Skip to main content
Springer Nature Link
Log in

Investigate the In-Vehicle Healthcare System Design Opportunities: Findings from a Co-design Study

  • Conference paper
  • First Online:
HCI in Mobility, Transport, and Automotive Systems (HCII 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13335))

Included in the following conference series:

  • 2020 Accesses

Abstract

Many people spend a long time in vehicles in their daily commute, and they want their health condition to be taken care of during the journey. In line with this need, the advancement of smart technologies brings possibilities for ubiquitous healthcare. This work intends to explore users’ expectations regarding an in-vehicle healthcare system (IVHS) and guide the development of relevant technologies. Four co-design workshops were organized with sixteen participants with diverse professional backgrounds. Over two hundred ideas were generated and categorized into seven groups, indicating seven promising perspectives in developing an IVHS. Furthermore, a conceptual framework was proposed based on the ideas collected from the workshops. The framework organized the expected functions of an IVHS into three groups, namely data collection, communication, and actuation. In combination with the literature review about relevant technologies, the framework pointed out some future research directions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Ullah, H., Nair, N.G., Moore, A., Nugent, C., Muschamp, P., Cuevas, M.: 5G communication: an overview of vehicle-to-everything, drones, and healthcare use-cases. IEEE Access 7, 37251–37268 (2019)

    Article  Google Scholar 

  2. ENERGIZING comfort control: Wellness while driving. https://media.daimler.com/marsMediaSite/ko/en/41880672. Accessed 05 Feb 2022

  3. Chaudhry, J.A., Saleem, K., Alazab, M., Zeeshan, H.M.A., Al-Muhtadi, J., Rodrigues, J.J.: Data security through zero-knowledge proof and statistical fingerprinting in vehicle-to-healthcare everything (v2HX) communications. IEEE Trans. Intell. Transp. Syst. 22(6), 3869–3879 (2021)

    Article  Google Scholar 

  4. Pavithra, B., Suchitra, S., Subbulakshmi, P., Mercy Faustina, J.: RFID based smart automatic vehicle management system for healthcare applications. In: 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA), pp. 390–394. IEEE, Coimbatore, India (2019)

    Google Scholar 

  5. Park, S.J., Subramaniyam, M., Hong, S., Kim, D., Yu, J.: Conceptual design of the elderly healthcare services in-vehicle using IoT. SAE Technical Paper, 2017-01-1647, (2017)

    Google Scholar 

  6. Kerr, D., Olateju, T.: Driving with diabetes in the future: in-vehicle medical monitoring. J. Diabetes Sci. Technol. 4(2), 464–469 (2010)

    Article  Google Scholar 

  7. Dumitru, A.I., Mogan, G.L.: Aspects concerning drivers monitoring healthcare systems. Bulletin of the Transilvania university of Brasov. Eng. Sci. Ser. I 7(1), 7 (2014)

    Google Scholar 

  8. Kurebwa, J.G., Mushiri, T.: Passenger car safety and emergency healthcare: a literature review. Procedia Manuf. 35, 35–49 (2019)

    Article  Google Scholar 

  9. Thirugnanam, T., Ghalib, M.R.: A new healthcare architecture using IoV technology for continuous health monitoring system. Heal. Technol. 10(1), 289–302 (2019). https://doi.org/10.1007/s12553-019-00306-7

    Article  Google Scholar 

  10. Mukhopadhyay, A.: QoS based telemedicine technologies for rural healthcare emergencies. In: 2017 IEEE Global Humanitarian Technology Conference (GHTC), pp. 1–7. IEEE, San Jose, CA, USA (2017)

    Google Scholar 

  11. Balters, S., Mauriello, M.L., Park, S.Y., Landay, J.A., Paredes, P.E.: Calm commute: guided slow breathing for daily stress management in drivers. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4(1), 1–19 (2020)

    Article  Google Scholar 

  12. Koch, K., et al.: When do drivers interact with in-vehicle well-being interventions? An exploratory analysis of a longitudinal study on public roads. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5(1), 1–30 (2021)

    Article  Google Scholar 

  13. Braun, M., Mainz, A., Chadowitz, R., Pfleging, B., Alt, F.: At your service: designing voice assistant personalities to improve automotive user interfaces. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–11. Glasgow, Scotland, UK (2019)

    Google Scholar 

  14. Yokota, Y., Aoki, M., Mizuta, K., Ito, Y., Isu, N.: Motion sickness susceptibility associated with visually induced postural instability and cardiac autonomic responses in healthy subjects. Acta Otolaryngol. 125(3), 280–285 (2005)

    Article  Google Scholar 

  15. Bles, W., Bos, J.E., Kruit, H.: Motion sickness. Curr. Opin. Neurol. 13(1), 19–25 (2000)

    Article  Google Scholar 

  16. Smart, L.J., Jr., Stoffregen, T.A., Bardy, B.G.: Visually induced motion sickness predicted by postural instability. Hum. Factors 44(3), 451–465 (2002)

    Article  Google Scholar 

  17. Kamiji, N., Kurata, Y., Wada, T., Doi, S.I.: Modeling and validation of carsickness mechanism. In: SICE Annual Conference 2007, pp. 1138–1143. IEEE, Takamatsu, Japan (2007)

    Google Scholar 

  18. Bos, J.E., Bles, W.: Modelling motion sickness and subjective vertical mismatch detailed for vertical motions. Brain Res. Bull. 47(5), 537–542 (1998)

    Article  Google Scholar 

  19. Salter, S., Diels, C., Herriotts, P., Kanarachos, S., Thake, D.: Model to predict motion sickness within autonomous vehicles. Proc. Inst. Mech. Eng. Part D: J. Automob. Eng. 234(5), 1330–1345 (2020)

    Article  Google Scholar 

  20. Diels, C., Bos, J.E.: Self-driving carsickness. Appl. Ergon. 53, 374–382 (2016)

    Article  Google Scholar 

  21. DiZio, P., et al.: An active suspension system for mitigating motion sickness and enabling reading in a car. Aerosp. Med. Hum. Perform. 89(9), 822–829 (2018)

    Article  Google Scholar 

  22. Kobrinskii, B.A., Grigoriev, O.G., Molodchenkov, A.I., Smirnov, I.V., Blagosklonov, N.A.: Artificial intelligence technologies application for personal health management. IFAC-PapersOnLine 52(25), 70–74 (2019)

    Article  MathSciNet  Google Scholar 

  23. Liu, J., Ma, D., Weimerskirch, A., Zhu, H.: A functional co-design towards safe and secure vehicle platooning. In: Proceedings of the 3rd ACM Workshop on Cyber-Physical System Security, pp. 81–90. Association for Computing Machinery, New York, United States (2017)

    Google Scholar 

  24. Nahum-Shani, I., et al.: Just-in-time adaptive interventions (JITAIs) in mobile health: key components and design principles for ongoing health behavior support. Ann. Behav. Med. 52(6), 446–462 (2018)

    Article  Google Scholar 

  25. Hakimi, N., Jodeiri, A., Mirbagheri, M., Setarehdan, S.K.: Proposing a convolutional neural network for stress assessment by means of derived heart rate from functional near infrared spectroscopy. Comput. Biol. Med. 121, 103810 (2020)

    Google Scholar 

  26. Pourmohammadi, S., Maleki, A.: Continuous mental stress level assessment using electrocardiogram and electromyogram signals. Biomed. Signal Process. Control 68, 102694 (2021)

    Google Scholar 

  27. Wang, J., Warnecke, J.M., Haghi, M., Deserno, T.M.: Unobtrusive health monitoring in private spaces: the smart vehicle. Sensors 20(9), 2442 (2020)

    Article  Google Scholar 

  28. Ran, X., Wang, C., Xiao, Y., Gao, X., Zhu, Z., Chen, B.: A portable sitting posture monitoring system based on a pressure sensor array and machine learning. Sens. Actuators A Phys 331, 112900 (2021)

    Google Scholar 

  29. Chuang, M.C., Bala, R., Bernal, E.A., Paul, P., Burry, A.: Estimating gaze direction of vehicle drivers using a smartphone camera. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 165–170. IEEE Computer Society (2014)

    Google Scholar 

  30. Lohani, D., Acharya, D.: Real time in-vehicle air quality monitoring using mobile sensing. In: 2016 IEEE Annual India Conference (INDICON), pp. 1–6. IEEE, Bangalore, India (2016)

    Google Scholar 

  31. Chen, S., et al.: Vehicle-to-everything (V2X) services supported by LTE-based systems and 5G. IEEE Commun. Stand. Mag. 1(2), 70–76 (2017)

    Article  Google Scholar 

  32. Ghosal, A., Conti, M.: Security issues and challenges in V2X: a survey. Comput. Netw. 169, 107093 (2020)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Science and Engineering, University of Nottingham Ningbo China, 199 Taikang East Road, Ningbo, 315100, China

    Jiming Bai, Yaorun Zhang, Xu Sun, Siyuan Zhou & Ruiheng Lan

  2. Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, 211 Xingguang Road, Ningbo, 315100, China

    Xu Sun

  3. Ningbo Weizhi Digital Information Technology Co., Ltd., Building E, 655 Xueshi Road, Ningbo, 315194, China

    Xiaowu Jiang

Authors
  1. Jiming Bai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yaorun Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xu Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Siyuan Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ruiheng Lan
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiaowu Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xu Sun .

Editor information

Editors and Affiliations

  1. Technische Universität Ilmenau, Ilmenau, Germany

    Heidi Krömker

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bai, J., Zhang, Y., Sun, X., Zhou, S., Lan, R., Jiang, X. (2022). Investigate the In-Vehicle Healthcare System Design Opportunities: Findings from a Co-design Study. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2022. Lecture Notes in Computer Science, vol 13335. Springer, Cham. https://doi.org/10.1007/978-3-031-04987-3_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-04987-3_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-04986-6

  • Online ISBN: 978-3-031-04987-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics