Detection Of Atrial Fibrillation in Electrocardiogram Signals using Machine Learning

Abstract

Atrial fibrillation is a type of heart abnormality often called as an arrhythmia. It is detected when the heart does not beat at a normal pace i.e at spurious time intervals. Automatic atrial fibrillation (AFib) detection is a problem that has been tackled by researchers and engineers for a few decades. It is the most common of the arrhythmias [5]. Many people are susceptible to get AFib. According to the Centers for Disease Control and Prevention (CDC), approximately 2% of people younger than 65 years old have AFib, while about 9% of people ages 65 and older have it [6]. A device which can differentiate between sinus rhythm and AFib would be a gift for people having this illness.