A framework for cardiac arrhythmia detection from IoT-based ECGs
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Software
Link
http://link.springer.com/content/pdf/10.1007/s11280-019-00776-9.pdf
Reference54 articles.
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4. Afkhami, R.G., Azarnia, G., Tinati, M.A.: Cardiac arrhythmia classification using statistical and mixture modeling features of ecg signals. Pattern Recogn. Lett. 70, 45–51 (2016)
5. Alejo, R., Sotoca, J.M., Valdovinos, R.M., Toribio, P.: Edited nearest neighbor rule for improving neural networks classifications. In: International Symposium on Neural Networks, pp 303–310. Springer (2010)
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