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Emotion Recognition Using Bio-sensors: First Steps towards an Automatic System

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3068)

Abstract

The detection of emotion is becoming an increasingly important field for human-computer interaction as the advantages emotion recognition offer become more apparent and realisable. Emotion recognition can be achieved by a number of methods, one of which is through the use of bio-sensors. Bio-sensors possess a number of advantages against other emotion recognition methods as they can be made both inobtrusive and robust against a number of environmental conditions which other forms of emotion recognition have difficulty to overcome. In this paper, we describe a procedure to train computers to recognise emotions using multiple signals from many different bio-sensors. In particular, we describe the procedure we adopted to elicit emotions and to train our system to recognise them. We also present a set of preliminary results which indicate that our neural net classifier is able to obtain accuracy rates of 96.6% and 89.9% for recognition of emotion arousal and valence respectively.

Keywords

Heart Rate Variability Emotion Recognition Skin Conductivity Facial Expression Recognition International Affective Picture System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  1. 1.Sony Corporate Laboratories EuropeStuttgartGermany

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