Institute of Biomedical Engineering

Classification of atrial ectopic origins into spatial segments based on the 12-lead ECG

  • The aim of this thesis is to study, whether the standard 12-lead ECG can be used to localize the origin of atrial ectopic beats.
    A neural network shall be used to classify ECG signals into predefined spatial segments of the atria.
    This work will involve the following steps:

    *Literature research about:
       -Atrial ectopic beats and their relation to changes in the ECG features
       -Methods to split the atria into spatial segments
       -Similar ML approaches to solve the inverse problem
       -Design, training and validation of neural networks
    *Splitting the atria into spatial segments
    *Excitation simulations using Fast Marching
    *Forward calculations
    *Analysis of ECG variations and feature extraction
    *Neural network design and training
    *Application of to simulated data / validation
    *(Application to measured data)