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Intelligent In-Car Health Monitoring System for Elderly Drivers in Connected Car

  • Se Jin Park
  • Seunghee Hong
  • Damee Kim
  • Iqram Hussain
  • Young Seo
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 823)

Abstract

Introduction: Health has become a major concern nowadays. People pass significant amount of time of daily life on driving seat. Some health complexity happens during driving like heart problem, stroke etc. Driver’s health abnormality may also effect safety of other vehicles. So, automotive manufacturers and users are interested to include real-time health monitoring in car system.

Intelligent in-car health monitoring is considered most innovative technology which is able to measure real-time physiological parameters of drivers, feed data to web cloud, analysis using machine learning, artificial intelligence and big data. Brain stroke is most deadly diseases and effected persons lose conscience and ability to contact emergency services or hospital. Emergency medical assistance is necessary in order to survive from any kind of disability due to stroke.

Purpose: The aim of our study is to develop a health monitoring system for elderly drivers using air cushion car seat and embedded IoT (Internet of Things) devices in order to detect stroke onset during driving.

Method: Real-time monitoring is desired to detect stroke onset during regular activities like driving. Abnormal physiological signals, face pattern generated during stroke onset can be traced by real-time monitoring using sensors. Here, we have suggested a framework of stroke onset detection using sensors and developed a system suitable for elderly drivers. This system can measure and analyze data of ECG, EEG, heart rate, seat pressure balance data, face/eye tracking etc. using IoT sensors. Physiological data will be feed to cloud and compared with reference normal person data.

Findings: If any health abnormality such as stroke is found in real-time monitoring, system will predict type and severity of stroke and suggest possible steps. System may switch car control to autonomous driving mode if available and move the car to safe place. System may also generate alarm and send message with available information such as position to relatives and emergency services to provide emergency assistance so that effected driver can be transferred to hospital/clinic.

Keywords

Internet of Things Elderly healthcare Brain stroke Real-time monitoring 

References

  1. 1.
    Park SJ, Hong S, Kim D, Seo Y et al. (2018) Development of a real-time stroke detection system for elderly drivers using quad-chamber air cushion and IoT devices, SAE Technical Paper 2018-01-0046.  https://doi.org/10.4271/2018-01-0046
  2. 2.
    Park SJ, Subramaniyam M, Hong S, Kim D, Yu J (2017) Conceptual design of the elderly healthcare services in-vehicle using IoT. SAE Technical paper (No. 2017-01-1647)Google Scholar
  3. 3.
    Park SJ, Subramaniyam M, Kim SE, Hong SH, Lee JH, Jo CM (2017) Older driver’s physiological response under risky driving conditions–overtaking, unprotected left turn. In: Duffy V (ed) Advances in applied digital human modeling and simulation. AISC, vol 481. Springer, Heidelberg, pp 107–114.  https://doi.org/10.1007/978-3-319-41627-4_11
  4. 4.
    Park SJ, Min SN, Lee H, Subramaniyam M (2015) A driving simulator study: elderly and younger driver’s physiological, visual and driving behavior on intersection. In: IEA 2015, Melbourne, AustraliaGoogle Scholar
  5. 5.
    Pérennou D (2006) Postural disorders and spatial neglect in stroke patients: a strong association. Restor Neurol Neurosci 24:319–334Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Se Jin Park
    • 1
    • 2
    • 3
  • Seunghee Hong
    • 1
    • 2
  • Damee Kim
    • 1
    • 2
  • Iqram Hussain
    • 1
    • 2
    • 3
  • Young Seo
    • 1
  1. 1.Korea Research Institute of Standards and ScienceDaejeonSouth Korea
  2. 2.Electronics Telecommunication Research InstituteDaejeonSouth Korea
  3. 3.University of Science and TechnologyDaejeonSouth Korea

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