Intelligent Actuation and Control in Rehabilitation Robotic Systems

Dear Colleagues,

Rehabilitation robotics has undergone a transformative shift over the past decade, driven by the convergence of advanced actuation technologies and intelligent control paradigms. As the global burden of neurological and musculoskeletal disorders continues to rise, there is an urgent need for robotic systems that not only assist physical movement but actively adapt to the complex, time-varying dynamics of the human body. Traditional rehabilitation devices, constrained by rigid mechanics and fixed control strategies, have demonstrated limited efficacy in translating laboratory performance into real-world therapeutic outcomes. The next frontier lies in achieving a seamless symbiosis between humans and rehabilitation robotic systems—an integrated coupling in which physical and cognitive dimensions of interaction are unified into a coherent, adaptive whole.

This seamless symbiosis demands progress on two inseparable fronts. On the physical side, actuator design must reconcile competing demands of power density, compliance, and biomechanical compatibility, enabling robots to engage with the human musculoskeletal system in a manner that is safe, natural, and energetically efficient. On the cognitive side, control architectures must continuously sense, interpret, and respond to the user's movement intent, fatigue, and neuromotor state—closing the loop not merely around position or force, but around the human's own adaptive physiology. Together, these physical and cognitive layers constitute the substrate of true human–robot symbiosis: a dynamic, bidirectional partnership in which the robotic system and the human co-evolve toward restored function.

This Special Issue aims to present and disseminate the most recent advances in intelligent actuation and control for rehabilitation robotic systems. We invite contributions that address the full spectrum of challenges at the human–robot interface, from novel actuator architectures and compliant mechanism design to AI-driven control, motor intent decoding, and co-adaptive learning frameworks. Topics of interest include, but are not limited to, the following:

• [Topic 1] Design and control of compliant and quasi-direct-drive actuators for rehabilitation robotics;
• [Topic 2] AI-driven motor intent recognition and co-adaptive control using multimodal biosignals;
• [Topic 3] Exoskeleton and orthosis development for upper and lower limb rehabilitation;
• [Topic 4] Musculoskeletal simulation and digital twin frameworks for rehabilitation device validation.

Dr. Ho-seon Choi
Guest Editor

Manuscript Submission Information

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• rehabilitation robotics
• intelligent actuation
• seamless symbiosis
• co-adaptive control
• motor intent recognition
• wearable exoskeleton
• musculoskeletal simulation