Chen-Hao Chang

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About

Chen-Hao Chang is a leading researcher in rehabilitation robotics and human-machine interaction, with a primary focus on restoring mobility for individuals with neurological injuries. His work centers on the development and control of hybrid exoskeletons that integrate powered robotic assistance with functional electrical stimulation (FES), leveraging the benefits of both muscle activation and mechanical support. Chang’s most-cited paper, "Closed-Loop Torque and Kinematic Control of a Hybrid Lower-Limb Exoskeleton for Treadmill Walking" (2022, 15 citations), introduces advanced control strategies that enable seamless, adaptive walking assistance—a critical step toward improving quality of life for those with movement impairments. He further advances the field with "Switched Adaptive Integral Concurrent Learning for Powered FES-Cycling" (2023), which tackles the complex, nonlinear dynamics of human-robot systems by developing robust, personalized control algorithms. By addressing the uncertainties and time-varying nature of these systems, Chang’s contributions enhance the safety, efficiency, and customization of neurorehabilitation technologies, making him a rising voice in the quest to restore lost function and independence.