Designing an AI Health Coach and Studying its Utility in Promoting Regular Aerobic Exercise

TL;DR

This paper presents an adaptive, model-based AI health coach integrated into a smartphone app that personalizes aerobic exercise goals to promote regular activity among sedentary individuals, showing promising results in a 6-week study.

Contribution

It introduces a novel adaptive goal-setting algorithm for an embodied AI health coach that personalizes exercise plans based on trainee progress and capability modeling.

Findings

The coach's goals align with clinical recommendations.

Participants increased weekly exercise volume.

The approach adapts to different trainee capabilities.

Abstract

Our research aims to develop interactive, social agents that can coach people to learn new tasks, skills, and habits. In this paper, we focus on coaching sedentary, overweight individuals (i.e., trainees) to exercise regularly. We employ adaptive goal setting in which the intelligent health coach generates, tracks, and revises personalized exercise goals for a trainee. The goals become incrementally more difficult as the trainee progresses through the training program. Our approach is model-based - the coach maintains a parameterized model of the trainee's aerobic capability that drives its expectation of the trainee's performance. The model is continually revised based on trainee-coach interactions. The coach is embodied in a smartphone application, NutriWalking, which serves as a medium for coach-trainee interaction. We adopt a task-centric evaluation approach for studying the utility of the proposed algorithm in promoting regular aerobic exercise. We show that our approach can adapt the trainee program not only to several trainees with different capabilities, but also to how a trainee's capability improves as they begin to exercise more. Experts rate the goals selected by the coach better than other plausible goals, demonstrating that our approach is consistent with clinical recommendations. Further, in a 6-week observational study with sedentary participants, we show that the proposed approach helps increase exercise volume performed each week.