Analysis of electrocardiographic signals using a new method based on the principles of wavelet processing and Gauss-Hermit functions

Diagnosis of human diseases at an early stage is an actual direction in medical practice. It is important not only to detect pathology, but also to predict the further progression of the disease. The situation is complicated by the fact that medical signals are non-stationary, which is due to the constant change in the shape of the signal under the influence of a wide range of factors. In practice, such a dynamic picture is observed when adding noise and interference components. In this regard, high requirements are imposed on new processing methods in terms of resistance to interference and adaptation to changes in the signal shape. The article presents the results of processing model medical signals, in particular ECG signals, by a new method, which is based on the combined application of the theory of optimal filtering, wavelet transform and Hermite transform. The modeling of situations of changing the shape of the ECG signal under the influence of noise are simulated. The conclusion and further prospects for the development of the processing method are given.