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

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Abstract

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.

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Acknowledgements

This work was supported in part by National Key Research and Development Program of China (Grant No. 2019YFB2204500), in part by National Natural Science Foundation of China (Grant No. 61874171), in part by Science, Technology and Innovation Action Plan of Shanghai Municipality, China (Grant No. 1914220370), and Alibaba Group through Alibaba Innovative Research (AIR) Program.

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Authors and Affiliations

  1. Department of Micro and Nano Electronics, Shanghai Jiao Tong University, Shanghai, 200240, China

    Kai Zhao, Yongfu Li, Guoxing Wang & Yong Lian

  2. Alibaba Group, Sunnyvale, CA, 94085, USA

    Yu Pu

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  1. Kai Zhao
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  2. Yongfu Li
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  3. Guoxing Wang
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  4. Yu Pu
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Correspondence to Yongfu Li.

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Zhao, K., Li, Y., Wang, G. et al. A robust QRS detection and accurate R-peak identification algorithm for wearable ECG sensors. Sci. China Inf. Sci. 64, 182401 (2021). https://doi.org/10.1007/s11432-020-3150-2

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  • DOI: https://doi.org/10.1007/s11432-020-3150-2

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