The thesis deals with detection of T-wave alternans. The presence of T-wave in surface ECG is recognized as a marker of electrical instability of heart in stage his repolarization, arise increased risk of emergence ventricular fibrillation and sudden cardiac death. The goal of our project is familiarize with methods of detection T-wave alternans. In particular spectral method and spectral method which was realized in variant for running reading values in time (“sliding window”). To suggest a QRS complex detector, localize the T-wave and to make TWA detection using spectral method and modified spectral method. This project is to be made in C language in appropriate user interface.

This thesis deals with analysis of T-wave Alternans (TWA), periodical changes of T wave in ECG signal. Presence of these alternans may predict higher risk of sudden cardiac death. From the several possible ways of TWA classification, the training algorithms of self organizing maps are used in this thesis. Result of the thesis is a program, which in the first step detects QRS complexes in the signal. Then, in the next step, gained reference points are used for T-waves detection. Detected waves are represented by a vector of significant points, which is used as an input for artificial neural network. Final output of the program is a decision about presence of TWA in the signal and its rate.