Paper Title
Deriving The 12-Lead ECG From EASI Electrodes Via Nonlinear Regression

The standard 12-lead Electrocardiogram (ECG) is the basic clinical method of heart disease diagnosis. Measuring all 12 leads is often cumbersome and impractical especially on a long term monitoring. In 1988, Gordon Dower has introduced an EASI-lead ECG System, where only 5 electrodes are used. In order to gain all 12-lead ECG back from this EASI system, Dower’s equation was proposed then. Ever since various attempts have been explored to improve the synthesis accuracy, mostly via Linear Regression. This paper presents how Polynomial Regression is used to find a set of transfer coefficients for deriving the 12-lead ECG from EASI system. The experiments were conducted to compare the results those of Polynomial Regression against those of Linear equation and those of Dower’s method. The experimental results have shown that the best performance amongst those methods with the highest correlation coefficient for all signals with the standard 12-lead ECG was obtained by Polynomial degree 3, followed by degree 2, then Linear Regression and Dower’s equation, respectively. Keywords- ECG; 12-lead System; EASI-lead ECG System; Linear Regression; Dower; Polynomial Regression.