Advertisement

Toward Supporting Food Journaling Using Air Quality Data Mining and a Social Robot

  • Federica Gerina
  • Barbara Pes
  • Diego Reforgiato Recupero
  • Daniele RiboniEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11912)

Abstract

Unhealthy diet is a leading cause of health issues. A powerful means for monitoring and improving nutrition is keeping a food diary. Unfortunately, frail people such as the elderly have a hard time filling food diaries on a continuous basis due to forgetfulness or physical issues. For this reason, in this paper we investigate the integration of nutrition monitoring in a robotic platform. A machine learning module detects cooking activities based on air quality sensor data. When cooking is detected, a social robot interacts with the user to fill the food diary through a conversational interface. We report our experience on the development of a partial prototype of our system. Moreover, we illustrate the results of preliminary experiments with annotated sensor data gathered over one month from a real-world apartment.

Keywords

Healthcare Context-aware computing Social robots 

Notes

Acknowledgements

This research was partially funded by the EU’s Marie Curie training network PhilHumans - Personal Health Interfaces Leveraging HUman-MAchine Natural interactionS (grant number 812882).

References

  1. 1.
    Amft, O., Stäger, M., Lukowicz, P., Tröster, G.: Analysis of chewing sounds for dietary monitoring. In: Beigl, M., Intille, S., Rekimoto, J., Tokuda, H. (eds.) UbiComp 2005. LNCS, vol. 3660, pp. 56–72. Springer, Heidelberg (2005).  https://doi.org/10.1007/11551201_4CrossRefGoogle Scholar
  2. 2.
    Anzalone, S.M., Boucenna, S., Ivaldi, S., Chetouani, M.: Evaluating the engagement with social robots. Int. J. Soc. Robot 7(4), 465–478 (2015)CrossRefGoogle Scholar
  3. 3.
    Bemelmans, R., Gelderblom, G.J., Jonker, P., Witte, L.: Socially assistive robots in elderly care: a systematic review into effects and effectiveness. J. Am. Med. Dir. Assoc. 13(2), 114–120.e1 (2010)CrossRefGoogle Scholar
  4. 4.
    Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)CrossRefGoogle Scholar
  5. 5.
    Cordeiro, F., Bales, E., Cherry, E., Fogarty, J.: Rethinking the mobile food journal: exploring opportunities for lightweight photo-based capture. In: Proceedings of Conference on Human Factors in Computing Systems (CHI), pp. 3207–3216. ACM (2015)Google Scholar
  6. 6.
    DiFilippo, K.N., Huang, W.H., Andrade, J.E., Chapman-Novakofski, K.M.: The use of mobile apps to improve nutrition outcomes: a systematic literature review. J. Telemed. Telecare 21(5), 243–253 (2015)CrossRefGoogle Scholar
  7. 7.
    Frank, E., et al.: Weka-a machine learning workbench for data mining. In: Maimon, O., Rokach, L. (eds.) Data Mining and Knowledge Discovery Handbook. Springer, Boston (2009)Google Scholar
  8. 8.
    Mankoff, J., Hsieh, G., Hung, H.C., Lee, S., Nitao, E.: Using low-cost sensing to support nutritional awareness. In: Borriello, G., Holmquist, L.E. (eds.) UbiComp 2002. LNCS, vol. 2498, pp. 371–378. Springer, Heidelberg (2002).  https://doi.org/10.1007/3-540-45809-3_29CrossRefGoogle Scholar
  9. 9.
    Norvig, P., Russell, S.: Artificial Intelligence A Modern Approach. Prentice Hall Series in Artificial Intelligence. Prentice Hall, Upper Saddle River (2003)zbMATHGoogle Scholar
  10. 10.
    Vaufreydaz, D., Johal, W., Combe, C.: Starting engagement detection towards a companion robot using multimodal features. Robot Auton. Syst. 75, 4–16 (2016)CrossRefGoogle Scholar
  11. 11.
    Zhu, F., et al.: The use of mobile devices in aiding dietary assessment and evaluation. J. Sel. Topics Signal Process 4(4), 756–766 (2010)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Federica Gerina
    • 1
  • Barbara Pes
    • 1
  • Diego Reforgiato Recupero
    • 1
  • Daniele Riboni
    • 1
    Email author
  1. 1.Department of Mathematics and Computer ScienceUniversity of CagliariCagliariItaly

Personalised recommendations