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ECG ANALYSIS

made-with-python

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Motivation

ECG is a type of time-series data, it has its own particular properties. This project is created to learn these specifics and how to obtain valuable features from the ECG signal. In particular, from QRS complexes, RR intervals.

QRS complex

Visualization:

Screenshots

Raw signal: Raw signal

Filter frequency response: Filter frequency response

Applied filter: Applied filter

R peaks detection process: R peaks detection process

Comparison with different R-peaks detecors: Comparison with different R-peaks detecors

Dependencies

  • Anaconda-Server Badge: conda install nb_conda
  • Anaconda-Server Badge: conda install matplotlib
  • Anaconda-Server Badge: conda install seaborn
  • Anaconda-Server Badge: conda install numpy
  • Anaconda-Server Badge: conda install pywavelets
  • Anaconda-Server Badge: conda install scipy
  • PyPI version: pip install biosppy
  • PyPI version: pip install pyhrv

Literature:

  1. DOI:10.1109/TBME.1985.325532 Pan-Tomkins algorithm (Pan J., Tompkins W. J., A real-time QRS detection algorithm, IEEE Transactions on Biomedical Engineering, Vol. BME-32, No. 3, March 1985, pp. 230-236).
  2. ECGwaves.com
  3. "ECG filtering T-61.181" – Biomedical Signal Processing Presentation 11.11.2004 Matti Aksela (Aalto University)
  4. "Mining the ECG: Algorithms and Applications" - 2015 KU Leuven – Faculty of Engineering Science Carolina Varon
  5. https://imotions.com/blog/heart-rate-variability/
  6. http://www.medteq.info/med/ECGFilters
  7. http://www.ems12lead.com/2014/03/10/understanding-ecg-filtering/
  8. Band-pass filter | Wikipedia
  9. Butterworth filter | Wikipedia
  10. Heart rate variability (HRV) | Wikipedia
  11. Electrocardiography | Wikipedia
  12. DOI:10.1093/acprof:oso/9780195058239.003.0019 Bioelectromagnetism. 19. The Basis of ECG Diagnosis 1995 by Jaakko Malmivuo, Robert Plonsey
  13. Exploring Heart Rate Variability using Python
  14. DOI:10.1037/1089-2680.10.3.229 Heart rate variability as an index of regulated emotional responding (Appelhans, Bradley M.,Luecken, Linda J. Review of General Psychology, Vol 10(3), Sep 2006, 229-240)