Detekce raménkové blokády s využitím analýzy vektorkardiografických průběhů

Abstract

This diploma thesis deals with the detection of bundle branch block through the analysis of vectorcardiographic (VCG) signals. The main focus is placed on the extraction of morphological characteristics of the QRS and T loops, which may serve as diagnostic indicators of this cardiac conduction disorder. Subsequently, the extracted features are subjected to statistical analysis to assess their significance. In the next phase, classification models utilizing these features are designed and implemented to predict bundle branch block. The final part of the thesis focuses on testing the models and evaluating their performance in terms of classification accuracy and reliability.