The research presented in this article specifically explores the utility of Chebyshev polynomials in electrocardiogram (ECG) signal processing and specializes in its correction and development capability. ECG sign evaluation is an important a part of coronary heart monitoring and is crucial for figuring out and monitoring heart issues. However, dependable analysis is hard, mainly while looking to come across small defects. Additionally, this observe presents a brand new technique for interpolation, smoothing and optimization of ECG statistics using Chebyshev polynomials. ECG features had been normalized to conform to the character of Chebyshev polynomials. Then the polynomial coefficients are calculated by way of the orthogonal projection technique. The aim of this look at is to reduce the mistake among the reconstructed ECG characteristics and the original ECG traits with the aid of optimizing the coefficients using a genetic algorithm (GA) in MATLAB. This strategy calls for collecting ECG statistics, segmenting it into person heartbeats the use of the Pan-Tompkins technique, the usage of a finite impulse reaction (FIR) bandpass filter as a preprocessing step, and ultimately applying Chebyshev polynomials for function extraction. The effects show how effective our technique is, showing desirable convergence of GA and lowering errors, for that reason offering an accurate and dependable illustration of ECG alerts that may be utilized in prognosis and monitoring