Progreso de la investigación en robots de rehabilitación de la articulación del codo

Elbow orthoses offer a straightforward mechanical approach to rehabilitation following elbow joint injuries. The convergence of artificial intelligence with these orthoses has given rise to elbow rehabilitation robots, designed to address the personalized rehabilita-tion requirements of patients with diverse injury profiles. A typical elbow rehabilitation robot system comprises four key components: a mechanical rigid structure, an actuation system, bionic sensors, and integrated software. The rigid structure, analogous to the human skeletal system, includes linkage assemblies and gear transmission systems. The actuation system, mimicking muscles and ligaments, generates and modulates the necessary forces and torques for movement, employing actuators such as pneumatic, elastic (e.g., series elastic actuators), and cable-driven types. Bionic sensors, serving as the robot's perceptual interface, encompass photoelectric encoders, force/torque sensors, electromyo-graphic (EMG) signal sensors, and temperature sensors. The software system-encompassing control algorithms and machine learning models-functions as the "neural center," analogous to the brain and spinal cord, and is responsible for intelligent decision-making and motion control. The core technological achievement lies in seamlessly integrating hardware and software to enable precise tracking of elbow joint kinematics and adaptive modulation of assistive forces based on real-time human-robot interaction. This integration supports multiple training modalities-including passive, assistive, active, and resistive modes-to deliver safe, tailored, and intelligent rehabilitation support across different recovery phases. By harnessing technologies like bio-inspired design, precise impedance control, EMG-based assistance, and virtual reality integrated task training, these robotic systems improve training comfort, assistance accuracy, and patient adherence, potentially reducing post-injury disability rates. This review outlines the current state of research in elbow rehabilitation robotics, details the key system components and primary training modalities, discusses clinical demands and future development trends, and aims to offer insights for the further refinement of rehabilitation robotic systems.