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ECG-I2S: a method for extracting heartbeat cycle and numerical signals from ECG captured images

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References

  1. Anbalagan T, Nath M K, Vijayalakshmi D, Anbalagan A. Analysis of various techniques for ECG signal in healthcare, past, present, and future. Biomedical Engineering Advances, 2023, 6: 100089

    Article  MATH  Google Scholar 

  2. Ansari Y, Mourad O, Qaraqe K, Serpedin E. Deep learning for ECG arrhythmia detection and classification: an overview of progress for period 2017–2023. Frontiers in Physiology, 2023, 14: 1246746

    Article  MATH  Google Scholar 

  3. De Palma L, D’Alessandro V I, Attivissimo F, Di Nisio A, Lanzolla A M L. ECG wave segmentation algorithm for complete P-QRS-T detection. In: Proceedings of 2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA). 2023, 1–6

    Google Scholar 

  4. Iqbal U, Wah T Y, Rehman M H U, Mujtaba G, Imran M, Shoaib M. Deep deterministic learning for pattern recognition of different cardiac diseases through the internet of medical things. Journal of Medical Systems, 2018, 42(12): 252

    Article  MATH  Google Scholar 

  5. Sahoo S, Dash M, Behera S, Sabut S. Machine learning approach to detect cardiac arrhythmias in ECG signals: a survey. IRBM, 2020, 41(4): 185–194

    Article  MATH  Google Scholar 

  6. Chen J Y, Wang L H. Multi-lead data extraction method of ECG waveform based on mobile device application. In: Proceedings of 2020 International Symposium on Computer, Consumer and Control (IS3C). 2020, 557–560

    MATH  Google Scholar 

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Acknowledgements

This work was supported by the NSFC-FDCT Grant 62361166662; the National Key R&D Program of China (2023YFC3503400, 2022YFC3400400); the Innovative Research Group Project of Hunan Province (2024JJ1002); the Key R&D Program of Hunan Province (2023GK2004, 2023SK2059, 2023SK2060); the Top 10 Technical Key Project in Hunan Province (2023GK1010); the Key Technologies R&D Program of Guangdong Province (2023B1111030004 to FFH); and the Funds of the National Supercomputing Center in Changsha.

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Author notes

  1. These authors contributed equally to this work.

Authors and Affiliations

  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

    Xiongjun Zhao, Linzhuang Zou & Shaoliang Peng

  2. Cardiology Department, Hunan Provincial People’s Hospital, Changsha, 410005, China

    Zhengyu Liu

Authors
  1. Xiongjun Zhao
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  2. Linzhuang Zou
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  3. Zhengyu Liu
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  4. Shaoliang Peng
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Corresponding author

Correspondence to Shaoliang Peng.

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Competing interests The authors declare that they have no competing interests or financial conflicts to disclose.

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Zhao, X., Zou, L., Liu, Z. et al. ECG-I2S: a method for extracting heartbeat cycle and numerical signals from ECG captured images. Front. Comput. Sci. 19, 198915 (2025). https://doi.org/10.1007/s11704-024-40990-x

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  • DOI: https://doi.org/10.1007/s11704-024-40990-x