Cardiovascular diseases are among the ultimate causes of death worldwide. The earlier they are interpreted and treated, the more lives can be rescued. The electrocardiogram (ECG) is a standard, non-invasive, and inexpensive tool employed to measure the heart’s electrical activity and diagnose cardiovascular disorders. This proposal employs artificial augmented reality (AR) and intelligence (AI) to interpret and analyse arrhythmias. Unlike previous works that focus solely on the development of AI approaches, our study bridges the gap between AI-driven diagnostics and clinician-in-the-loop AR systems. We developed an AR application that integrates deep learning techniques, including convolutional neural networks (CNNs), with an augmented reality interface to analyse ECGs and assist healthcare practitioners in their diagnoses. This approach makes a significant contribution to the advancement of medical diagnostic tools, feedback from medical professionals after deployment evaluation is satisfactory.