Augmented reality and mobile-based digitalization, processing, classification and visualization of electrocardiograms in a real-world clinical environment Augmented reality and mobile-based digitalization, processing, classification and visualization of electrocardiograms in a real-world clinical environment

Even nowadays there are a lot of difficulties to obtain a digitalized representation of electrocardiograms (ECG) in the hospitals, either in the emergency unit or in the cardiology department. Sometimes, the ECG acquisition systems only output a printed representation of the ECG. Other times, only a pdf is extracted. The main goal of this project is to use AR glasses and mobile devices to acquire pictures of ECGs, extract them from the images and classify them according to different type of cardiac abnormalities. Classical image processing techniques could be used in conjunction with deep learning methods for classification (or end-to-end network). Visualization of the classification results would be included in the AR glasses and mobiles to guiding the user.


Supervisor: Oscar Camara