Therapist-Robot-Patient Physical Interaction is Worth a Thousand Words: Enabling Intuitive Therapist Guidance via Remote Haptic Control

2026-02-25

AI Summary

This study addresses the lack of intuitive physical interaction between therapists and patients in current rehabilitation robot systems, which hinders clinical adoption. The authors propose a novel approach integrating haptic teleoperation with upper-limb exoskeleton control, employing a virtual contact point model to emulate human-like physical guidance. This enables therapists to intuitively direct patient movements using off-the-shelf haptic devices. The system innovatively combines haptic guidance, exoskeleton control, and large language model–driven voice command classification, substantially reducing reliance on verbal instructions. Experimental results demonstrate that the proposed method significantly decreases task completion time, enhances movement smoothness, improves therapists’ sense of competence, and reduces patients’ physical workload—all without imposing additional cognitive or physical burden.

Technology Category

• Intelligent Robots: Manipulation
• Humans and AI: Interaction Techniques and Devices
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

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.

Problem

• therapist-patient interaction
• rehabilitation robotics
• intuitive guidance
• haptic teleoperation
• human-robot interaction

Innovation

• haptic teleoperation
• remote physical interaction
• arm exoskeleton
• intuitive guidance
• robot-assisted therapy