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

Classification of atrial ectopic origins into spatial segments based on the 12-lead ECG
Typ:Masterarbeit
Betreuer:

M.Sc. Steffen Schuler

Bearbeiter:

B.Sc. Pedro Álvarez Guirado

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)