A robust QRS detection and accurate R-peak identification algorithm for wearable ECG sensors

This paper presents a robust QRS detection algorithm that is capable of detecting QRS complexes as well as accurately identifying R-peaks. The proposed bilateral threshold scheme combined with QRS watchdog greatly improves the detection accuracy and robustness, resulting in consistent detection performance on 9 available ECG databases. Simulations show that the proposed algorithm achieves good results on the datasets from both QTDB healthy database and MITDB arrhythmia database, i.e. the sensitivity of 99.99% and 99.88%, the precision of 99.98% and 99.88%, and the detection error rate of 0.04% and 0.31%, respectively. Furthermore, it also outperforms many existing algorithms on six other ECG databases, such as NSTDB, TWADB, STDB, SVDB, AFTDB, and FANTASIADB.

Automated summary

The study introduces a robust QRS detection algorithm that achieves high accuracy and robustness, demonstrating consistent detection performance across multiple ECG databases.