AI-Enabled Smart Watch Detection of Cardiac Arrest: A Review

Abstract

Cardiac arrest is a common cause of death, with a high mortality rate if it occurs outside of hospitals and does not receive immediate care. This paper explored the possibilities of using the widespread technology, smart watches, in the detection of cardiac arrest, with the assistance of AI and deep learning algorithms. After understanding cardiac arrest and the electrocardiogram (ECG) waves for diagnosis, current smart watch technology is more focused on other ECG readings, and despite its accuracy, it cannot support the detection of cardiac arrest. However, with the use of deep learning and generative AI, the potential of early onset cardiac arrest detection seems to be likely in the near future. Currently, smart watches are capable of capturing 3-lead ECG readings, as well as precordial ECG diagrams. With further research in AI training and hardware upgrades, early onset cardiac arrest detection is possible, and could help save many lives from cardiac arrest.