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

Abstract
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.