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About

Jaeyong Song is a leading researcher in the field of rehabilitation and assistive robotics, with a primary focus on the design and control of soft wearable exosuits and exoskeletons for upper-limb assistance. His work addresses critical challenges in human-robot interaction, including gravity compensation for tendon-driven systems and the development of intuitive, individualized control frameworks for neurorehabilitation. Song has made significant contributions to improving the clinical adoption of robotic therapy, notably through the creation of the ARMStick interface—a therapist-friendly tool designed to bridge the gap between clinicians and complex robotic systems. His research also explores innovative methodologies such as human-in-the-loop simulation for exoskeleton validation, which he terms the "Digital Guinea Pig" approach, and the feasibility of combining robotic hand orthoses with botulinum toxin therapy for spasticity management. With key papers accumulating over 20 citations each, Song’s work is widely recognized for its practical impact on rehabilitation technology. His recent studies on polymorphic control frameworks and attachment system design further underscore his commitment to making robotic assistance safe, effective, and accessible for patients and therapists alike.