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Combinations of Modalities for the Words Learning Memory Test Implemented on Tablets for Seniors

  • Erika Hernández-Rubio
  • Amilcar Meneses-ViverosEmail author
  • Erick Mancera-Serralde
  • Javier Flores-Ortiz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9754)

Abstract

Mnesic problems in older adults is a global health problem. Some proposals have been made to support health care in older adults using mobile technologies. In particular,there are analysis and design of mobile applications focusing on the elderly to apply memory tests Luria. For example, in word learning test, multiple words or numerical figures unraleted are shown to the patient. The number of item exceed the numer that the patient can remember. Usually the serie consist of ten or twelve words or numerical digits. After this task, the patient is asked to repeat the series in any order. In one hand, the physical deterioration of the elderly makes it difficult the usability of the user interface of mobile applications. These deteriorations can be auditory, visual and motor. They are particular to each elderly. For this reason, a traditional user interface loses effectiveness when it has interaction with older people. In another hand, some studies suggest that Tablets are the best mobile devices for older adults, because the size of their screen and usability of their user interface. However, tablets have different modes of interaction and it is not yet clear how the elderly respond to them. One solution to this problem is to provide different modalities for interaction. This modalities they must be presents in applications for tablets. In this work, we present the implementation of the test world learning Luria memory test. And we implemented several combinations of modalities for the test. Finally we present the result of interaction with the older adults.

Keywords

Mobile Device Mobile Application Word Learn Multimodal Interface Prototype Design 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Czaja, S., Beach, S., Charness, N., Schulz, R.: Older adults and the adoption of healthcare technology: opportunities and challenges. Technologies for active aging. International Perspectives on Aging, pp. 27–46. Springer, New York (2013)CrossRefGoogle Scholar
  2. 2.
    Pak, R., McLaughlin, A.: Designing Displays for Older Adults. CRC Press, Boca Raton (2010)CrossRefGoogle Scholar
  3. 3.
    Fisk, A.D., Rogers, W.A., Charness, N., Czaja, S.J., Sharit, J.: Designing for Older Adults: Principles and Creative Human Factors Approaches. CRC Press, Boca Raton (2009)CrossRefGoogle Scholar
  4. 4.
    Yamagata, C., Kowtko, M., Coppola, J.F., Joyce, S.: Mobile app development and usability research to help Dementia and Alzheimer patients. In: Systems, Applications and Technology Conference (LISAT), 2013 IEEE Long Island, pp. 1–6. IEEE (2013)Google Scholar
  5. 5.
    Mandala, P.K., Saharana, S., Khana, S.A., Jamesa, M.: Apps for dementia screening: a cost-effective and portable solution. J. Alzheimers Disease 47, 869–872 (2015)CrossRefGoogle Scholar
  6. 6.
    Pereira, C., Almeida, N., Martins, A.I., Silva, S., Rosa, A.F., Oliveira e Silva, M., Teixeira, A.: Evaluation of complex distributed multimodal applications: evaluating a telerehabilitation system when it really matters. In: Zhou, J., Salvendy, G. (eds.) ITAP 2015. LNCS, vol. 9194, pp. 146–157. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  7. 7.
    Demiris, G., Rantz, M.J., Aud, M.A., Marek, K.D., Tyrer, H.W., Skubic, M., Hussam, A.A.: Older adults’ attitudes towards and perceptions of “smart home” technologies: a pilot study. Med. Inform. Internet Med. 29(2), 87–94 (2004)CrossRefGoogle Scholar
  8. 8.
    Demongeot, J., Virone, G., Duchêne, F., Benchetrit, G., Hervé, T., Noury, N., Rialle, V.: Multi-sensors acquisition, data fusion, knowledge mining and alarm triggering in health smart homes for elderly people. Comptes Rendus Biologies 325(6), 673–682 (2002)CrossRefGoogle Scholar
  9. 9.
    Boletsis, C., McCallum, S., Landmark, B.F.: The use of smartwatches for health monitoring in home-based dementia care. In: Zhou, J., Salvendy, G. (eds.) ITAP 2015. LNCS, vol. 9194, pp. 15–26. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  10. 10.
    Sawyer, P., Sutcliffe, A., Rayson, P., Bull, C.: Dementia and social sustainability: challenges for software engineering (2015)Google Scholar
  11. 11.
    Span, M., Hettinga, M., Vernooij-Dassen, M., Eefsting, J., Smits, C.: Involving people with dementia in the development of supportive it applications: a systematic review. Ageing Res. Rev. 12(2), 535–551 (2013)CrossRefGoogle Scholar
  12. 12.
    Novitzky, P., Smeaton, A.F., Chen, C., Irving, K., Jacquemard, T., O’Brolcháin, F., O’Mathúna, D., Gordijn, B.: A review of contemporary work on the ethics of ambient assisted living technologies for people with dementia. Sci. Eng. Ethics 21(3), 707–765 (2015)CrossRefGoogle Scholar
  13. 13.
    Ancient, C., Good, A., Wilson, C., Fitch, T.: Can Ubiquitous devices utilising reminiscence therapy be used to promote well-being in Dementia patients? An exploratory study. In: Stephanidis, C., Antona, M. (eds.) UAHCI 2013, Part III. LNCS, vol. 8011, pp. 426–435. Springer, Heidelberg (2013)Google Scholar
  14. 14.
    Miranda, J.A.H., Hernàndez Rubio, E., Meneses Viveros, A.: Analysis of luria memory tests for development on mobile devices. In: Duffy, V.G. (ed.) DHM 2014. LNCS, vol. 8529, pp. 546–557. Springer, Heidelberg (2014)Google Scholar
  15. 15.
    Lund, H.H.: Play for the elderly - effect studies of playful technology. In: Zhou, J., Salvendy, G. (eds.) ITAP 2015. LNCS, vol. 9194, pp. 500–511. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  16. 16.
    Oviatt, S.: Ten myths of multimodal interaction. Commun. ACM 42(11), 74–81 (1999)CrossRefGoogle Scholar
  17. 17.
    Turk, M.: Multimodal interaction: a review. Pattern Recogn. Lett. 36, 189–195 (2014)CrossRefGoogle Scholar
  18. 18.
    Oviatt, S., Coulston, R., Lunsford, R.: When do we interact multimodally?: cognitive load and multimodal communication patterns. In: Proceedings of the 6th International Conference on Multimodal Interfaces, pp. 129–136. ACM (2004)Google Scholar
  19. 19.
    Bush, E.: The use of human touch to improve the well-being of older adults a holistic nursing intervention. J. Holist. Nurs. 19(3), 256–270 (2001)CrossRefGoogle Scholar
  20. 20.
    Teixeira, V., Pires, C., Pinto, F., Freitas, J., Dias, M.S., Rodrigues, E.M.: Towards elderly social integration using a multimodal human-computer interface. In: Proceeding International Living Usability Lab Workshop on AAL Latest Solutions, Trends and Applications, AAL (2012)Google Scholar
  21. 21.
    Hackney, M.E., Hall, C.D., Echt, K.V., Wolf, S.L.: Multimodal exercise benefits mobility in older adults with visual impairment: a preliminary study. J. Aging Phys. Act. 23(4), 630–639 (2015)CrossRefGoogle Scholar
  22. 22.
    Patil, R., Uusi-Rasi, K., Tokola, K., Karinkanta, S., Kannus, P., Sievänen, H.: Effects of a multimodal exercise program on physical function, falls, and injuries in older women: a 2-year community-based, randomized controlled trial. J. Am. Geriatrics Soc. 63(7), 1306–1313 (2015)CrossRefGoogle Scholar
  23. 23.
    Sixsmith, A., Johnson, N.: A smart sensor to detect the falls of the elderly. IEEE Pervasive Comput. 3(2), 42–47 (2004)CrossRefGoogle Scholar
  24. 24.
    Sorwar, G., Hasan, R.: Smart-tv based integrated e-health monitoring system with agent technology. In: 26th International Conference on Advanced Information Networking and Applications Workshops (WAINA), pp. 406–411. IEEE (2012)Google Scholar
  25. 25.
    Aal, K., Ogonowski, C., von Rekowski, T., Wieching, R., Wulf, V.: A Fall Preventive iTV Solution for Older Adults. Siegen, Germany (2014)Google Scholar
  26. 26.
    Li, R., Zhu, X., Yin, S., Niu, Y., Zheng, Z., Huang, X., Wang, B., Li, J., et al.: Multimodal intervention in older adults improves resting-state functional connectivity between the medial prefrontal cortex and medial temporal lobe. Front Aging Neurosci. 6, 39 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Erika Hernández-Rubio
    • 1
  • Amilcar Meneses-Viveros
    • 2
    Email author
  • Erick Mancera-Serralde
    • 3
  • Javier Flores-Ortiz
    • 3
  1. 1.Instituto Politécnico NacionalSEPI-ESCOMMéxico D.F.Mexico
  2. 2.Departamento de ComputaciónCINVESTAV-IPNMéxico D.F.Mexico
  3. 3.School of ComputingInstituto Politeécnico NacionalMéxico D.F.Mexico

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