Modelling patient-robot interaction dynamics (Game Theory)



Sponsor:

This work is supported by Science Foundation Ireland, grant number 09/RFP/ECE2376 and a John and Pat Hume scholarship from the National University of Ireland Maynooth.

Individuals:

Aodhan Coffey, Tomas Ward

Summary:

Designing suitable robotic controllers for automating movement-based rehabilitation therapy requires an understanding of the interaction between patient and therapist. Current approaches do not take into account the highly dynamic and interdependent nature of this relationship. We propose that a better understanding can be accomplished through framing the interaction as a problem in game theory. An agent-based model (ABM) (sometimes confused with the term multi-agent system or multi-agent simulation) is a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole.

Agents learn from experiences, and adapt their behaviors so they are better suited to their environment. As the models evolve, structures, patterns and behaviors emerge that were not explicitly programmed into the original models, but which instead surface through the agent interactions with each other and their environment. This paper advocates the use of such agent based models for analysing patient-therapist interactions with a view to designing more efficient and effective robotic controllers for automated therapeutic intervention in motor rehabilitation. The authors demonstrate in a simplified implementation the effectiveness of this approach through simulating known behavioral patterns observed in real patient-therapist interactions, such as learned dependency.



Papers (2011-2013):


Aodhan L. Coffey, Tomas E. Ward, Richard H. Middleton: Game Theory: A Potential Tool for the Design and Analysis of Patient-Robot Interaction Strategies. International Journal of Ambient Computing and Intelligence (IJACI), 3(3), 43-51. doi:10.4018/jaci.2011070106

Aodhan L. Coffey, Tomas E. Ward: A Sensor Glove System for Rehabilitation in Instrumental Activities of Daily Living. HCI (29) 2013: 135-139