Real-time anomaly detection over ECG data stream based on component spectrum

Abstract

Anomaly detection is a popular research in the age of Big Data. As a typical application scenario, anomaly detection over ECG data stream is confronted with particular difficulties including high realtime requirement and poor data quality. In this article, a novel method based on component spectrum is presented to provide a practicable solution for the problem. Experiments on real data show that the proposed method achieves high sensitivity, high specificity and low false alarm rate.