A review of different ECG classification/detection techniques for improved medical applications
Author:
Publisher
Springer Science and Business Media LLC
Subject
Strategy and Management,Safety, Risk, Reliability and Quality
Link
https://link.springer.com/content/pdf/10.1007/s13198-021-01548-3.pdf
Reference179 articles.
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3. Acharya UR, Fujita H, Adam M, Lih OS, Sudarshan VK, Hong TJ, Koh JE, Hagiwara Y, Chua CK, Poo CK, San TR (2017) Automated characterization and classification of coronary artery disease and myocardial infarction by decomposition of ECG signals: a comparative study. Infor Sci 377:17–29
4. Acharya UR, Oh SL, Hagiwara Y, Tan JH, Adam M, Gertych A, Tan RS (2017) A deep convolutional neural network model to classify heartbeats. Comp Biol Med 89:389–396
5. Acharya UR, Fujita H, Lih OS, Hagiwara Y, Tan JH, Adam M (2017) Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network. Infor Sci 405:81–90
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