Intelligent Electrocardiogram Monitoring System for Early Arrhythmia Detection

An electrocardiogram is a record of the electrical activity of the heart. There has been considerable research on associated monitoring techniques and on the automated analysis of the resulting data. We integrate these processes within an intelligent heart monitoring system. Designed to fit in with the daily life of a subject, it uses smartphone and web applications to link to a monitoring station via a decision support server. This server analyzes heart activity using the well-known Pan-Tompkins algorithm to detect heartbeats and a decision tree to classify them. We have simulated these analyses with data from the MIT-BIH Arrhythmia Database, and found that the server software had a 97% success rate in heartbeat detection and almost 97% accuracy in heartbeat classification.