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

Author:

Xu Jiale,Mei Xiaoyu,Chen Yunfan,Wan Xiangkui

Funder

Wuhan Knowledge Innovation Project

Publisher

Springer Science and Business Media LLC

Reference24 articles.

1. Abdalla, F.Y.O., Wu, L., Ullah, H., et al.: ECG arrhythmia classification using artificial intelligence and nonlinear and nonstationary decomposition. SIViP 13, 1283–1291 (2019)

2. Lin, M.: Design of premature ventricular contraction pacing point localization algorithm for dynamic electrocardiogram. Southeast University (2018)

3. Wang, J.: Automated detection of premature ventricular contraction based on the improved gated recurrent unit network. Comput. Methods Progr. Biomed. 208, 106284 (2021)

4. Du, Q., Zhang, W.: Research on arrhythmia detection model based on machine learning. Journal of Liaoning University of Science and Technology (2020)

5. Yang, B., Zhang, Y.: Ventricular premature beat discrimination algorithm based on multiple template matching. Comput. Eng. 36(16), 291–296 (2010)

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