Toward Intelligent Human–Robot Interaction for Upper Limb Rehabilitation: A Review of Emerging Modalities and Strategies

Human-robot interaction (HRI) has emerged as a transformative approach in upper limb reha-bilitation, enabling intelligent, adaptive, and patient-centered interventions. This review provides a compre-hensive synthesis of recent advancements in HRI strategies for upper limb rehabilitation, covering interaction modalities, intelligent control mechanisms, real-world deployment practices, and clinical evaluation methods. We highlight the transition from conventional, therapist-led therapy to dynamic, sensor-driven systems that integrate physical, perceptual, cognitive, and multi-modal feedback. Emphasis is placed on adaptive control, user state estimation, and co-adaptive learning frameworks. Practical insights are drawn from hospital-based deployments, home rehabilitation systems, and user experience studies, culminating in a discussion on current limitations and future research directions. This review aims to guide researchers, engineers, and clinicians in designing inclusive, evidence-based HRI systems for enhanced rehabilitation outcomes.