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.

翻译：摘要：个性化的锻炼方案对确保充足的身体活动至关重要，但制定这样的方案颇具挑战性，因为人们面临复杂的日程安排和多种考量因素，且制定过程通常需要与专家反复沟通。我们提出PlanFitting——一种辅助个性化锻炼规划的对话式人工智能系统。通过利用大语言模型的生成能力，PlanFitting使用户能够用自然语言描述各种约束条件和查询需求，从而在遵循基本原则的前提下，帮助用户创建并优化符合其具体情况的每周锻炼计划。通过一项用户研究（18名参与者使用PlanFitting生成个性化锻炼计划，并由3名专家规划师进行评估），我们验证了PlanFitting在生成个性化、可操作且基于证据的锻炼计划方面的潜力。本文进一步探讨了人工智能助手在制定更符合运动原则且兼顾个人限制条件方案时的未来设计机遇。