Cancellation of Powerline Interference from Biomedical Signals Using an Improved Affine Projection Algorithm

Abstract

Powerline contamination of recorded signals represents a major source of noise in electrophysiology and impairs the use of recordings for research. Furthermore it degrades the signal quality and overwhelms tiny features that may be critical for clinical monitoring and diagnosis. During last years, notch filters and adaptive cancellers have been suggested to suppress this interference. In this article we present an improved adaptive canceller for the reduction of the fundamental powerline interference component and harmonics in electrocardiogram (ECG) and electrocardiograph (EEG) recordings. In this new ECG and EEG denoising approach is used an affine projection (AP) algorithm based on Gauss---Seidel method. The results show that the proposed method is able to reduce powerline interference from the noisy ECG and EEG signals more accurately and consistently in comparison to some of the state of-the-art methods. Furthermore, AP can be efficiently used with very low signal-to-noise ratios, while preserving original signal waveform.