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Review ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Robot. AI | doi: 10.3389/frobt.2019.00119

Computational Commensality: from theories to computational models for social food preparation and consumption in HCI

  • 1Istituto Italiano di Tecnologia, Italy
  • 2Department of Computer Science, Bioengineering, Robotics and Systems Engineering, School of Mathematical, Physical and Natural Sciences, University of Genoa, Italy
  • 3Amsterdam University of Applied Sciences, Netherlands
  • 4University of Genoa, Italy
  • 5School of Computer Science and Information Technology, University College Cork, Ireland

Food and eating are inherently social activities taking place, for example, around the dining
table at home, in restaurants, or in public spaces. Enjoying eating with others, often referred
to as “commensality”, positively affects mealtime in terms of, among other factors, food intake, food choice, and food satisfaction. In this paper we discuss the concept of “Computational Commensality”, that is, technology which computationally addresses various social aspects of food and eating. In the past few years, Human-Computer Interaction started to address how interactive technologies can improve mealtimes. However, the main focus has been made so far on improving the individual’s experience, rather than considering the inherently social nature of food consumption. In this survey, we first present research from the field of social psychology on the social relevance of Food- and Eating-related Activities (F&EA). Then, we review existing computational models and technologies that can contribute, in the near future, to achieve Computational Commensality. We also discuss the related research challenges and indicate future applications of such new technology that can potentially improve F&EA from the commensality perspective.

Keywords: commensality, Food, Food recognition, Well-being, social signal processing, embodied interfaces, augmented experience, HCI

Received: 02 Mar 2019; Accepted: 28 Oct 2019.

Copyright: © 2019 Niewiadomski, Ceccaldi, Huisman, Volpe and Mancini. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Dr. Radoslaw Niewiadomski, Istituto Italiano di Tecnologia, Genoa, Italy, radoslaw.niewiadomski@iit.it
Ms. Eleonora Ceccaldi, Department of Computer Science, Bioengineering, Robotics and Systems Engineering, School of Mathematical, Physical and Natural Sciences, University of Genoa, Genoa, Italy, eleonoraceccaldi@gmail.com
Dr. Gijs Huisman, Amsterdam University of Applied Sciences, Amsterdam, Netherlands, g.huisman@hva.nl
Prof. Gualtiero Volpe, University of Genoa, Genoa, 16126, Italy, gualtiero.volpe@unige.it
Dr. Maurizio Mancini, School of Computer Science and Information Technology, University College Cork, Cork, Ireland, m.mancini@cs.ucc.ie