Authors

C. L. Lisetti;F. Nasoz

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Abbreviated Journal Title

EURASIP J Appl. Signal Process.

Keywords

multimodal human-computer interaction; emotion recognition; multimodal; affective user interfaces; NERVOUS-SYSTEM ACTIVITY; RESPONSES; TASK; FEAR; DIFFERENTIATION; ABILITY; MOOD; Engineering, Electrical & Electronic

Abstract

We discuss the strong relationship between affect and cognition and the importance of emotions in multimodal human computer interaction (HCl) 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.

Journal Title

Eurasip Journal on Applied Signal Processing

Volume

2004

Issue/Number

11

Publication Date

1-1-2004

Document Type

Article

Language

English

First Page

1672

Last Page

1687

WOS Identifier

WOS:000225581000006

ISSN

1110-8657

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