A Method for Detecting Coronary Artery Disease using Noisy Ultrashort Electrocardiogram Recordings - iOS Application

For the full paper, please visit https://ieeexplore.ieee.org/document/9746632

This is an iOS application trying to classificate your ECG recordings from Apple Watch as showing Coronary Artery Disease or not.

The application uses a Deep Learning model to understand if the recording's quality is good, and then uses a Machine Learning model, by extracting some time, frequency and non-linear features in order to classificate the recording as CAD or non CAD.

The main application is inside diplomaThesis folder.

Some demos of the application can be found here https://www.youtube.com/watch?v=-511izXddnM&t=3s and here https://www.youtube.com/watch?v=2l9-f1rZ-tk&t=2s .

For any question regarding the project, you can contact me at [email protected].

Since this is the product of a full Master's diploma thesis, if you want to know more about the project, or understand it better, you can request the full thesis at the above e-mail address.

Orestis Apostolou, Vasileios Charisis, Georgios Apostolidis, Leontios J. Hadjileontiadis

April 2022