Changmao Yang

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About

Changmao Yang is a leading researcher in the field of biomechatronics and assistive robotics, with a primary focus on lower limb exoskeleton technologies. His most cited work, "Research on human gait prediction and recognition algorithm of lower limb-assisted exoskeleton robot" (2021, 29 citations), represents a significant contribution to the development of intelligent, human-aware robotic systems. In this study, Yang pioneered novel algorithms for real-time gait phase detection and motion intention prediction, enabling exoskeletons to seamlessly synchronize with a user’s natural walking patterns. This breakthrough addresses a critical challenge in assistive robotics: achieving intuitive, safe, and efficient human-robot interaction. By integrating sensor fusion and machine learning techniques, his research has laid the groundwork for more responsive and adaptive exoskeletons, with potential applications in rehabilitation, mobility assistance for the elderly, and industrial load-bearing. Yang’s work is widely recognized for its practical impact, bridging the gap between theoretical control systems and real-world wearable robotics. His contributions continue to inspire advances in human augmentation, making him a key figure in the evolution of next-generation assistive devices.