Master project for analysing ECG data using machine learning techniques. Started in July 2018. Purpose for the project was to learn and improve on aspects of current ECG analysis techniques.
Blog post and progress report : https://chontiramaster.blogspot.com/?zx=c376798730ec5246
Referece softwares: WFDB from PhysioNet and https://github.com/mondejar/ecg-classification
Referecne papers:
Luz, E. J. da S., Schwartz, W. R., Cámara-Chávez, G., & Menotti, D. (2016). ECG-based heartbeat classification for arrhythmia detection: A survey. Computer Methods and Programs in Biomedicine, 127, 144–164. https://doi.org/10.1016/j.cmpb.2015.12.008
Macfarlane, P. W., Mason, J. W., Kligfield, P., Sommargren, C. E., Drew, B., van Dam, P., … Hodges, M. (2017). Debatable issues in automated ECG reporting. Journal of Electrocardiology, 50(6), 833–840. https://doi.org/10.1016/j.jelectrocard.2017.08.027
Moody, G. B., & Mark, R. G. (2001). The impact of the MIT-BIH arrhythmia database. IEEE Engineering in Medicine and Biology Magazine, 20(3), 45–50. https://doi.org/10.1109/51.932724
Postma, S., Bergmeijer, T., ten Berg, J., & van ’t Hof, A. (2012). Pre-hospital diagnosis, triage and treatment in patients with ST elevation myocardial infarction. Heart, 98(22), 1674–1678. https://doi.org/10.1136/heartjnl-2012-302035
Potter, B. J., Matteau, A., Mansour, S., Essiambre, R., Montigny, M., Savoie, S., & Gobeil, F. (2013). Performance of a new “physician-less” automated system of prehospital ST-segment elevation myocardial infarction diagnosis and catheterization laboratory activation. American Journal of Cardiology, 112(2), 156–161. https://doi.org/10.1016/j.amjcard.2013.03.005
Poulikakos, D., & Malik, M. (2016). Challenges of ECG monitoring and ECG interpretation in dialysis units. Journal of Electrocardiology, 49(6), 855–859. https://doi.org/10.1016/j.jelectrocard.2016.07.019
Schläpfer, J., & Wellens, H. J. (2017). Computer-Interpreted Electrocardiograms: Benefits and Limitations. Journal of the American College of Cardiology, 70(9), 1183–1192. https://doi.org/10.1016/j.jacc.2017.07.723
Sun, X., Park, J., & Kang, K. (2015). Arrhythmia classification using nearest neighbor search with principal component analysis. Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics - BCB ’15, 553–555. https://doi.org/10.1145/2808719.2811573