Miran Lee
Papers
7
Total Citations
48
H-Index
5
About
Miran Lee’s research lies at the vital intersection of robotics, geriatric care, and human-robot interaction, with a focused mission to revolutionize elderly care training. Her major contribution is the development of the **Care Training Assistant Robot (CaTARo)** series, including the elbow-joint CaTARo-E and a multi-DOF shoulder complex robot. These robotic simulators are designed to train caregivers—especially novices—by providing realistic, quantifiable feedback on care techniques. Lee’s work integrates real-time monitoring systems and fuzzy-logic-based assessment to objectively evaluate trainee performance, addressing the critical shortage of safe, repeatable practice opportunities in elderly care education. Her impact is demonstrated through a growing body of work, with her 2019 paper on the CaTARo-E robot accumulating **16 citations** and her 2019 study on real-time monitoring earning **8 citations**. Notably, Lee has advanced the field by incorporating **3D facial pain expressions** and **mood transitions** into patient robots, using Siamese and triplet networks to generate realistic, empathetic feedback. Her 2023 database, RU-FEMOIN, further supports robotic emotional expression. By combining engineering precision with compassionate care, Lee’s research directly addresses the global challenge of training a skilled, empathetic elderly-care workforce.
Research Focus
Key Achievements
Top Papers
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