Our research aims to develop interactive, social agents that can coach people to learn new tasks, skills, and habits. In this article, 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, N utri W alking , 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.

中文翻译：

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设计人工智能健康教练并研究其在促进定期有氧运动中的效用

我们的研究旨在开发可以指导人们学习新任务、技能和习惯的交互式社交代理。在本文中，我们专注于指导久坐、超重的人（即“受训者”）定期锻炼。我们采用自适应目标设置，智能健康教练在其中生成、跟踪和修改受训者的个性化锻炼目标。随着学员在培训计划中的进展，目标变得越来越困难。我们的方法是基于模型的——教练维护受训者有氧能力的参数化模型，从而推动其对受训者表现的期望。该模型会根据受训者与教练的互动不断进行修订。教练体现在智能手机应用程序中，N乌特里W行走，作为教练与学员互动的媒介。我们采用以任务为中心的评估方法来研究所提出的算法在促进定期有氧运动方面的效用。我们表明，我们的方法不仅可以使受训者计划适应具有不同能力的几个受训者，而且还可以适应受训者在开始更多锻炼时的能力如何提高。专家对教练选择的目标的评价高于其他可能的目标，这表明我们的方法与临床建议一致。此外，在一项针对久坐参与者的为期 6 周的观察性研究中，我们表明所提出的方法有助于增加每周进行的运动量。