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Master's Thesis.pdf (3.56 MB)
ETD Abstract Container
Abstract Header
A Wireless early prediction system of cardiac arrest through IoT
Author Info
ElSaadany, Yosuf
ORCID® Identifier
http://orcid.org/0000-0001-8038-2202
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=miami1500990636074389
Abstract Details
Year and Degree
2017, Master of Science, Miami University, Computational Science and Engineering.
Abstract
The increase in popularity for wearable technologies has opened the door for an Internet of Things (IoT) solution to healthcare. One of the most prevalent healthcare problems today is the poor survival rate of out-of-hospital sudden cardiac arrests. The objective of this study is to present a multisensory system using IoT that can collect physical activity heart rates and body temperatures. For this study, we implemented an embedded sensory system with a Low Energy Bluetooth communication module to discreetly collect electrocardiogram and body temperature data using a smartphone in a common environment. This study introduces the use of signal processing and machine learning techniques for sensor data analytics for sudden cardiac arrest and or heart attack prediction.
Committee
Donald Ucci (Advisor)
Jahangir Majumder (Advisor)
Yamuna Rajasekhar (Committee Member)
Subject Headings
Biomedical Engineering
;
Computer Engineering
;
Electrical Engineering
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Citations
ElSaadany, Y. (2017).
A Wireless early prediction system of cardiac arrest through IoT
[Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1500990636074389
APA Style (7th edition)
ElSaadany, Yosuf.
A Wireless early prediction system of cardiac arrest through IoT.
2017. Miami University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=miami1500990636074389.
MLA Style (8th edition)
ElSaadany, Yosuf. "A Wireless early prediction system of cardiac arrest through IoT." Master's thesis, Miami University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=miami1500990636074389
Chicago Manual of Style (17th edition)
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Document number:
miami1500990636074389
Download Count:
1,935
Copyright Info
© 2017, some rights reserved.
A Wireless early prediction system of cardiac arrest through IoT by Yosuf ElSaadany is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Miami University and OhioLINK.