HeartNetEC: a deep representation learning approach for ECG beat classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering
Link
http://link.springer.com/content/pdf/10.1007/s13534-021-00184-x.pdf
Reference18 articles.
1. Ullah A, Anwar SM, Bilal M, Mehmood RM. Classification of arrhythmia by using deep learning with 2-d ecg spectral image representation. Remote Sens. 2020;12:1685.
2. Nurmaini S, Partan RU, Caesarendra W, Dewi T, Rahmatullah MN, Darmawahyuni A, Bhayyu V, Firdaus F. An automated ecg beat classification system using deep neural networks with an unsupervised feature extraction technique’’. Appl Sci. 2019;9(14):2921.
3. Willems JL, Lesaffre E. Comparison of multigroup logistic and linear discriminant ecg and vcg classification. J Electrocardiol. 1987;20(2):83–92.
4. Coast DA, Stern RM, Cano GG, Briller SA. An approach to cardiac arrhythmia analysis using hidden markov models. IEEE Trans Biomed Eng. 1990;37(9):826–36.
5. Dutta S, Chatterjee A, Munshi S. Correlation technique and least square support vector machine combine for frequency domain based ecg beat classification. Med Eng Phys. 2010;32(10):1161–9.
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