@inproceedings{4f362425876142dbaa4be9d83ad1373a,
title = "Graphene oxide - Nylon ECG sensors for wearable IOT healthcare",
abstract = "The Internet of Things (IoT) presents opportunities to address a variety of systemic, metabolic healthcare issues. Cardiovascular disease and diabetes are among the greatest contributors to premature death worldwide. Wireless wearable continuous monitoring systems (CMS) such as ECG sensors connected to the Internet of Things can greatly decrease the risk of death related to cardiac issues by providing valuable long-term information to physicians, as well as immediate contact with emergency services in the event of a heart attack or stroke. In this report we discuss the fabrication, characterization and validation of composite fabric ECG sensors made from Nylon coated with reduced graphene oxide (rGOx) as part of a self-powered wearable IoT sensor. We utilize an electronic probing station to measure electrical properties, take live ECG data to measure signal reliability, and provide detailed surface characterization through scanning electron microscopy (SEM). Finally, bonding between the layers of the composite and between composite and the Nylon is analyzed by Fourier transform Infrared (FTIR) spectroscopy.",
keywords = "Conductive Fabric, ECG Sensor, IoT Sensors, Reduced Graphene Oxide",
author = "Hallfors, {N. G.} and {Abi Jaoude}, M. and K. Liao and Mohammed Ismail and Isakovic, {A. F.}",
note = "Funding Information: We acknowledge assistance of Dr. Y. A. Samad in early stages of rGOx growth. This work was supported by the Mubadala and SRC through 2013-HJ-2440 and in part, through the Mubadala SRC task 2011-KJ-2190. KL and AFI acknowledge 2012-KUIRF-L2 support and we thank A. Devarajan for her assistance. A part of this work was conducted in the KU Core Nanocharacterization Facilities (KU CNCF). Publisher Copyright: {\textcopyright} 2017 IEEE.; 1st International Conference on Sensors Networks Smart and Emerging Technologies, SENSET 2017 ; Conference date: 12-09-2017 Through 14-09-2017",
year = "2017",
month = nov,
day = "29",
doi = "10.1109/SENSET.2017.8125034",
language = "British English",
series = "2017 Sensors Networks Smart and Emerging Technologies, SENSET 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--4",
booktitle = "2017 Sensors Networks Smart and Emerging Technologies, SENSET 2017",
address = "United States",
}