A novel method of preprocessing and modeling ECG signals with Lagrange–Chebyshev interpolating polynomials

An electrocardiogram (ECG) records electrical potential of the heart and its morphology changes due to the addition of various types of noises during recording which consequently affects accurate analysis and clinical evaluation. Also, due to generation of enormous volume of digital data by ECG monitoring devices, efficient techniques for ECG approximation are necessary for proper data accumulation and transmission, and improved functionality of ECG recorders. Here, we propose a polynomial approximation model which initially enhances the signal quality using total variation optimization; characterizes the enhanced signal through bottom-up method and finally approximates the characterized signal using suitable order Lagrange–Chebyshev interpolation polynomial. The proposed model is tested on MIT-BIH data through standard ECG performance parameters and the results obtained are found to be diagnostically useful.