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An effective premature ventricular contraction detection algorithm based on adaptive template matching and characteristic recognition

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Abstract

Traditional premature ventricular contraction (PVC) detection algorithms based on template matching use fixed templates which is sensitive to the variability of electrocardiogram (ECG) and is likely to reduce detection accuracy. This paper proposes an effective PVC detection algorithm based on adaptive template matching and characteristic recognition. An adaptive template update rule has been developed to construct the optimal normal heartbeat template library, which is used to identify normal and abnormal beats. And the matching result directed the subsequent characteristic classification. Four features were extracted and used for PVC recognition based on feature knowledge. The algorithm is evaluated on the MIT-BIH arrhythmia dataset, and the results show that the accuracy was 99.48%, and the sensitivity and specificity were 98.39% and 99.54%, respectively. And it is compared with those of other recent approaches algorithms, which shows higher sensitive and accurate, and its low complexity is suitable for real-time ECG monitoring in wearable ECG devices.

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Data availability

The data used to support the findings of this study have been deposited in the MIT-BIH arrhythmia database (https://doi.org/https://doi.org/10.13026/C2F305).

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Acknowledgements

This work was supported by the Wuhan Knowledge Innovation Project (No. 2022020801010258).

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Authors and Affiliations

  1. Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan, 430068, China

    Jiale Xu, Xiaoyu Mei, Yunfan Chen & Xiangkui Wan

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  1. Jiale Xu
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  2. Xiaoyu Mei
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  3. Yunfan Chen
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Contributions

Xiangkui wan presented the conception and design of the study and interpretation of data. Yunfan Chen drafted the article and revised it critically for important intellectual content. Jiale Xu and Xiaoyu Mei wrote the main manuscript text and prepared figures. All authors reviewed the manuscript and final approval of the version to be submitted.

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Correspondence to Xiangkui Wan.

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Xu, J., Mei, X., Chen, Y. et al. An effective premature ventricular contraction detection algorithm based on adaptive template matching and characteristic recognition. SIViP 18, 2811–2818 (2024). https://doi.org/10.1007/s11760-023-02951-y

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  • DOI: https://doi.org/10.1007/s11760-023-02951-y

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