Exoskeleton systems have emerged as one of themost significant advancements in rehabilitation engineering andwearable robotics. These systems are designed to assist, augment,or restore human movement capabilities in patients sufferingfrom neurological disorders, muscular disabilities, stroke, andmobility impairments. This review paper presents a detailedcomparative analysis of recent research works related to upperlimb and lower-limb exoskeleton systems. The reviewed studiesfocus on rehabilitation robotics, electromyography (EMG)-basedintention detection, machine learning-assisted motion recognition,low-cost wearable robotic systems, and biomechanical exoskeleton architectures.The paper compares various design methodologies, controltechniques, sensor integration strategies, rehabilitation capabilities, portability, computational intelligence, and implementationcosts. Particular emphasis is given to EMG-based human intention recognition systems and lightweight rehabilitation architectures developed for economically constrained environments.The review also discusses the evolution of exoskeleton technologyfrom rigid mechanical systems toward intelligent adaptive wearable robotics integrated with artificial intelligence and neuralnetwork-based control systems.Finally, future developments involving adaptive learning algorithms, soft robotics, cloud-assisted rehabilitation analytics, andsmart wearable technologies are discussed. The study concludesthat future rehabilitation exoskeletons should focus on lightweightstructures, improved portability, intelligent human-machine interaction, and affordable manufacturing techniques to ensureaccessibility and rehabilitation efficiency.
Prem Nakshatra S (Tue,) studied this question.