Noise tolerant QRS detection using template matching with short-term autocorrelation

This paper describes a robust method for heart beat detection from noisy electrocardiogram (ECG) signals. Generally, the QRS-complex of heart beat is extracted from the ECG using a threshold. However, in a noisy condition such a mobile and wearable bio-signal monitoring system, noise increases the incidence of misdetection and false detection of QRS-complex. To prevent incorrect detection, we introduce a novel template matching algorithm. The template waveform can be generated autonomously using a short-term autocorrelation method, which leverages the similarity of QRS-complex waveforms. Simulation results show the proposed method achieves state-of-the-art noise tolerance of heart beat detection.