An Energy Efficient Wearable Smart IoT System to Predict Cardiac Arrest
Recently, many people have become more concerned about having a sudden cardiac arrest. With the increase in popularity of smart wearable devices, an opportunity to provide an Internet of Things (IoT) solution has become more available. Unfortunately, out of hospital survival rates are low for people...
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| Veröffentlicht in: | Advances in human-computer interaction Jg. 2019; H. 2019; S. 1 - 21 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Cairo, Egypt
Hindawi Publishing Corporation
01.01.2019
Hindawi John Wiley & Sons, Inc Wiley |
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| ISSN: | 1687-5893, 1687-5907 |
| Online-Zugang: | Volltext |
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| Abstract | Recently, many people have become more concerned about having a sudden cardiac arrest. With the increase in popularity of smart wearable devices, an opportunity to provide an Internet of Things (IoT) solution has become more available. Unfortunately, out of hospital survival rates are low for people suffering from sudden cardiac arrests. The objective of this research is to present a multisensory system using a smart IoT system that can collect Body Area Sensor (BAS) data to provide early warning of an impending cardiac arrest. The goal is to design and develop an integrated smart IoT system with a low power communication module to discreetly collect heart rates and body temperatures using a smartphone without it impeding on everyday life. This research introduces the use of signal processing and machine-learning techniques for sensor data analytics to identify predict and/or sudden cardiac arrests with a high accuracy. |
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| AbstractList | Recently, many people have become more concerned about having a sudden cardiac arrest. With the increase in popularity of smart wearable devices, an opportunity to provide an Internet of Things (IoT) solution has become more available. Unfortunately, out of hospital survival rates are low for people suffering from sudden cardiac arrests. The objective of this research is to present a multisensory system using a smart IoT system that can collect Body Area Sensor (BAS) data to provide early warning of an impending cardiac arrest. The goal is to design and develop an integrated smart IoT system with a low power communication module to discreetly collect heart rates and body temperatures using a smartphone without it impeding on everyday life. This research introduces the use of signal processing and machine-learning techniques for sensor data analytics to identify predict and/or sudden cardiac arrests with a high accuracy. |
| Author | Ucci, Donald R. Young, Roger ElSaadany, Yosuf Amr Majumder, AKM Jahangir Alam |
| Author_xml | – sequence: 1 fullname: Ucci, Donald R. – sequence: 2 fullname: Young, Roger – sequence: 3 fullname: ElSaadany, Yosuf Amr – sequence: 4 fullname: Majumder, AKM Jahangir Alam |
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| Copyright | Copyright © 2019 AKM Jahangir Alam Majumder et al. Copyright © 2019 AKM Jahangir Alam Majumder et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
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| SubjectTerms | Analytics Architectural engineering Big Data Body temperature Cardiac arrest Cardiovascular disease Cloud computing Communication Communications systems Data processing Energy efficiency Energy management Engineering Fourier transforms Health care policy Heart Heart rate International conferences Internet of Things Learning algorithms Machine learning Patients Power management Quality of life R&D Research & development Sensors Signal processing Smartphones Wearable computers Wearable technology Wireless networks |
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| Title | An Energy Efficient Wearable Smart IoT System to Predict Cardiac Arrest |
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