ECG signal classification
Abstract
This thesis deals with classification of different types of time courses of ECG signals. Main objective was to recognize the normal cycles and several forms of arrhythmia and to classify the exact types of them. Classification has been done with usage of algorithms of Neural Networks in Matlab program, with its add-on (Neural Network Toolbox). The result of this thesis is application, which makes possible to load an ECG signal, pre-process it and classify its each cycle into five classes. Percentage results of this classification are in the conclusion of this thesis- info:eu-repo/semantics/masterThesis
- MLP; heart; Neural Networks; arytmie; BP; Matlab; Guide.; tansig; filtration; VPS; Elektrokardiogram; normal contraction; NS; srdce; arrhythmia; extra systole; ECG classification; normální cyklus; BPRT; extrasystoly; NN; kardiostimulace; klasifikace EKG; cardio stimulation; neuronové sítě; filtrace; BPLT; Electrocardiogram