Approximation of ECG Signals Using Chebyshev Nodes and Lagrange-interpolation

Abstract

An ECG (Electrocardiography) is a graphical representation of electrical behavior of heart and is measured by placing electrodes on specific locations of limbs and chest. The characteristics of these signals change during acquisition and transmission due to addition of noises of variable frequency and amplitude. These noises need to be removed for better clinical evaluation. In this paper, ECG signals of MIT-BIH database have been approximated through a series of steps, i.e., denoising using total variation, segmentation using Bottom Up approach and finally utilizing Chebyshev nodes for Lagrange interpolation method. This paper also explores the concept and the benefit of second difference total variation over the first difference. The performance of the method is analyzed in terms of mean absolute deviation, root mean square deviation, percentage root mean square difference error, signal to noise ratio and cross correlation. The results obtained are found to be better than exiting techniques.