Zhouyang Wang

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About

Zhouyang Wang is a leading researcher in the intersection of rehabilitation robotics and neural engineering, with a primary focus on advancing lower limb exoskeleton technologies. His work centers on three key areas: gait phase prediction, brain-computer interfaces (BCIs), and intelligent exoskeleton control systems. Wang’s most influential contribution is his pioneering approach to robust gait phase prediction, which addresses critical challenges in detecting user intention and reducing motion signal lag in exoskeleton robots—a foundational study that has garnered 25 citations. He has further pushed boundaries by developing an asynchronous BCI-based exoskeleton control system using motor imagery (MI), enabling users to perform complex actions like walking, sitting, and standing through real-time EEG decoding. Additionally, Wang has innovated hybrid control methods that integrate Steady-State Visual Evoked Potentials (SSVEP) with traditional force and angle sensors, creating more intuitive rehabilitation systems. His work represents a significant step toward seamless human-robot interaction, with potential to transform mobility assistance for individuals with lower limb impairments. Through these contributions, Wang continues to shape the future of intelligent, brain-controlled assistive technologies.