Signal Compression by Second Order Polynomials and Piecewise Non-interpolating Approximation

In this paper we present a time domain signal compression scheme based on the coding of line segments which are used to approximate the signal. These segments are t in a way that is optimal given the number of retained signal samples. Although the approach is useful for many types of signals, we focus in this paper on compression of ElectroCardioGram (ECG) signals. ECG signal compression has traditionally been tackled by heuristic approaches. However, it has been demonstrated 1] that optimization algorithms out-perform these heuristic approaches by a wide margin with respect to reconstruction error. The optimization algorithm extracts signal samples from the original signal by formulating the sample selection problem as a graph theory problem. Thus, known optimization theory can be applied in order to yield optimal compression. This paper generalizes the optimization scheme by removing the interpolation restriction and applying second order polynomi-als in approximation of the signal. The method shows superior performance compared to traditional ECG compression methods.