A rate distortion optimal ECG coding algorithm

Signal compression is an important problem encountered in many applications . Various techniques have been proposed over the years for addressing the p roblem. In this paper, we present a time domain algorithm based on the codi ng of line segments which are used to approximate the signal. These segment s are fit in a way that is optimal in the rate distortion sense. Although t he approach is applicable to any type of signal, we focus, in this paper, o n the compression of electrocardiogram (ECG) signals. ECG signal compressio n has traditionally been tackled by heuristic approaches. However, it has b een demonstrated [1] that exact optimization algorithms outperform these he uristic approaches by a wide margin with respect to reconstruction error By formulating the compression problem as a graph theory problem, known optim ization theory can be applied in order to yield optimal compression. In thi s paper, we present an algorithm that will guarantee the smallest possible distortion among all methods applying linear interpolation given an upper b ound on the available number of bits, Using a varied signal test set, extensive coding experiments are presented. We compare the results from our coding method to traditional time domain E CG compression methods, as well as, to more recently developed frequency do main methods. Evaluation is based both on percentage root-mean-square diffe rence (PRD) performance measure and visual inspection of the reconstructed signals. The results demonstrate that the ex-act optimization methods have superior performance compared to both traditional ECG compression methods a nd the frequency domain methods.