Processing ECG signals using rational function systems

We introduce a novel approach for the processing of ECG signals (ElectroCardioGrams), which are frequently used in medical diagnostics. (They describe the functioning of the human heart.) The use of Fourier, wavelet and Gabor transforms has been already widely studied in the case of analysing medical signals. In our approach we shall use rational function systems, the basic theory of which is also well elaborated, and suggests a wide area of possible future application. The rational function systems, such as Malmquist-Takenaka systems, are very flexible, and can be adapted to the special needs of the variety of signals, therefore providing good compression, noise filtering and simple representation. Moreover these functions fit naturally to different parts of the ECG, the representation could contain direct diagnostic information. However numerical methods are required to find suitable parameters. Our results suggest that these systems can be applied also in the case of processing ECG signals. We present measurements concerning achievable compression ratios and approximation properties. The applicability of our approach is to be examined in more detail from the medical and diagnostic point of view.