A new approach for removal of baseline wande in ECG signal using Empirical Mode Decomposition & Hurst Exponent

Abstract

In this paper, a new method for removal of baseline wander from ECG signals is proposed. This method uses the algorithm of Empirical Mode Decomposition (EMD) with Hurst Exponent selection. The hurst exponent is used to select those Intrinsic Mode Functions (IMF's), obtained on applying EMD on the signal, which are least corrupted by baseline wander. Using those selected IMF's, the original noisy signal is reconstructed which is free from baseline wander. The algorithm was applied to 10 ECG signals obtained from MIT-BIH Arrhythmia Database. The simulation results show that the new method EMDH removes the noise better as compared to the other methods. On an average, −7.734 dB of the noise power was removed by application of EMDH as compared to −10.089 dB & −9.883 dB by application of EMD and Ensemble Empirical Mode Decomposition (EEMD) respectively.