Realtime ECG baseline removal: An isoelectric point estimation approach

This paper presents a novel method for ECG baseline drift removal while preserving the integrity of the ST segment. Baseline estimation is achieved by tracking 3 isoelectric points within the ECG waveform as fiducial markers used in an interpolation filter. These points are determined relative to the QRS complex, which is extracted using a known method (Pan-Tompkins algorithm). The proposed algorithm has been tested extensively using synthetic signals and also validated with real data. The synthetic signals assume a 2mV p-p ECG signal and 300 µV p-p baseline drift in the presence of noise artefacts including EMG pickup (20 dB - max. 200 µV), and residual power-line interference (50 µV p-p). The results show a maximum (worst-case ST-segment distortion) error of 34.7 µV (mean), 27.8 µV (median) and 21.2 µV (std. dev.) across 50 randomly generated synthetic ECG signals each containing 100 heartbeats. Validation of the algorithm applied to signals from the MIT-BIH arrhythmia databases reveals maximum error per P-T interval with mean, median and std. dev. of 34.4 µV, 35.2 µV and 9.6 µV respectively with suppressed motion artefacts.