Novel Lower Limb Exoskeleton Rehabilitation System Based on Tactile Sensors and Digital Twin

This study presents a novel lower limb exoskeleton rehabilitation system integrating advanced tactile sensor matrices with a digital twin framework for enhanced patient recovery. The system incorporates piezoresistive and piezoelectric sensor matrices strategically placed on the soles of the feet and the lower limb structure, with the piezoelectric sensor matrix fabricated using near-field electrospinning (NFES) technology, placed on the sole to accurately capture gait patterns and center of pressure (COP) dynamics. Sensor data is collected by an Analog-To-Digital Converter (ADC) on the master control board. The master control board and slave control board communicate via a controller area network (CAN) bus to ensure real-time biomechanical data transmission to the exoskeleton's motion control unit. The primary innovation of this research lies in the seamless integration of sensor technology with a digital twin environment and virtual reality (VR) feedback mechanisms using Transmission Control Protocol (TCP) and Internet Protocol (IP), providing real-time gait analysis, adaptive rehabilitation strategies, and immersive user engagement. The exoskeleton's hardware design features a lightweight aluminum frame and torque-controlled actuators, ensuring precise assistance during gait cycles. The virtual rehabilitation environment, developed using Unreal Engine (UE) and HTC Vive tracking technology, enables patients to visualize their gait and receive real-time biomechanical feedback for improved and evaluated training outcomes. The combination of sensor placement, data communication, exoskeleton control, and VR integration represents a comprehensive and intelligent approach to rehabilitation, bridging the gap between the physical and digital domains.