Tue, Feb 19, 2019 @ 01:30 PM - 03:30 PM
Thomas Lord Department of Computer Science
Title: Towards Socially Assistive Robot Support Methods for Physical Activity Behavior Change
PhD Candidate: Katelyn Swift-Spong
Date, Time, and Location: Tuesday, February 19, 2019 at 1:30pm in RTH 406
Committee: Prof. Maja MatariÄ (chair), Prof. Stefanos Nikolaidis, and Prof. Elizabeth Zelinski
Socially Assistive Robot (SAR) systems have the potential to support the complex process of human behavior change by providing social support such as feedback and encouragement at opportune times. This dissertation presents a framework for SAR behavior change support in the context of physical activity behavior. This framework is designed around the goal of creating lasting behavior change that extends past the SAR interaction. Within this framework, the robot is equipped with one or more SAR physical activity behavior change support methods designed to affect a specific mechanism of behavior change.
This dissertation develops the design of SAR feedback, backstory, and messaging support methods for physical activity behavior change. These three methods were each designed to support a different mechanism of achieving behavior change by leveraging the robot\'s relational and support capabilities. Feedback was designed to support a user\'s beliefs about their ability to perform a physical activity task. Robot backstory was designed to increase the robot\'s ability to provide social support, and messaging was designed to increase the user\'s positive feelings towards the physical activity. These three support methods are evaluated in real-world physical activity domains with a fully autonomous SAR system. The feedback support method is evaluated in the domain of post-stroke rehabilitation, and the backstory and messaging support methods are evaluated in the domain of adolescent exercise.
Reminder and social reward decision making is also developed as a SAR physical activity behavior change support method using a model of SAR habit formation support. This model formalizes the SAR sequential decision making task of determining when to give reminders and social rewards towards the goal of supporting the formation of a new desired habit. Habits are formed when the occurrence of a cue is followed by a desired behavior, and that combination is reinforced repeatedly over time. The model of habit formation support enables a robot to intervene in this process. This model is evaluated in the domain of reducing older adult sedentary behavior through a two-week in-home SAR intervention. The robot was able to generate a high level of reminder adherence in this setting.
In this work, four SAR physical activity behavior change support methods were developed and evaluated in three different physical activity domains with fully autonomous SAR systems. This dissertation contributes to understanding the methods a robot could use to support behavior change in a variety of physical activity domains both in situ within the context of the behavior in everyday life and outside of that context.
Audiences: Everyone Is Invited
Contact: Lizsl De Leon