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AALADIN: Ambient Assisted Living Assistive Device for Internet

  • Priscila CedilloEmail author
  • Wilson Valdez
  • Andrés Córdova
Conference paper
  • 81 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1129)

Abstract

Accidents during elderly are one of the greatest geriatric syndromes due to the frequency with which they appear between patients. There are incidents that mark a milestone for acute and chronic deterioration in the health during old age. Among the instruments explored over time by the medical area in order to know the factors that lead to falls in elderly people, the Tinetti test is the most complete and validated measurement instrument. Tinetti is an observational scale that allows the evaluation by means of two sub-scales (i) the march (9 items) and (ii) the balance (13 items) in static position and when the patient is moving. Generally, this test is performed by specialized medical personnel (doctors or physiotherapists) and the acquisition of data used in each one of the items in this test is recorded manually. This paper presents the design and construction of an Assistive Technology Device, which supports medical personnel during the application of the balance sub-scale in the Tinetti test. This solution will consist of a carpet equipped with sensors that allows to know the position of the patient through heat maps and the body weight that is distributed in each area during the performance of the Tinetti test. In addition, it will allow the acquisition of data in a digital form, and since it is an object of the Internet of Things, it will allow the monitoring of the information coming from the test locally and remotely, as well as registering the information and making it available on the cloud.

Keywords

Tinetti test Ambient intelligent Assistive technology Ambient assisted living 

Notes

Acknowledgment

This development is part of the research projects called (i) Design of architectures and interaction models for assisted living environments aimed at older adults. Case study: playful and social environments, winner of the XVIII DIUC Call for Research Projects; and, (ii) Fog Computing applied to monitoring devices used in assisted living environments; Case study: platform for the elderly, winner of the XVII DIUC Call for Research Projects. Therefore, thanks to the sponsor “DIUC, Direccion de Investigación de la Universidad de Cuenca” because of the support during this work. Besides, very special thanks to the Education Coordination Zonal 6 and educational authorities of the participating educational institutions that enabled the execution of this research.

References

  1. 1.
    Vasilakos, A., Pedrycz, W.: Ambient Intelligence, Wireless Networking, And Ubiquitous Computing. Artech House Inc., Norwood (2006)Google Scholar
  2. 2.
    Tapia, D.I., De Salamanca, U.: An ambient intelligence based multi-agent system for Alzheimer health care. Int. J. Ambient. Comput. Intell. (IJACI) 1(1), 15–26 (2009)CrossRefGoogle Scholar
  3. 3.
    de Salud, M.: Manual del Modelo de Atención Integral del Sistema Nacional de Salud Familiar Comunitario e Intercultural (MAIS - FCI). Minist. Salud publica del Ecuador, pp. 64–72 (2012)Google Scholar
  4. 4.
    Cook, D.J., Augusto, J.C., Jakkula, V.R.: Ambient intelligence: technologies, applications, and opportunities. Pervasive Mob. Comput. 5(4), 277–298 (2009)CrossRefGoogle Scholar
  5. 5.
    McCreadie, C., Tinker, A.: The acceptability of assistive technology to older people. Ageing Soc. 25(1), 91–110 (2005)CrossRefGoogle Scholar
  6. 6.
    Cowan, D.D., Turner-smith, D.A., Engineering, C.O.R.: The role of assistive technology in alternative models of care for older people. Res. HMSO 2, 325–346 (1999)Google Scholar
  7. 7.
    World Health Organization: Assistive Technology. http://www.who.int/mediacentre/factsheets/assistivetechnology/%0Aen/
  8. 8.
    Roelands, M., Van Oost, P., Buysse, A., Depoorter, A.: Awareness among community-dwelling elderly of assistive devices for mobility and self-care and attitudes towards their use. Soc. Sci. Med. 54(9), 1441–1451 (2002)CrossRefGoogle Scholar
  9. 9.
    ITU: The Internet of Things. Itu Internet Rep., p. 212 (2005)Google Scholar
  10. 10.
    Domingo, M.C.: An overview of the Internet of Things for people with disabilities. J. Netw. Comput. Appl. 35(2), 584–596 (2012)CrossRefGoogle Scholar
  11. 11.
    Tinetti, M.E.: Preventing falls in elderly persons. N. Engl. J. Med. 348, 42–49 (2003)CrossRefGoogle Scholar
  12. 12.
    Nevitt, M.C., Cummings, S.R., Hudes, E.S.: Risk factors for injurious falls: a prospective study. J. Gerontol. 46(5), M164–M170 (1991)CrossRefGoogle Scholar
  13. 13.
    Sattin, R.W.: Falls among older persons: a public health perspective. Annu. Rev. Public Health 79, 489–508 (1992)CrossRefGoogle Scholar
  14. 14.
    Persons, O.: Risk factors for serious injury during falls by older persons in the community. J. Am. Geriatr. Soc. 43, 1214–1221 (1995)CrossRefGoogle Scholar
  15. 15.
    Tinetti, M.E., Speechley, M., Ginter, S.F.: Risk factors for falls among elderly persons living in the community. N. Engl. J. Med. 319(26), 1701–1707 (1988)CrossRefGoogle Scholar
  16. 16.
    Nevitt, M.C., Cummings, S.R., Kidd, S., Black, D.: Risk factors for recurrent nonsyncopal falls: a prospective study. JAMA 261(18), 2663–2668 (1989)CrossRefGoogle Scholar
  17. 17.
    Tinetti, M.E.: Performance-oriented assessment of mobility problems in elderly patients (1986)Google Scholar
  18. 18.
    Raîche, M., Hébert, R., Prince, F., Corriveau, H.: Screening older adults at risk of falling with the Tinetti balance scale. Lancet 356(9234), 1001–1002 (2000)CrossRefGoogle Scholar
  19. 19.
    Panella, L., Tinelli, C., Buizza, A., Lombardi, R., Gandolfi, R.: Towards objective evaluation of balance in the elderly : validity and reliability of a measurement instrument applied to the Tinetti test. Int. J. Rehabil. Res. 31, 65–72 (2008)Google Scholar
  20. 20.
    Ballesteros, J., Urdiales, C., Martinez, A.B., Tirado, M.: Online estimation of rollator user condition using spatiotemporal gait parameters, pp. 3180–3185 (2016)Google Scholar
  21. 21.
    Ballesteros, J., Urdiales, C., B. Martinez, A., Tirado, M.: Automatic assessment of a rollator-user’s condition during rehabilitation using the i-Walker platform 4320(c) (2017)Google Scholar
  22. 22.
    Bruno, B., Christophe, B., Véronique, F., Bart, J.: A preliminary study of the integration of specially developed serious games in the treatment of hospitalized elderly patients (2017)Google Scholar
  23. 23.
    Giansanti, D., Member, I., Tiberi, Y., Maccioni, G., Member, I.: The Codivilla-Spring for daily activity monitoring, pp. 4720–4723 (2008)Google Scholar
  24. 24.
    Jaume-i-capó, A., Martínez-bueso, P., Moyà-alcover, B., Varona, J.: Interactive rehabilitation system for improvement of balance therapies in people with cerebral palsy. IEEE Trans. Neural Syst. Rehabil. Eng. 22(2), 419–427 (2014)CrossRefGoogle Scholar
  25. 25.
    Pina, J.A.L.: Análisis psicométrico de la escala de marcha y equilibrio de Tinetti con el modelo de Rasch. Fisioterapia 31(5), 192–202 (2009)CrossRefGoogle Scholar
  26. 26.
    Conroy, S., et al.: A multicentre randomised controlled trial of day hospital-based falls prevention programme for a screened population of community-dwelling older people at high risk of falls. Age Ageing 39(6), 704–710 (2010)CrossRefGoogle Scholar
  27. 27.
    Blank, W.A., et al.: An interdisciplinary intervention to prevent falls in community-dwelling elderly persons: protocol of a cluster-randomized trial [PreFalls]. BMC Geriatr. 11, 7 (2011)CrossRefGoogle Scholar
  28. 28.
    de Vries, O.J., et al.: Multifactorial intervention to reduce falls in older people at high risk of recurrent falls: a randomized controlled trial reducing falls in older people at high risk. JAMA Intern. Med. 170(13), 1110–1117 (2010)CrossRefGoogle Scholar
  29. 29.
    Paunovic, N., Kova, J., Rešetar, I.: A methodology for testing complex professional electronic systems *. Serb. J. Electr. Eng. 9(1), 71–80 (2012)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Priscila Cedillo
    • 1
    Email author
  • Wilson Valdez
    • 1
  • Andrés Córdova
    • 1
  1. 1.Computer Science DepartmentUniversity of CuencaCuencaEcuador

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