Manida Swangnetr
Papers
5
Total Citations
220
H-Index
4
About
Manida Swangnetr is a pioneering researcher at the intersection of human-robot interaction (HRI), healthcare robotics, and affective computing. Her work addresses one of modern healthcare's most pressing challenges: the critical shortage of nursing professionals in the United States and the potential for intelligent service robots to bridge this gap in patient care. Swangnetr's most influential contribution, cited over 112 times, introduced a sophisticated framework for classifying patient emotional states during robot interactions using wavelet analysis and statistics-based feature selection — a breakthrough that brought emotional intelligence to nursing robot design. Complementing this, her highly cited work on service robot feature design (86 citations) explored how physical and behavioral robot characteristics shape user perceptions and emotional responses, providing essential design guidelines for developers. Across multiple studies, she has systematically examined how humanoid features — including facial appearance, voice, and interactivity — influence patient emotions, and how factors such as user age should inform robot configuration in clinical settings. Her application of rigorous statistical and signal processing methods to patient-robot interaction data reflects a deeply empirical approach. Collectively, Swangnetr's research has laid critical groundwork for developing emotionally responsive, patient-centered healthcare robots.
Research Focus
Key Achievements
Top Papers
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