Towards Dynamic Action Planning with user preferences in Automated Health Coaching

Health coaching is an evidence-based approach to help individuals adopt health behaviors such as physical activity (PA). However, human health coaching is limited by a lack of real-time data and scalability. In this paper, we present the architecture and functionality of a novel semi-automated health coach that we call BeSMART that automates the goal modification and dialogue functionalities of human health coaching using a commercial health tracker and mobile phone. Results from an acceptability study (N=10) indicate that users have difficulty fully completing all actions as initially planned. To build planning systems that can dynamically adapt action plans to such changes, we show that user preferences are vital, and that users find re-planning acceptable. Towards solving this problem, we extracted and categorized user preferences from health coaching sessions and propose extensions to Hierarchical Task Network (HTN) representations. When taking users personally re-planned activities into account, post-hoc analysis shows that users are much more likely to complete their overall PA goals.