Inseung Kang

Wearable assistive devices, such as robotic exoskeletons, can help individuals with lower-limb disabilities to regain their mobility. However, current exoskeleton technology faces key limitations. Laboratory-optimized control strategies cannot account for the complexities of real-world environments, control frameworks based on data from healthy individuals struggle to adapt to the varying neuromuscular characteristics of clinical populations, and there is a lack of incorporation of human motor learning mechanisms. Consequently, exoskeletons have yet to gain widespread adoption in our daily life.

Inseung Kang's research addresses this core challenge: how to achieve natural coordination between an exoskeleton and the user’s motion. By integrating multifunctional hardware design with biomechanical principles, he has proposed a more intelligent and intuitive control mechanism, moving towards a new generation of wearable systems.

The hip exoskeleton system he developed is capable of assisting a diverse set of locomotor tasks. Its design has been optimized to provide joint assistance comparable to human biological joint moments while minimizing the system's overall mass and accounting for user comfort. During locomotion, the exoskeleton performs real-time inference of the user's state and accurately provides a biomechanically optimal hip joint assistance.

In addition, he has studied the application of exoskeletons in clinical populations such as stroke patients and children with cerebral palsy, providing key insights into control parameter optimization. These findings provide a crucial foundation for improving exoskeleton controllability for patient gait, enabling personalized assistance, and allowing for the iterative improvement of adaptive exoskeleton systems.