AI-based detection for Remote Electrocardiogram Monitoring System

With the rapid advancement of artificial intelligence (AI) and remote patient monitoring technologies, there is a growing interest in developing robust and efficient AI-based detection systems for cardiac arrhythmias. This study presents the implementation of an AI-driven arrhythmia detection system utilizing the MIT-BIH Arrhythmia Database which not only classifies normal and abnormal ECG segments but also detects bad-read segments caused by network data attacks.