GilHwan Kim
Papers
4
Total Citations
11
H-Index
2
About
GilHwan Kim is a pioneering researcher at the intersection of robotics, motor learning, and rehabilitation engineering. His work centers on developing intelligent robotic exoskeletons that can adapt to individual users, with a particular focus on improving walking propulsion and upper-limb function after neurological injury. Kim’s most influential study, “Using Bayesian Optimization to Identify Optimal Exoskeleton Parameters Targeting Propulsion Mechanics” (2021, 6 citations), demonstrated a novel computational framework for personalizing robotic assistance during gait—a foundational step toward truly adaptive rehabilitation. In his 2024 work on modeling neuromotor adaptation to pulsed torque assistance (2 citations), Kim advanced the field by integrating error-based and use-dependent learning mechanisms into a unified model, addressing a critical gap in understanding how humans adapt to robot-aided gait training. His recent pilot study on self-guided, active robotic training for proprioception in chronic stroke (2025, 1 citation) expands the scope of robotic therapy beyond motor function to sensory rehabilitation. Kim’s contributions are shaping the next generation of personalized, data-driven rehabilitation technologies, offering new hope for individuals recovering from stroke and other movement disorders.
Research Focus
Key Achievements
Top Papers
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