Papers
2
Total Citations
14
H-Index
2
About
Yeji Hwang is a rising researcher in rehabilitation robotics, with a focus on developing intelligent systems to restore upper-limb motor function after neurological injury. Her work sits at the intersection of robotics, human motor control, and clinical assessment, aiming to make robot-aided therapy more personalized and effective. Hwang’s most cited paper (2020, 9 citations) introduces a novel end-effector robot system that overcomes a critical limitation of conventional rehabilitation robots: the inability to monitor a patient’s upper-extremity joint angles during planar reaching movements. By integrating posture sensing directly into the robot’s end-effector, this work enables more precise, data-driven therapy. Building on this, her 2023 paper (5 citations) proposes a groundbreaking method to objectively evaluate upper-limb motor performance after stroke. Instead of relying on pre-set movement templates, Hwang’s approach models a patient’s *normal* reaching patterns, allowing clinicians to quantify deviation and tailor rehabilitation protocols to each individual’s unique motor characteristics. This shift from one-size-fits-all to personalized assessment represents a significant step toward optimizing robot-aided training. With a growing citation record and a clear trajectory toward clinically impactful, human-centered robotics, Hwang is establishing herself as a key contributor to the future of neurorehabilitation technology.
Research Focus
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Top Papers
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