Skip to main content

Using Artificial Intelligence and Companion Robots to Improve Home Healthcare for the Elderly

  • Conference paper
  • First Online:
HCI International 2023 – Late Breaking Papers (HCII 2023)

Abstract

Several statistical reports have addressed the problem of increasing old age and the related increase in emergency room requests in hospital centers. In this paper, interviews were conducted with specialists in the field of geriatrics, a branch of medicine that deals with disorders and diseases related to aging, with the aim of understanding the main health and cognitive problems of an elderly person. From the data that emerged from the interviews conducted, it was realized that the elderly tend to alarm physicians about any alterations, whether serious or not. This behavior causes an increase in healthcare costs associated with keeping more individuals in the emergency room. According to experts, one of the useful practices to keep cognitive impairment under control is mental training. In this context, the constant intervention of a caregiver, whether a family member or a person from outside the family, is helpful, so strategies to cope with the stress involved in managing a patient with dementia need to be improved. Therefore, the emotional state of the caregiver should be a factor that should not be underestimated. Based on these aspects, the goal is to reinvent caregiving so that it is automated and effective. In this article, we focus on the use of robots, with the integration of artificial intelligence, to monitor the health and cognitive status of an elderly person at home. We present the design of a system involving four actors and show a usage scenario.

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

Access this chapter

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

Notes

  1. 1.

    https://www.istat.it/, last access 15 May 2023.

References

  1. Alaskar, K.M., et al.: Artificial intelligence (AI) in healthcare management. J. Pharm. Negat. Results 1011–1020 (2022)

    Google Scholar 

  2. Alatise, M.B., Hancke, G.P.: A review on challenges of autonomous mobile robot and sensor fusion methods. IEEE Access 8, 39830–39846 (2020). https://doi.org/10.1109/ACCESS.2020.2975643

    Article  Google Scholar 

  3. Amato, F., Di Gregorio, M., Monaco, C., Sebillo, M., Tortora, G., Vitiello, G.: The therapeutic use of humanoid robots for behavioral disorders. In: Proceedings of the International Conference on Advanced Visual Interfaces. AVI 2020. Association for Computing Machinery, New York (2020). https://doi.org/10.1145/3399715.3399960

  4. Amato, F., Di Gregorio, M., Monaco, C., Sebillo, M., Tortora, G., Vitiello, G.: Socially assistive robotics combined with artificial intelligence for ADHD. In: 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC), pp. 1–6 (2021). https://doi.org/10.1109/CCNC49032.2021.9369633

  5. Battistoni, P., Di Gregorio, M., Romano, M., Sebillo, M., Vitiello, G., Solimando, G.: Sign language interactive learning - measuring the user engagement. In: Zaphiris, P., Ioannou, A. (eds.) HCII 2020. LNCS, vol. 12206, pp. 3–12. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50506-6_1

    Chapter  Google Scholar 

  6. Battistoni, P., Sebillo, M., Di Gregorio, M., Vitiello, G., Romano, M.: Prosign+ a cloud-based platform supporting inclusiveness in public communication. In: 2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC), pp. 1–5 (2020). https://doi.org/10.1109/CCNC46108.2020.9045191

  7. Belpaeme, T., Kennedy, J., Ramachandran, A., Scassellati, B., Tanaka, F.: Social robots for education: a review. Sci. Robot. 3(21), eaat5954 (2018)

    Google Scholar 

  8. Broadbent, E., Jayawardena, C., Kerse, N., Stafford, R., MacDonald, B.A.: Human-robot interaction research to improve quality of life in elder care-an approach and issues (2011)

    Google Scholar 

  9. Cantone, A.A., Mortezapour, A., Sebillo, M., Tortora, G., Vitiello, G.: Personalized IoT’s service providers: a neurocognitive approach to assess their usability (2023)

    Google Scholar 

  10. Cifuentes, C.A., Pinto, M.J., Céspedes, N., Múnera, M.C.: Social robots in therapy and care. Curr. Robot. Rep. 1, 59–74 (2020)

    Article  Google Scholar 

  11. Di Gregorio, M., Romano, M., Sebillo, M., Vitiello, G.: Dyslexeasy-app to improve readability through the extracted summary for dyslexic users, pp. 1–6 (2022). https://doi.org/10.1109/CCNC49033.2022.9700618

  12. Dobra, A.: General classification of robots. size criteria. In: 2014 23rd International Conference on Robotics in Alpe-Adria-Danube Region (RAAD), pp. 1–6 (2014). https://doi.org/10.1109/RAAD.2014.7002249

  13. Golnazarian, W., Hall, E.: Intelligent industrial robots (2002). https://doi.org/10.1201/9780203908587.ch6.5

  14. Gross, H.M., et al.: Robot companion for domestic health assistance: implementation, test and case study under everyday conditions in private apartments. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5992–5999. IEEE (2015)

    Google Scholar 

  15. Hammond, N.E., Spooner, A.J., Barnett, A.G., Corley, A., Brown, P., Fraser, J.F.: The effect of implementing a modified early warning scoring (MEWS) system on the adequacy of vital sign documentation. Aust. Crit. Care 26(1), 18–22 (2013)

    Article  Google Scholar 

  16. Çiğdem, S., Meidute-Kavaliauskiene, I., Yıldız, B.: Industry 4.0 and industrial robots: a study from the perspective of manufacturing company employees. Logistics 7(1), 17 (2023). https://doi.org/10.3390/logistics7010017

  17. Ismail, Z., Wan Ahmad, W.I., Hanin Hamjah, S., Astina, I.K.: The impact of population ageing: a review. Iran. J. Public Health 50(12), 2451–2460 (2021). https://doi.org/10.18502/ijph.v50i12.7927

    Article  Google Scholar 

  18. Jung, M., Lazaro, M.J.S., Yun, M.H.: Evaluation of methodologies and measures on the usability of social robots: a systematic review. Appl. Sci. 11(4), 1388 (2021). https://doi.org/10.3390/app11041388

    Article  Google Scholar 

  19. Kar, S.: Robotics in healthcare. In: 2019 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC), pp. 78–83 (2019). https://doi.org/10.1109/PEEIC47157.2019.8976668

  20. Köksal, Ö., Torun, G., Ahun, E., Sığırlı, D., Güney, S., Aydın, M.: The comparison of modified early warning score and glasgow coma scale-age-systolic blood pressure scores in the assessment of nontraumatic critical patients in emergency department. Niger. J. Clin. Pract. 19(6), 761–765 (2016)

    Article  Google Scholar 

  21. Le-Anh, T., De Koster, R.: A review of design and control of automated guided vehicle systems. Eur. J. Oper. Res. 171, 1–23 (2004). https://doi.org/10.1016/j.ejor.2005.01.036

    Article  MathSciNet  MATH  Google Scholar 

  22. Leonardsen, A.C.L., Hardeland, C., Helgesen, A.K., Bååth, C., Del Busso, L., Grøndahl, V.A.: The use of robotic technology in the healthcare of people above the age of 65-a systematic review. In: Healthcare, vol. 11, p. 904. MDPI (2023)

    Google Scholar 

  23. Łukasik, S., Tobis, S., Kropińska, S., Suwalska, A.: Role of assistive robots in the care of older people: survey study among medical and nursing students. J. Med. Internet Res. 22(8), e18003 (2020)

    Article  Google Scholar 

  24. Mahmoudi Asl, A., Molinari Ulate, M., Franco Martin, M., van der Roest, H.: Methodologies used to study the feasibility, usability, efficacy, and effectiveness of social robots for elderly adults: scoping review. J. Med. Internet Res. 24(8), e37434 (2022). https://doi.org/10.2196/37434

    Article  Google Scholar 

  25. Mahum, R., Shafique Butt, F., Ayyub, K., Islam, S., Nawaz, M., Abdullah, D.: A review on humanoid robots. Int. J. Adv. Appl. Sci. 4, 83–90 (2017). https://doi.org/10.21833/ijaas.2017.02.015

    Article  Google Scholar 

  26. Rocha, T.F.D., Neves, J.G., Viegas, K.: Modified early warning score: evaluation of trauma patients. Revista brasileira de enfermagem 69, 906–911 (2016)

    Google Scholar 

  27. Romano, M., Bellucci, A., Aedo, I.: Understanding touch and motion gestures for blind people on mobile devices. In: Abascal, J., Barbosa, S., Fetter, M., Gross, T., Palanque, P., Winckler, M. (eds.) INTERACT 2015. LNCS, vol. 9296, pp. 38–46. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22701-6_3

    Chapter  Google Scholar 

  28. Schaeffer, C., May, T.: Care-o-bot-a system for assisting elderly or disabled persons in home environments. In: Assistive Technology on the Threshold of the New Millenium, vol. 3 (1999)

    Google Scholar 

  29. Sánchez, H., Martínez, L.S., González, J.D.: Educational robotics as a teaching tool in higher education institutions: a bibliographical analysis. J. Phys. Conf. Ser. 1391(1), 012128 (2019). https://doi.org/10.1088/1742-6596/1391/1/012128

  30. Stuart, A., et al.: Loneliness in older people and COVID-19: applying the social identity approach to digital intervention design. Comput. Hum. Behav. Rep. 6, 100179 (2022). https://doi.org/10.1016/j.chbr.2022.100179

    Article  Google Scholar 

  31. Volkhardt, M., Schneemann, F., Gross, H.M.: Fallen person detection for mobile robots using 3D depth data. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics, pp. 3573–3578. IEEE (2013)

    Google Scholar 

  32. Weinrich, C., Vollmer, C., Gross, H.M.: Estimation of human upper body orientation for mobile robotics using an SVM decision tree on monocular images. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2147–2152. IEEE (2012)

    Google Scholar 

  33. Weinrich, C., Wengefeld, T., Schroeter, C., Gross, H.M.: People detection and distinction of their walking aids in 2D laser range data based on generic distance-invariant features. In: The 23rd IEEE International Symposium on Robot and Human Interactive Communication, pp. 767–773. IEEE (2014)

    Google Scholar 

Download references

Acknowledgement

We acknowledge financial support from the project PNRR MUR project PE0000013-FAIR.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marco Romano .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 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

Battistoni, P. et al. (2023). Using Artificial Intelligence and Companion Robots to Improve Home Healthcare for the Elderly. In: Gao, Q., Zhou, J., Duffy, V.G., Antona, M., Stephanidis, C. (eds) HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14055. Springer, Cham. https://doi.org/10.1007/978-3-031-48041-6_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-48041-6_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48040-9

  • Online ISBN: 978-3-031-48041-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics