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Advances in Human-Computer Interaction
Volume 2019, Article ID 1507465, 21 pages
https://doi.org/10.1155/2019/1507465
Research Article

An Energy Efficient Wearable Smart IoT System to Predict Cardiac Arrest

1University of South Carolina Upstate, SC, USA
2Miami University, OH 45056, USA

Correspondence should be addressed to AKM Jahangir Alam Majumder; ude.hoimaim@aadmujam

Received 26 October 2018; Accepted 1 January 2019; Published 12 February 2019

Guest Editor: Maurizio Rebaudengo

Copyright © 2019 AKM Jahangir Alam Majumder et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

AKM Jahangir Alam Majumder, Yosuf Amr ElSaadany, Roger Young Jr., and Donald R. Ucci, “An Energy Efficient Wearable Smart IoT System to Predict Cardiac Arrest,” Advances in Human-Computer Interaction, vol. 2019, Article ID 1507465, 21 pages, 2019. https://doi.org/10.1155/2019/1507465.