Wavelet-Analysis of Cardiosignals Using Matlab

This article is devoted to the problem of accurate detection of cardiosignal QRS-complexes for early diagnosis of various diseases of human cardiovascular system. For that purpose various algorithms based on either digital filtering methods or mathematical modeling of ECG signal particular sections are used. However, all listed methods have a number of disadvantages impairing the accuracy of QRS-complex determination. Yet wavelet transforms enabling accurate identification of local features for non-stationary signals are becoming more common in various fields of technology.The article presents wavelet spectrogram calculation by means of various wavelets and levels of decomposition in the Wavelet Toolbox environment. Based on wavelet coefficient amplitudes, the presence of jumps, discontinuities, i.e. QRS complex can be identified. In addition, by comparing the form of the QRS complex and the graph of the scaling function of different wavelets, the most optimal wavelet is determined for identifying the QRS complex, as well as noise suppression in cardiosignals.The obtained results can be used not only in electrocardiography, but also in solving problems of identification and processing of various types of signals.