Advertisement

An Integrated System for Improved Assisted Living of Elderly People

  • Imad Alex AwadaEmail author
  • Irina Mocanu
  • Alexandru Sorici
  • Adina Magda Florea
Chapter
Part of the Intelligent Systems Reference Library book series (ISRL, volume 170)

Abstract

The number of elderly people (aged 60 years or over) is increasing significantly. Moreover, this happens in the context of increasing well-being costs and decreasing caregiver availability. Therefore, technology must create assisted living solutions that support elderly in their daily activities and ensure their continuous health-monitoring, safety and social integration while maintaining an acceptable degree of independence. In this context we present the CAMI system—an intelligent system that provides health and home monitoring, supervised physical exercises and interaction between the user and the system is performed through a multimodal interface. The supervised physical exercises are recommended based on the current medical parameters of the user. The results performed by the user are presented in an interactive way using a feedback module. The multimodal interface accepts voice and gesture-based commands and is adapted to the device and to the user profile and preferences.

Keywords

Ambient assisted living Elderly people support Health monitoring Multimodal interface Supervised physical exercises User profile 

Notes

Acknowledgements

This work was supported by the following two programmes: Active and Assisted Living program through a grant of the Romanian National Authority for Scientific Research and Innovation, CCCDI—UEFISCDI, CAMI—“The Artificially intelligent ecosystem for self-management and sustainable quality of life in AAL”, project number AAL-2014-1-087 and National Research Grant PN-III-P2-2.1-PED-2016-1753.

References

  1. 1.
    Cayton, H.: The flat-pack patient? Creating health together. Patient Educ. Couns. J. 62, 288–290 (2006).  https://doi.org/10.1016/j.pec.2006.06.016CrossRefGoogle Scholar
  2. 2.
    Darwish, M., Senn, E., Lohr, C., Kermarrec, Y.: A comparison between ambient assisted living systems. In: 12th International Conference on Smart Homes and Health Telematics (ICOS), pp. 231–237. Denver, Colorado, USA,  https://doi.org/10.1007/978-3-319-14424-5_26 (2014)Google Scholar
  3. 3.
    Tazari, M.R., Furfari, F., Ramos, J.P.L., Ferro, E.: The persona service platform for AAL spaces. In: Handbook of Ambient Intelligence and Smart Environments, pp. 1171–1199. Springer (2010)Google Scholar
  4. 4.
    Lamprinakos, G., Kosmatos, E., Kaklamani, D., Venieris, I.: An integrated architecture for remote healthcare monitoring. In: Proceedings of the 14th Panhellenic Conference on Informatics, pp. 12–15. Tripoli, Greece,  https://doi.org/10.1109/pci.2010.20 (2010)
  5. 5.
    Active and Assisted Living Program: healthy@work, retrieved from the project page on the official AAL website. http://www.aal-europe.eu/projects/healthywork/. Visited on: 21 June 2018
  6. 6.
    Planinc, R., Hödlmoser, M., Kampel, M.: Enhancing the wellbeing at the workplace. In: The 7th International Conference on eHealth, Telemedicine, and Social Medicine (eTelemed), pp. 213–216. Lisbon, Portugal (2015)Google Scholar
  7. 7.
    Azevedo, C., Chesta, C., Coelho, J., Dimola, D., Duarte, C., Manca, M., Nordvik, J., Paterno, F., Sanders, A., Santoro, C.: Towards a platform for persuading older adults to adopt healthy behaviors. In: Orji, R., Reisinger, M., Busch, M., Dijkstra, A., Kaptein, M., Mattheiss, E. (eds.) Proceedings of the Second International Workshop on Personalization in Persuasive Technology, pp. 50–56. Amsterdam, Netherlands (2017)Google Scholar
  8. 8.
    Giannoglou, V., Smagas, K., Valari, E., Stylianidis, E.: Elders-up! an adaptive system for enabling knowledge transfer from senior adults to small companies. In: 22nd International Conference on Virtual System & Multimedia (VSMM), pp. 17–23, Kuala Lumpur, Malaysia.  https://doi.org/10.1109/vsmm.2016.7863163 (2016)
  9. 9.
    http://www.andonline.com/medical, visited on 29 June 2018
  10. 10.
    https://www.openhab.org, visited on 29 June 2018
  11. 11.
    http://www.docker.io, visited on 29 June 2018
  12. 12.
    https://www.rabbitmq.com, visited on 29 June 2018
  13. 13.
  14. 14.
    Sorici, A., Picard, G., Boissier, O., Florea, A.M.: Multi-agent based flexible deployment of context management in ambient intelligence applications. In: International Conference on Practical Applications of Agents and Multi-Agent Systems, pp. 225–239. Springer, Cham (2015)CrossRefGoogle Scholar
  15. 15.
    American Heart Association. Understanding blood pressure readings, June 2018. Retrieved from http://www.heart.org/HEARTORG/Conditions/HighBloodPressure/KnowYourNumbers/Understanding-Blood-Pressure-Readings_UCM_301764_Article.jsp, visited on 29 June 2018
  16. 16.
    Sorici, A., Picard, G., Boissier, O., Zimmermann, A., Florea, A.M.: CONSERT: applying semantic web technologies to context modeling in ambient intelligence. Comput. Electr. Eng. 44, 280–306 (2015)CrossRefGoogle Scholar
  17. 17.
    Trăscău, M., Sorici, A., Florea, A.M.: Detecting activities of daily living using the CONSERT engine. In: Novais, P., et al. (eds.) Ambient Intelligence—Software and Applications, 9th International Symposium on Ambient Intelligence (ISAmI2018), Advances in Intelligent Systems and Computing, vol. 806, pp. 94–102. Springer, Cham (2018)Google Scholar
  18. 18.
    https://pushbots.com, visited on 29 June 2018
  19. 19.
  20. 20.
    Stuckless, R.: Developments in real-time speech-to-text communication for people with impaired hearing. In: Ross, M. (ed.) Communication access for people with hearing loss, pp. 197–226. York Press, Baltimore, MD (1994)Google Scholar
  21. 21.
    Mocanu, I., Schipor, O.A.: A serious game for improving elderly mobility based on user emotional state. In: 13th eLearning and Software for Education Conference, vol. 2, pp. 487–494. Bucharest, Romania (2017)Google Scholar
  22. 22.
    Kinect for Windows SDK 2.0, https://www.microsoft.com/en-us/download/details.aspx?id=44561, visited on Nov 2017
  23. 23.
    Softbank robotics. Who is pepper? Retrieved from www.softbankrobotics.com/emea/en/robots/pepper, visited on 29 June 2018
  24. 24.
    Ghiță, Ș.A., Barbu, M.S., Gavril, A.F., Trăscău, M., Sorici, A., Florea, A.M.: User detection, tracking and recognition in robot assistive care scenarios. In: Giuliani, M., Assaf, T., Giannaccini, M. (eds.) Towards Autonomous Robotic Systems (TAROS2018), Lecture Notes in Computer Science, vol. 10965, pp. 271–283. Springer, Cham (2018)CrossRefGoogle Scholar
  25. 25.
    Awada, I.A., Codreanu, A., Mocanu, I., Florea, A.M., Apostu, M.: An adaptive multimodal interface to improve elderly people’s rehabilitation exercises. In: 13th eLearning and Software for Education Conference, vol. 2, pp. 41–47. Bucharest, Romania (2017)Google Scholar
  26. 26.
    Awada, I.A., Mocanu, I., Florea, A.M., Cramariuc, B.: Multimodal interface for elderly people. In: 21st International Conference on Control Systems and Computer Science (CSCS), pp. 536–541. IEEE, Bucharest, Romania (2017)Google Scholar
  27. 27.
    Awada, I.A., Mocanu, I., Florea, A.M.: Exploiting multimodal interfaces in eLearning systems. In: 14th eLearning and Software for Education Conference, vol. 2, pp. 174–181. Bucharest, Romania (2018)Google Scholar
  28. 28.
    Awada, I.A., Mocanu, I., Rusu, L., Arba, R., Florea, A.M., Cramariuc, B.: Enhancing the physical activity of older adults based on user profiles. In: 16th RoEduNet Conference: Networking in Education and Research (RoEduNet), pp. 120–125. IEEE, Targu Mures, Romania. ISSN: 2068-1038.  https://doi.org/10.1109/roedunet.2017.8123749 (2017)
  29. 29.
    Mocanu, I., Rusu, L., Arba, R., Marian, C.: A kinect based adaptive exergame. In: 12th International Conference on Intelligent Computer Communication and Processing, pp. 117–124. Cluj-Napoca, Romania,  https://doi.org/10.1109/iccp.2016.7737132 (2016)
  30. 30.
    Mocanu, I., Caciula, R., Gherman, L.: Improving physical activity through exergames. In: 14th eLearning and Software for Education Conference, vol. 2, pp. 225–232. Bucharest, Romania (2018)Google Scholar
  31. 31.
    Su, C.J., Chiang, C.Y., Huang, J.Y.: Kinect-enabled home-based rehabilitation system using dynamic time warping and fuzzy logic. Appl. Soft Comput 22, 652–666 (2014).  https://doi.org/10.1016/j.asoc.2014.04.020CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Imad Alex Awada
    • 1
    Email author
  • Irina Mocanu
    • 1
  • Alexandru Sorici
    • 1
  • Adina Magda Florea
    • 1
  1. 1.Computer Science DepartmentUniversity Politehnica of BucharestBucharestRomania

Personalised recommendations