the baseline faster than the constant model.