ECG Multiclass Classification Using Temporal Features, Information Measures, and Non-linear Parameters
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-51723-5_59
Reference21 articles.
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2. Annam, J.R., Kalyanapu, S., Ch, S., Somala, J., Raju, S.B.: Classification of ECG heartbeat arrhythmia: a review. Procedia Comput. Sci. 171, 679–688 (2020)
3. Chen, M., Wang, G., Ding, Z., Li, J., Yang, H.: Unsupervised domain adaptation for ECGarrhythmia classification. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 304–307. IEEE (2020)
4. Sahoo, S., Dash, M., Behera, S., Sabut, S.: Machine learning approach to detect cardiac arrhythmias in ECG signals: a survey. Irbm 41(4), 185–194 (2020)
5. Plawiak, P.: ECG signals (1000 fragments), Mendeley Data, v3 (2017)
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