A Study on Autonomic Nervous System Responses and Feauture Selection for Emotion Recognition - Emotion Recognition using Machine Learning Algorithms

Byoung-Jun Park, Eun-Hye Jang, Sang-Hyeob Kim, Myung-Ae Chung, Jin-Hun Sohn

2014

Abstract

This study is related with emotion recognition based on autonomic nervous system responses. Three different emotional states, fear, surprise and stress, are evoked by stimuli and the autonomic nervous system responses for the induced emotions are measured as physiological signals such as skin temperature, electrodermal activity, electrocardiogram, and photoplethysmography. Twenty-eight features are analysed and extracted from these signals. The results of one-way ANOVA toward each parameter, there are significant differences among three emotions in some features. Therefore we select eight features from 28 features for emotion recognition. The comparative results of emotion recognition are discussed in view point of feature space with the selected features. For emotion recognition, we use four machine learning algorithms, namely, linear discriminant analysis, classification and regression tree, self-organizing map and naïve bayes, and those are evaluated by only training, 10-fold cross-validation and repeated random sub-sampling validation. This can be helpful to provide the basis for the emotion recognition technique in human computer interaction as well as contribute to the standardization in emotion-specific ANS responses.

Paper Citation

in Harvard Style

Park B., Jang E., Kim S., Chung M. and Sohn J. (2014). A Study on Autonomic Nervous System Responses and Feauture Selection for Emotion Recognition - Emotion Recognition using Machine Learning Algorithms . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014) ISBN 978-989-758-011-6, pages 116-121. DOI: 10.5220/0004731201160121

in Bibtex Style

@conference{biosignals14,
author={Byoung-Jun Park and Eun-Hye Jang and Sang-Hyeob Kim and Myung-Ae Chung and Jin-Hun Sohn},
title={A Study on Autonomic Nervous System Responses and Feauture Selection for Emotion Recognition - Emotion Recognition using Machine Learning Algorithms},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)},
year={2014},
pages={116-121},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004731201160121},
isbn={978-989-758-011-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)
TI - A Study on Autonomic Nervous System Responses and Feauture Selection for Emotion Recognition - Emotion Recognition using Machine Learning Algorithms
SN - 978-989-758-011-6
AU - Park B.
AU - Jang E.
AU - Kim S.
AU - Chung M.
AU - Sohn J.
PY - 2014
SP - 116
EP - 121
DO - 10.5220/0004731201160121