Removal of Embedded Artefacts in ECG Signals by Independent Component Analysis

Routinely recorded Electrocardiograms (ECGs) are often corrupted by artefacts; these artefacts make the visual interpretation and analysis of the ECG signal difficult. This paper presents a model, dynamic in structure, sufficiently suitable for removing the ECG artefacts caused by embedded objects in the body using independent component analysis technique. By simulation, the model is able to detect and remove extraneous noises in the conductive paths and discern essential nodes of ECG that are useful to clinicians. Our study, also demonstrates that convolutive ICA can be regarded as a useful tool for accurately estimating the effects of embedded object in the patients on ECG signals.