Categorizing Autonomic Nervous System (ANS) emotional signals using bio-sensors for HRI within the MAUI paradigm Conference

Lisetti, CL, Nasoz, F. (2006). Categorizing Autonomic Nervous System (ANS) emotional signals using bio-sensors for HRI within the MAUI paradigm . 277-284. 10.1109/ROMAN.2006.314430

cited authors

  • Lisetti, CL; Nasoz, F

authors

abstract

  • In this article, we discuss the strong relationship between affect and cognition and the importance of emotions in Multimodal Human Computer Interaction (HCI) and User-Modeling. We introduce the overall paradigm for our multimodal system that aims at recognizing its users' emotions and at responding to them accordingly depending upon the current context or application. We then describe the design of the emotion elicitation experiment we conducted by collecting, via wearable computers, physiological signals from the autonomic nervous system (galvanic skin response, heart rate, temperature) and mapping them to certain emotions (Sadness, Anger, Fear, Surprise, Frustration, and Amusement). We show the results of three different supervised learning algorithms that categorize these collected signals in terms of emotions, and generalize their learning to recognize emotions from new collections of signals. We finally discuss possible broader impact and possible applications of emotion recognition for multimodal intelligent systems. © 2006 IEEE.

publication date

  • December 1, 2006

Digital Object Identifier (DOI)

International Standard Book Number (ISBN) 10

International Standard Book Number (ISBN) 13

start page

  • 277

end page

  • 284