Minsu Chang

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About

Minsu Chang is a leading researcher in rehabilitation robotics, specializing in the intersection of artificial intelligence and human motor recovery. Their work focuses on developing intelligent systems that enhance robot-assisted gait training, with a particular emphasis on replicating the nuanced expertise of human therapists. Chang's most impactful contribution is the pioneering "AI Therapist" framework, which models and automates the expert verbal cues—varying in expression, timing, and volume—that are critical for patient motivation and motor learning. This 2020 paper, with 20 citations, represents a significant step toward more adaptive and effective rehabilitation robots. Earlier foundational research (2017, 7 citations) established a method for assessing postural stability in users of lower limb exoskeletons, using the Head-Arm-Trunk (HAT) model to ensure safe and stable human-robot interaction. By bridging the gap between robotic assistance and the personalized, dynamic feedback of a human therapist, Chang is shaping the future of autonomous, intelligent rehabilitation technologies that can improve outcomes for individuals with mobility impairments.