Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Classification of normal and abnormal ECG records using lead convolutional neural network and rule inference

  • Highlight
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

References

  1. Dong J, Zhang J W, Zhu H H, et al. Wearable ECG monitors and its remote diagnosis service platform. IEEE Intell Syst, 2012, 6: 36–43

    Article  Google Scholar 

  2. Ye C, Kumar B V, Coimbra M T. Heartbeat classification using morphological and dynamic features of ECG signals. IEEE Trans Biomed Eng, 2012, 59: 2930–2941

    Article  Google Scholar 

  3. Willems J L, Abreu-Lima C, Arnaud P, et al. The diagnostic performance of computer programs for the interpretation of electrocardiograms. New England J Medicine, 1991, 325: 1767–1773

    Article  Google Scholar 

  4. Zhang J W, Liu X, Dong J. CCDD: an enhanced standard ECG database with its management & annotation tools. Int J Artif Intell Tools, 2012, 21: 1–26

    Article  Google Scholar 

  5. Zhu H H. Research on ECG recognition critical methods and development on remote multi body characteristic signal monitoring system. Dissertation for Ph.D. Degree. Beijing: University of Chinese Academy of Sciences, 2013

    Google Scholar 

  6. Wang L P. Study on approach of ECG classification with domain knowledge. Dissertation for Ph.D. Degree. Shanghai: East China Normal University, 2013

    Google Scholar 

  7. Jin L P, Dong J. Deep learning research on clinical electrocardiogram analysis (in Chinese). Sci Sin Inform, 2015, 45: 398–415

    Google Scholar 

  8. Zhu H H, Dong J. An R-peak detection method based on peaks of Shannon energy envelope. Biomed Signal Process Control, 2013, 8: 466–474

    Article  Google Scholar 

  9. Jin L P, Dong J. Ensemble deep learning for biomedical time series classification. Comput Intell Neurosci, 2016, 2016: 6212684

    Article  Google Scholar 

  10. Liu X. Atlas of Classical Electrocardiograms. Shanghai: Shanghai Science and Technology Press, 2011

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jun Dong.

Additional information

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jin, L., Dong, J. Classification of normal and abnormal ECG records using lead convolutional neural network and rule inference. Sci. China Inf. Sci. 60, 078103 (2017). https://doi.org/10.1007/s11432-016-9047-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11432-016-9047-6