Socio-Cognitive Engineering of a Robotic Partner for Child’s Diabetes Self-Management
article
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.
Topics
TNO Identifier
870022
Source
Frontiers in Robotics and AI, 6(118)