Socio-Cognitive Engineering of a Robotic Partner for Child's Diabetes Self-Management - Neerincx, Mark A.; van Vught, Willeke; Blanson Henkemans, Olivier; Oleari, Elettra; Broekens, Joost; Peters, Rifca; Kaptein, Frank; Demiris, Yiannis; Kiefer, Bernd; Fumagalli, Diego; Bierman, Bert (Frontiers in Robotics and AI, 2019)
Social or humanoid robots do hardly show up in "the wild", aiming at pervasive human benefits such as child health. This paper presents the socio-cognitive engineering (SCE) methodology for the required field research & development of robots, focusing on the incremental development of a social robot and child-robot activities that support the daily diabetes management processes of children, aged between 7 and 14 years (i.e., supporting a healthy lifestyle). The SCE methodology helps to integrate into the human-agent/robot system: (a) theories, models and methods from different scientific disciplines, (b) technologies from different fields, (c) varying diabetes management practices, and (d) last but not least, the diverse individual and context-dependent needs of the patients and caregivers. The resulting system represents a new type of long-term human-robot partnerships with evolving collective intelligence. The current prototype is based on four human-robot partnership functions, a knowledge-base and interaction design for child's prolonged disease self-management. It has been developed and tested in three cycles, and proved to support the children on the three basic needs of the Self-Determination Theory: autonomy, competence and relatedness. To our knowledge, this is the first design & test of a robot system "in the wild" for prolonged "blended" care of children with a chronic disease, showing positive results in a 3 month evaluation period.