EMOTION CLASSIFICATION BASED ON PHYSIOLOGICAL RESPONSES INDUCED BY NEGATIVE EMOTIONS - Discrimination of Negative Emotions by Machine Learning Algorithms

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

Abstract

The one of main topic of emotion recognition or classification research is to recognize human’s feeling or emotion using physiological signals, which is one of the core processes to implement emotional intelligence in HCI research. The aim of this study was to identify the optimal algorithm to discriminate negative emotions (sadness, anger, fear, surprise, and stress) using physiological features. Physiological signals such as EDA, ECG, PPG, and SKT were recorded and analysed. 28 features were extracted from these signals. For classification of negative emotions, five machine learning algorithms, namely, LDF, CART, SOM, Naïve Bayes and SVM were used. Result of emotion classification showed that an accuracy of emotion classification using SVM was the highest (100.0\%) and that of LDA was the lowest (41.3\%). 78.2\%, 45.8\%, and 73.3% were shown as the accuracy of emotion classification in CART, SOMs and Naïve Bayes, respectively. This can be helpful to provide the basis for the emotion recognition technique in HCI.

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Paper Citation


in Harvard Style

Jang E., Park B., Kim S. and Sohn J. (2012). EMOTION CLASSIFICATION BASED ON PHYSIOLOGICAL RESPONSES INDUCED BY NEGATIVE EMOTIONS - Discrimination of Negative Emotions by Machine Learning Algorithms . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012) ISBN 978-989-8425-89-8, pages 453-457. DOI: 10.5220/0003871304530457


in Bibtex Style

@conference{biosignals12,
author={Eun-Hye Jang and Byoung-Jun Park and Sang-Hyeob Kim and Jin-Hun Sohn},
title={EMOTION CLASSIFICATION BASED ON PHYSIOLOGICAL RESPONSES INDUCED BY NEGATIVE EMOTIONS - Discrimination of Negative Emotions by Machine Learning Algorithms},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)},
year={2012},
pages={453-457},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003871304530457},
isbn={978-989-8425-89-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)
TI - EMOTION CLASSIFICATION BASED ON PHYSIOLOGICAL RESPONSES INDUCED BY NEGATIVE EMOTIONS - Discrimination of Negative Emotions by Machine Learning Algorithms
SN - 978-989-8425-89-8
AU - Jang E.
AU - Park B.
AU - Kim S.
AU - Sohn J.
PY - 2012
SP - 453
EP - 457
DO - 10.5220/0003871304530457