Analysis of ECG signals for the prediction of atrial fibrillation (Report + Analysis in R Project)

The programming section must be done only in R Project.
Aim of the study: Analyse multichannel biosignals to identify important features that can be used for the prediction of AF and compare beat to beat analysis versus the analysis of an averaged beat. Background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, occurring in 1–2% of the general population. AF is characterized by an irregular and chaotic electrical activation of the atria resulting in the modification of the ventricular activity and increased risk of clot formation. “Paroxysmal” AF (PAF) is a type of AF which may last up to 48 hours and is usually self-terminated. Given the absence of remarkable structural remodeling in patients with PAF, the detection of possible changes in the surface electrocardiogram (ECG) is challenging. The atrial depolarization is represented on the surface ECG as the P-wave. P-wave closely correlates with the conduction in specific parts of the atria and thus any deflection of the P-wave characteristics implies regional changes in atrial activation time and conduction route.