Natalia Quiroga
Papers
1
Total Citations
2
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1
About
Natalia Quiroga is a researcher at the intersection of robotics, human-robot interaction, and assistive technologies, with a particular focus on robot-assisted therapy. Her work addresses a critical challenge in therapeutic robotics: enabling robots to learn new motions by observing human demonstrations, thereby making therapy sessions more adaptive and personalized. In her most-cited study, "A Study of Demonstration-Based Learning of Upper-Body Motions in the Context of Robot-Assisted Therapy" (2023), Quiroga explores how robots can acquire upper-body motions through imitation learning, allowing them to serve as dynamic models for patients in rehabilitation or therapeutic settings. This approach enhances the robot's ability to introduce varied, patient-specific movements without requiring explicit programming for each new activity. While her citation count is currently modest, her work contributes to a growing body of research aimed at making assistive robots more flexible and responsive in clinical environments. Quiroga's research holds promise for improving the quality and engagement of robot-mediated therapy, particularly for individuals with motor or cognitive impairments.
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Top Papers
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