PlanFitting: Tailoring Personalized Exercise Plans with Large Language
  Models
Donghoon Shin Gary Hsieh Young-Ho Kim
A personally tailored exercise regimen is crucial to ensuring sufficient
physical activities, yet challenging to create as people have complex schedules
and considerations and the creation of plans often requires iterations with
experts. We present PlanFitting, a conversational AI that assists in
personalized exercise planning. Leveraging generative capabilities of large
language models, PlanFitting enables users to describe various constraints and
queries in natural language, thereby facilitating the creation and refinement
of their weekly exercise plan to suit their specific circumstances while
staying grounded in foundational principles. Through a user study where
participants (N=18) generated a personalized exercise plan using PlanFitting
and expert planners (N=3) evaluated these plans, we identified the potential of
PlanFitting in generating personalized, actionable, and evidence-based exercise
plans. We discuss future design opportunities for AI assistants in creating
plans that better comply with exercise principles and accommodate personal
constraints.