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.

心电图（ECG）记录心脏的电势，并且由于在记录过程中添加了各种类型的噪声而导致心脏形态发生变化，从而影响了准确的分析和临床评估。此外，由于ECG监视设备会生成大量的数字数据，因此，有效的ECG逼近技术对于正确的数据积累和传输以及ECG记录器功能的改进是必不可少的。在这里，我们提出了一个多项式逼近模型，该模型最初使用总变化优化来增强信号质量。通过自下而上的方法对增强信号进行表征，最后使用适当的阶Lagrange–Chebyshev插值多项式近似表征信号。