Comprehensive Comparative Analysis of Lower Limb Exoskeleton Research: Control, Design, and Application

• Published in: Actuators Vol. 14; no. 7; p. 342
• Main Authors: Hasan, Sk, Alam, Nafizul
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2025
• Subjects: Actuator design; Actuators; adaptive control systems; Business metrics; Comparative analysis; Computer architecture; Configuration management; Control algorithms; Control engineering; Controllers; Cooperative control; Degrees of freedom; Design; Digital twins; Electroencephalography; Energy efficiency; Exoskeletons; Fuzzy logic; Gait; Hardware; Human engineering; human–robot interaction (HRI); Inclusion; Innovations; lower limb exoskeletons; Machine learning; Neural networks; Pediatrics; Real time; Recurrent neural networks; Rehabilitation; rehabilitation robotics; Robotics; Robots; Sensors; Simulation methods; Spinal cord; Synchronism; Technological change; Terrain; Trends; wearable assistive technology
• DOI: 10.3390/act14070342
• ISSN: 2076-0825

This review provides a comprehensive analysis of recent advancements in lower limb exoskeleton systems, focusing on applications, control strategies, hardware architecture, sensing modalities, human-robot interaction, evaluation methods, and technical innovations. The study spans systems developed for gait rehabilitation, mobility assistance, terrain adaptation, pediatric use, and industrial support. Applications range from sit-to-stand transitions and post-stroke therapy to balance support and real-world navigation. Control approaches vary from traditional impedance and fuzzy logic models to advanced data-driven frameworks, including reinforcement learning, recurrent neural networks, and digital twin-based optimization. These controllers support personalized and adaptive interaction, enabling real-time intent recognition, torque modulation, and gait phase synchronization across different users and tasks. Hardware platforms include powered multi-degree-of-freedom exoskeletons, passive assistive devices, compliant joint systems, and pediatric-specific configurations. Innovations in actuator design, modular architecture, and lightweight materials support increased usability and energy efficiency. Sensor systems integrate EMG, EEG, IMU, vision, and force feedback, supporting multimodal perception for motion prediction, terrain classification, and user monitoring. Human–robot interaction strategies emphasize safe, intuitive, and cooperative engagement. Controllers are increasingly user-specific, leveraging biosignals and gait metrics to tailor assistance. Evaluation methodologies include simulation, phantom testing, and human–subject trials across clinical and real-world environments, with performance measured through joint tracking accuracy, stability indices, and functional mobility scores. Overall, the review highlights the field’s evolution toward intelligent, adaptable, and user-centered systems, offering promising solutions for rehabilitation, mobility enhancement, and assistive autonomy in diverse populations. Following a detailed review of current developments, strategic recommendations are made to enhance and evolve existing exoskeleton technologies.