skip to main content
10.1145/3240508.3240598acmconferencesArticle/Chapter ViewAbstractPublication PagesmmConference Proceedingsconference-collections
research-article

Personalized Serious Games for Cognitive Intervention with Lifelog Visual Analytics

Authors Info & Claims
Published:15 October 2018Publication History

ABSTRACT

This paper presents a novel serious game app and a method to cre- ate and integrate personalized game content based on lifelog visual analytics. The main objective is to extract personalized content from visual lifelogs, integrate it into mobile games, and evaluate the effect of personalization on user experience. First, a suite of visual analysis methods is proposed to extract semantic informa- tion from visual lifelogs and discover the association among the lifelog entities. The outcome is dataset that contains augmented and personal lifelog images. Next, a mobile game app is developed that makes use of the dataset as game content. Finally, an experiment is conducted to evaluate user gameplay behaviors in the wild over three months, where a mixture of generic and personalized game content is deployed. It is observed that user adherence is heightened by personalized game content as compared to generic content. Also observed is a higher enjoyment level in personalized than generic game content. The result provides the first empirical evidence of the effect of personalized games on user adherence and preference for cognitive intervention. This work paves the way for effective cognitive training with user-generated content.

References

  1. J. A. Anguera, J. Boccanfuso, J. L. Rintoul, O. Al-Hashimi, F. Faraji, J. Janowich, E. Kong, Y. Larraburo, C. Rolle, E. Johnston, and A. Gazzaley. Video game training enhances cognitive control in older adults. Nature, 510(97--101), 2013.Google ScholarGoogle Scholar
  2. J. A. Anguera and A. Gazzaley. Video games, cognitive exercises, and hte enhancement of cognitive abilities. Current Opinion in Behavioral Sciences, 4:160--165, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  3. P. Belchior, M.Marsiske, S. Sisco, A. Yam, and W. Mann. Older adults' engagement with a video game training program. Act. Adapt. Aging, 36:269--279, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  4. A. Bermingham, J. O'Rourke, C. Gurrin, R. Collins, K. Irving, and A. F. Smeaton. Automatically recommending multimedia content for use in group reminiscence therap. In MIIRH'13, pages 49--58, New York, NY, USA, 2013. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. E. Berry, N. Kapur, L. Williams, S. Hodges, P. Watson, G. Smyth, J. Srinivasan, R. Smith, B. Wilson, and K. Wood. The use of a wearable camera, sensecam, as a pictorial diary to improve autobiographical memory in a patient with limbic encephalitis: A preliminary report. Neuropsychol Rehabil, 17(4--5):582--601, 2007.Google ScholarGoogle Scholar
  6. K. A. Blocker, T. J. Wright, and W. R. Boot. Gaming preferences of aging generations. Gerontechnology, 12(3):174--184, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  7. M. Bolanos, M. Dimiccoli, and P. Radeva. Toward storytelling from visual lifelogging: An overview. IEEE Trans. Human--Mach. Syst., 47:77--90, 2017.Google ScholarGoogle Scholar
  8. W. R. Boot, D. Souders, N. Charness, K. Blocker, N. Roque, and T. Vitale. The gamification of cognitive training: Older adults' perceptions of and attitudes toward digital game-based interventions. In J. Zhou and G. Salvendy, editors, Lecture Notes in Computer Science, volume 9754 of Human Aspects of IT for the Aged Population. Design for Aging, ITAP 2016. Springer, Cham, 2016.Google ScholarGoogle Scholar
  9. Y. Chen and G. J. Jones. Augmenting human memory using personal lifelogs. In AH'10. ACM, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. M. Cotelli, R. Manenti, O. Zanetti, and C. Miniussi. Non-pharmacological intervention for memory decline. Frontiers in Human Neuroscience, 6:No. 46, 2012.Google ScholarGoogle Scholar
  11. M. Csikszentmihalyi. Flow: The psychology of the optimal experience. New York: Harper & Row., 1990.Google ScholarGoogle Scholar
  12. J. R. Finley, W. F. Brewer, and A. S. Benjamin. The effects of end-of-day picture review and a sensor-based picture capture procedure on autobiographical memory using sensecam. Memory, 19(7):796--807, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  13. A. Garcia del Molino. First person view video summarization subject to the user needs. In MM '16, pages 1440--1444. ACM, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. N. J. Gates and P. Sachdev. Is cognitive training an effective treatment for preclinical and early alzheimer's disease? Journal of Alzheimer's Disease, 42:S551--S559, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  15. G. Gowans, J. Campbell, N. Alm, R. Dye, A. Astell, and M. Ellis. Designing a multimedia conversation aid for reminiscence therapy in dementia care environments. CHI EA '04, pages 825--836, New York, NY, USA, 2004. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition. In CVPR' 16, pages 770--778.Google ScholarGoogle Scholar
  17. G. Kim, L. Sigal, and E. Xing. Joint summarization of large-scale collections of web images and videos for storyline reconstruction. In CVPR, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. A. M. Kueider, J. M. Parisi, A. L. Gross, and G. W. Rebok. Computerized cognitive training with older adults: A systematic review. PLoS ONE, 7(7):e40588, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  19. A. Lampit, H. Hallock, and M. Valenzuela. Computerized cognitive training in cognitively healthy older adults: A systematic review and meta-analysis of effect modifiers. PLOS Medicine, 11(11):e1001756, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  20. M. Lee and K. Dey. Providing good memory cues for people with episodic memory impairment. In ASSETS'07, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollar, and L. Zitnick. Microsoft coco: Common objects in context. In ECCV'14.Google ScholarGoogle Scholar
  22. Z. Lu and K. Grauman. Story-driven summarization for egocentric video. 2013.Google ScholarGoogle Scholar
  23. H. W. Mahncke, B. B. Connor, J. Appelman, O. N. Ahsanuddin, J. L. Hardy, R. A. Wood, N. M. Joyce, T. Boniske, S. M. Atkins, and M. M. Merzenich. Memory enhancement in healthy older adults using a brain plasticity-based training program: A randomized, controlled study. PNAS, 103(33):12523--28, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  24. V. Manera, G. Ben-Sadoun, and T. Aalbers. Recommendations for the use of serious games in neurodegenerative disorders: 2016 delphi panel. Frontiers in Psychology, 8:1243:1--10, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  25. A. McLaughlin, M. Gandy, J. Allaire, and L. Whitlock. Putting fun into aging? overcoming usability and motivational issues in video games for older adults. Ergonomics in Design, 20(13--20), 2012.Google ScholarGoogle Scholar
  26. A. Mora, C. González, and J. Arnedo-Moreno. Gamification of cognitive training: A crowdsourcing- inspired approach for older adults. In Interacción '16, page Article No. 5, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. A. C. Oei and M. D. Patterson. Enhancing cognition with video games: A multiple game training study. PLOS ONE, 8(3):e58546, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  28. G. Oliveira-Barra, M. Bola nos, E. Talavera, A. Due nas, O. Gelonch, and M. Garolera. Serious games application for memory training using egocentric images. Sept. 11--15 2017.Google ScholarGoogle Scholar
  29. C. Peretz, A. D. Korczyn, E. Shatil, V. Aharonson, S. Birnboim, and N. Giladi. Computer-based, personalized cognitive training versus classical computer games: A randomized double-blind prospective trial of cognitive stimulation. Neruoepidemiology, 36:91--99., 2011.Google ScholarGoogle ScholarCross RefCross Ref
  30. V. Pieramico, R. Esposito, S. Cesinaro, V. Frazzini, and S. L. Sensi. Effects of non-pharmacological or pharmacological interventions on cognition and brain plasticity of aging individuals. Front in Syst Neurosci, 8:153: 1--10, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  31. S. Ren, K. He, R. Girshick, and J. Sun. Faster r-cnn: Towards real-time object detection with region proposal networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(6):1137 -- 1149, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. J. P. Salmon, S. M. Dolan, R. S. Drake, G. C. Wilson, R. M. Klein, and G. A. Eskes. A survey of video game preferences in adults: Building better games for older adults. Entertainment Computing, 21:45--64, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  33. V. Sarne-Fleischmann, N. Tractinsky, T. Dwolatzky, and I. Rief. Personalized reminiscence therapy for patients with alzheimer's disease using a computerized system. In PETRA '11, pages 48:1--48:4. ACM, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. A. Sellen and S. Whittaker. Beyond total capture: A constructive critique of lifelogging. Communications of the ACM, 53(5):70--77, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. E. Shatil. Does combined cognitive training and physical activity training enhance cognitive abilities more than either alone? a four-condition randomized controlled trial among healthy older adults. Front. Aging Neurosci., 5:8:1--12, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  36. E. Shatil, A. Metzer, O. Horvitz, and A. Miller. Home-based personalized cognitive training in ms patients: A study of adherence and cognitive performance. NeuroRehabilitation, 26:143--153, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  37. A. R. Silva, S. Pinho, L. M. Macedo, and C. J. Moulin. Benefits of sensecam review on neuropsychological test performance. Am J Prev Med, 44(3):302--307, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  38. P. Siriaraya and C. S. Ang. Recreating living experiences from past memories through virtual worlds for people with dementia. In CHI'14, pages 3977--3986, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. V. Subbaraju, Q. Xu, B. Mandal, L. Li, and J.-H. Lim. An empirical approach for automatic face clustering on personal lifelogging images. In ICSIP'17, pages 127--131.Google ScholarGoogle Scholar
  40. C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi. Inception-v4, inception-resnet and the impact of residual connections on learning. In AAAI'17, pages 4278--4284.Google ScholarGoogle Scholar
  41. P. Wang and A. F. Smeaton. Using visual lifelogs to automatically characterize everyday activities. Information Sciences, 230:147--161, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. S. L. Willis, S. L. Tennstedt, M. Marsiske, K. Ball, J. Elias, K. M. Koepke, J. N. Morris, G. W. Rebok, F. W. Unverzagt, A. M. Stoddard, and E. Wright. Long-term effects of cognitive training on everyday functional outcomes in older adults. JAMA, 296(23):2805--2814, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  43. Q. Xu, V. Subbaraju, A. G. del Molino, J. Lin, F. Fang, J. Lim, L. Li, and V. Chandrasekhar. Visualizing personal lifelog data for deeper insights at the ntcir-13 lifelog-2 task. In NTCIR17, pages 33--39, 2017.Google ScholarGoogle Scholar

Index Terms

  1. Personalized Serious Games for Cognitive Intervention with Lifelog Visual Analytics

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          MM '18: Proceedings of the 26th ACM international conference on Multimedia
          October 2018
          2167 pages
          ISBN:9781450356657
          DOI:10.1145/3240508

          Copyright © 2018 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 15 October 2018

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          MM '18 Paper Acceptance Rate209of757submissions,28%Overall Acceptance Rate995of4,171submissions,24%

          Upcoming Conference

          MM '24
          MM '24: The 32nd ACM International Conference on Multimedia
          October 28 - November 1, 2024
          Melbourne , VIC , Australia

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader