Robotic systems can enhance the amount and repeatability of physically guided motor training. Yet their real-world adoption is limited, partly due to non-intuitive trainer/therapist-trainee/patient interactions. To address this gap, we present a haptic teleoperation system for trainers to remotely guide and monitor the movements of a trainee wearing an arm exoskeleton. The trainer can physically interact with the exoskeleton through a commercial handheld haptic device via virtual contact points at the exoskeleton's elbow and wrist, allowing intuitive guidance. Thirty-two participants tested the system in a trainer-trainee paradigm, comparing our haptic demonstration system with conventional visual demonstration in guiding trainees in executing arm poses. Quantitative analyses showed that haptic demonstration significantly reduced movement completion time and improved smoothness, while speech analysis using large language models for automated transcription and categorization of verbal commands revealed fewer verbal instructions. The haptic demonstration did not result in higher reported mental and physical effort by trainers compared to the visual demonstration, while trainers reported greater competence and trainees lower physical demand. These findings support the feasibility of our proposed interface for effective remote human-robot physical interaction. Future work should assess its usability and efficacy for clinical populations in restoring clinicians' sense of agency during robot-assisted therapy.

翻译：机器人系统能够增强物理引导运动训练的强度与可重复性。然而，其在现实世界中的应用仍受限制，部分原因在于训练师/治疗师与受训者/患者之间的交互不够直观。为弥补这一不足，我们提出了一种触觉遥操作系统，使训练师能够远程引导和监控穿戴上肢外骨骼的受训者动作。训练师可通过商用手持触觉设备，经由外骨骼肘部和腕部的虚拟接触点进行物理交互，从而实现直观引导。三十二名参与者在训练师-受训者范式下测试了该系统，将我们的触觉演示系统与传统视觉演示在引导受训者执行手臂姿势方面进行了对比。定量分析表明，触觉演示显著缩短了动作完成时间并提升了运动平滑度，而基于大型语言模型的语音分析（用于自动转录和分类口头指令）则显示所需口头指示更少。与视觉演示相比，触觉演示并未导致训练师报告更高的心理与生理负荷，同时训练师反馈了更强的胜任感，受训者则报告了更低的生理需求。这些发现支持了我们所提出界面在实现有效远程人-机器人物理交互方面的可行性。未来工作应评估其在临床人群中的可用性与疗效，以恢复临床医生在机器人辅助治疗过程中的能动性感知。