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Development of a Real-Time Stroke Detection System for Elderly Drivers Using Quad-Chamber Air Cushion and IoT Devices Korea Research Institute of Standards and Science

SAE Technical Papers (1906-current) Available online

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Format:
Conference/Event
Author/Creator:
Park, Park, author.
Contributor:
Hong, Seunghee
Hur, Jae Hun
Hussain, Iqram
Jin, Woojae
Kim, Damee
Seo, Young
Conference Name:
WCX World Congress Experience (2018-04-10 : Detroit, Michigan, United States)
Language:
English
Physical Description:
1 online resource
Place of Publication:
Warrendale, PA SAE International 2018
Summary:
AbstractIoT (Internet of things) is considered most innovative technology in smart healthcare monitoring system which is able to show real-time physiological parameters feed data to web cloud, analysis using machine learning, artificial intelligence and big data. Stroke is most deadly diseases and real-time monitoring is desired to detect stroke onset during regular activities. The aim of our study is to develop a Real-time health monitoring system for elderly drivers using air cushion seat and IoT devices in order to detect stroke onset during driving. We have also made a prototype of brain stroke detection system using Quad-chamber air cushion system and IoT devices. This system can measure ECG, EEG, heart rate, seat pressure balance data, face/eye tracking et cetera using IoT sensors, compare real-time data with reference data, predict abnormality, generate alarm and send message to relatives and emergency services if any stroke onset happens in order to provide emergency assistance to driver
Notes:
Vendor supplied data
Publisher Number:
2018-01-0046
Access Restriction:
Restricted for use by site license

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