Preclinical evaluation of a safety-aware multimodal robotic pipeline for human–robot interaction in post-stroke rehabilitation

IntroductionPost-stroke rehabilitation increasingly requires technologies capable of supporting intensive, measurable, and adaptable interventions while preserving clinical supervision and patient safety. This study presents a lightweight, safety-aware, and modular multimodal robotic pipeline for embodied human–robot interaction in post-stroke rehabilitation, with a first target application in hemispatial inattention.MethodsThe system was implemented on the TIAGo mobile manipulator within a ROS 2-based architecture and integrates therapist-mediated supervision, speech-based and graphical interaction, head-orientation monitoring, adaptive auditory recall, robot-mediated and screen-based task delivery, and structured performance logging. Dialogue management is based on a deterministic finite-state machine coupled with a rule-based Natural Language Understanding pipeline, enabling predictable interaction handling, explicit fallback behavior, and therapist escalation for safety-relevant events. A preliminary preclinical evaluation was conducted in 16 healthy participants, with a repeated acquisition after 1 month. The study assessed operational feasibility, multimodal interaction robustness, head-orientation monitoring stability, task execution, ASR-related interaction events, usability, acceptance, and 1-month reproducibility of workflow execution.ResultsAll participants completed both acquisitions without adverse events or safety-relevant events requiring interruption of the experimental workflow. End-effector recognition accuracy remained high, attention-recall events were infrequent, screen-based visual tasks were successfully administered and logged, and usability and acceptance outcomes were favorable, with low anxiety toward the robotic platform.DiscussionThese findings support the feasibility of using a therapist-supervised robotic platform as an integrated tool for structured interaction, head-orientation monitoring, rehabilitation-oriented task delivery, and quantitative logging. The study presents a preclinical evaluation of system architecture, safety-aware interaction design, and workflow robustness. Future work is organized in two stages: a dedicated acceptance and robustness protocol in healthy controls to formally test interaction acceptance, speech-recognition robustness, and safety-relevant failure handling, followed by a true rehabilitation protocol in post-stroke patients with hemispatial inattention, including therapist-supervised exercise adaptation.