Using noninvasive wearable computers to recognize human emotions from physiological signals Article

Lisetti, CL, Nasoz, F. (2004). Using noninvasive wearable computers to recognize human emotions from physiological signals . 2004(11), 1672-1687. 10.1155/S1110865704406192

cited authors

  • Lisetti, CL; Nasoz, F

abstract

  • 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 potential applications of emotion recognition for multimodal intelligent systems.

publication date

  • September 1, 2004

Digital Object Identifier (DOI)

start page

  • 1672

end page

  • 1687

volume

  • 2004

issue

  • 11