Open Access

Using Noninvasive Wearable Computers to Recognize Human Emotions from Physiological Signals

EURASIP Journal on Advances in Signal Processing20042004:929414

DOI: 10.1155/S1110865704406192

Received: 30 July 2002

Published: 18 September 2004

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.

Keywords and phrases

multimodal human-computer interaction emotion recognition multimodal affective user interfaces

Authors’ Affiliations

(1)
Department of Multimedia Communications, Institut Eurecom
(2)
Department of Computer Science, University of Central Florida

Copyright

© Lisetti and Nasoz 2004

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.