SenseCare: Towards an Experimental Platform for Home-Based, Visualisation of Emotional States of People with Dementia

  • Felix Engel
  • Raymond BondEmail author
  • Alfie Keary
  • Maurice Mulvenna
  • Paul Walsh
  • Huiru Zheng
  • Haiying Wang
  • Ulrich Kowohl
  • Matthias Hemmje
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10084)


Analytics and visualisation of Big Data appearance is still a challenging task. In this paper, the management and visualisation of big data streams will be discussed at hand of data that comes into existence during the care of people with dementia in their own homes. Therein, basic requirements are explored towards the development of a data management, analytics and visualisation platform stemming from application scenarios in which various data streams are created, processed, analysed, visualised and stored for ad hoc or later reuse. The platform will be realised on open ICT standards, implemented within the EC co funded SenseCare project.


Information visualisation Interactive visualisation Emotional signals SenseCare platform Affective computing 



Open image in new windowThis publication has been produced in the context of the SenseCare project. This project has received funding from the European Union’s H2020 Programme under grant agreement No. 690862. However, this paper reflects only the author’s view and the European Commission is not responsible for any use that may be made of the information it contains.


  1. 1.
    Meiland, F., Davies, R., Moelaert, F., Mulvenna, M.D., Nugent, C., Dröes, R.-M.: Review of ICT-based services for identified unmet needs in people with dementia. Ageing Res. Rev. 6(3), 223–246 (2007)CrossRefGoogle Scholar
  2. 2.
    Walters, K., Iliffe, S., See Tai, S., Orrell, M.: Assessing needs from patient, carer and professional perspectives: the Camberwell assessment of need for the elderly people in primary care. Age Ageing 29, 505–510 (2000)CrossRefGoogle Scholar
  3. 3.
    Carswell, W., McCullagh, P., Augusto, J.C., Martin, S., Mulvenna, M.D., Zheng, H., Wang, H.Y., Wallace, J.G., McSorley, K., Taylor, B., Jeffers, P.: A review of the role of assistive technology for people with dementia in the hours of darkness. Technol. Health Care 17(4), 281–304 (2009)CrossRefGoogle Scholar
  4. 4.
    Takacs, B., Hanak, D.: A mobile system for assisted living with ambient facial interfaces. Int. J. Comput. Sci. Inf. Syst. 2(2), 33–50 (2007)Google Scholar
  5. 5.
    Mulvenna, M.D., Carswell, W., McCullagh, P.J., Augusto, J.C., Zheng, H., Jeffers, P., Wang, H.Y., Martin, S.: Visualization of data for ambient assisted living services. IEEE Commun. Mag. 49(1), 110–117 (2011)CrossRefGoogle Scholar
  6. 6.
    Walsh, L., Kealy, A., Loane, J., Doyle J., and Bond, R.: Inferring health metrics from ambient smart home data. In: IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Belfast, pp. 27–32 (2014)Google Scholar
  7. 7.
    Doyle, J., Walsh, L., Sassu, A., McDonagh. T.: Designing a wellness self-management tool for older adults: results from a field trial of YourWellness. In: Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare, pp. 134–141 (2014)Google Scholar
  8. 8.
    Consolvo, S., Klasnja, P., McDonald, D.W., Avrahami, D., Froehlich, J., LeGrand, L., Libby, R., Mosher, K., Landay. J.A.: Flowers or a robot army? Encouraging awareness & activity with personal, mobile displays. In: Proceedings of the 10th International Conference on Ubiquitous Computing (UbiComp 2008), pp. 54–63. ACM, New York (2008)Google Scholar
  9. 9.
    Nawroth, C., Schmedding, M., Brocks, H., Kaufmann, M., Fuchs, M., Hemmje, M.: Towards cloud-based knowledge capturing based on natural language processing. Procedia Comput. Sci. 68, 206–216 (2015)CrossRefGoogle Scholar
  10. 10.
    van den Broek, E.: Ubiquitous emotion-aware computing. Personal. Ubiquit. Comput. 17(1), 53–67 (2013)CrossRefGoogle Scholar
  11. 11.
    Picard, R.: Affective Computing. MIT Press, Cambridge (1997)Google Scholar
  12. 12.
    Emotient: Emotient API (2014). Accessed 12 Sep 2014
  13. 13.
    Intel Real Sense: Real Sense Architecture (2014). Accessed 30 Apr 2014
  14. 14.
    Affectiva: Affdex (2015). Accessed 07 May 2015
  15. 15.
    Shimmer: Shimmer Sensing (2014). Accessed 17 Apr 2014
  16. 16.
    Empatica: E4 Wristband (2015). Accessed 17 Apr 2015
  17. 17.
    Schuller, B., Eyben, F., Weninger, F.: OpenAudio, 09 March 2016. Accessed 09 Mar 2016
  18. 18.
    Emotiv: Emotiv EPOC, 05 February 2015. Accessed 05 Feb 2015
  19. 19.
    PSFK.COM: Kinect system reads emotions to help autistic children socialize (2014).!D1LyT. Accessed 17 Apr 2014
  20. 20.
    Metnitz, P.G.H., Lenz, K.: Patient data management systems in intensive care – the situation in Europe. Intense Care Med. 21(9), 703–715 (1995). ISSN: 1432-1238. SpringerCrossRefGoogle Scholar
  21. 21.
    Brooks, H., Kranstedt, A., Jäschke, G., Hemmje, M.: Modeling context for digital preservation. Stud. Comput. Intell. 260, 197–226 (2010)Google Scholar
  22. 22.
    Ming, X.G., Yan, J.Q., Wang, X.H., Li, S.N., Lu, W.F., Peng, Q.J., Ma, Y.S.: Collaborative process planning and manufacturing in product lifecycle management. Comput. Ind. 59(2–3), 154–166 (2008)CrossRefGoogle Scholar
  23. 23.
    Drake, G., Csipke, E., Wykes, T.: Assessing your mood online: acceptability and use of Moodscope. Psychol. Med. 7(7), 1455–1464 (2013)CrossRefGoogle Scholar
  24. 24.
    Bond, R.R., Zheng, H, Wang, H.Y., Mulvenna, M.D., McAllister, P., Delaney, K., Wlash, P., Keary, A., Riestra, R., Guaylupo, S., Hemmje, M., Becker, J., Engel, F.: SenseCare: using affective computing to manage and care for the emotional wellbeing of older people. In: EAI International Conference on Wearables in Healthcare (HealthWear), Budapest, 14–15 June 2016 Google Scholar
  25. 25.
    Bornschlegl, M.X., Berwind, K., Kaufmann, M., Engel, F.C., Walsh, P., Hemmje, M.L.: IVIS4BigData: a reference model for advanced visual interfaces supporting big data analysis in virtual research environments. In: Proceedings of IVIS4BigData: A Reference Model for Advanced Visual Interfaces Supporting Big Data Analysis in Virtual Research Environments (2016)Google Scholar

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Authors and Affiliations

  • Felix Engel
    • 1
  • Raymond Bond
    • 2
    Email author
  • Alfie Keary
    • 3
  • Maurice Mulvenna
    • 2
  • Paul Walsh
    • 3
    • 4
  • Huiru Zheng
    • 2
  • Haiying Wang
    • 2
  • Ulrich Kowohl
    • 5
  • Matthias Hemmje
    • 1
  1. 1.Research Institute for Telecommunication and CooperationDortmundGermany
  2. 2.Ulster UniversityNewtownabbeyNorthern Ireland
  3. 3.CIT InformaticsCork Institute of TechnologyCorkIreland
  4. 4.NSilico Life ScienceDublin 4Ireland
  5. 5.Faculty of Mathematics and Computer ScienceUniversity of HagenHagenGermany

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