  Artificial intelligence (AI) and robotic coaches promise the improved
engagement of patients on rehabilitation exercises through social interaction.
While previous work explored the potential of automatically monitoring
exercises for AI and robotic coaches, the deployment of these systems remains a
challenge. Previous work described the lack of involving stakeholders to design
such functionalities as one of the major causes. In this paper, we present our
efforts on eliciting the detailed design specifications on how AI and robotic
coaches could interact with and guide patient's exercises in an effective and
acceptable way with four therapists and five post-stroke survivors. Through
iterative questionnaires and interviews, we found that both post-stroke
survivors and therapists appreciated the potential benefits of AI and robotic
coaches to achieve more systematic management and improve their self-efficacy
and motivation on rehabilitation therapy. In addition, our evaluation sheds
light on several practical concerns (e.g. a possible difficulty with the
interaction for people with cognitive impairment, system failures, etc.). We
discuss the value of early involvement of stakeholders and interactive
techniques that complement system failures, but also support a personalized
therapy session for the better deployment of AI and robotic exercise coaches.
