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Authors: Yujun Niu 1 ; Hao Zhang 2 ; Shin'ichi Warisawa 1 and Ichiro Yamada 1

Affiliations: 1 University of Tokyo, Japan ; 2 The University of Tokyo, Japan

ISBN: 978-989-758-068-0

Keyword(s): Arousal Recognition, Electroencephalography (EEG), Discrete Wavelet Transform (DWT), Channel Selection.

Related Ontology Subjects/Areas/Topics: Affective Computing ; Biomedical Engineering ; Evaluation and Use of Healthcare IT ; Health Information Systems ; ICT, Ageing and Disability ; Pattern Recognition and Machine Learning

Abstract: Improving arousal recognition accuracy by using EEG signals is important for emotion recognition. In this research, discrete wavelet transform is used to extract features, and a cross-level method is adopted to select effective features. The cross-level method shows great potential for two-level arousal classification, and the recognition accuracy reaches 91.8%. The sensitivity of EEG channels is also discussed based on two ranking methods of SCP (single-channel performance) and ANOVA (analysis of variance). Finally, arousal recognition method based on EEG signals is applied to construct a Japanese emotion database.

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Paper citation in several formats:
Niu, Y.; Zhang, H.; Warisawa, S. and Yamada, I. (2015). Arousal Recognition Method using Electroencephalography Signals to Construct Emotional Database.In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015) ISBN 978-989-758-068-0, pages 360-366. DOI: 10.5220/0005208403600366

@conference{healthinf15,
author={Yujun Niu. and Hao Zhang. and Shin'ichi Warisawa. and Ichiro Yamada.},
title={Arousal Recognition Method using Electroencephalography Signals to Construct Emotional Database},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)},
year={2015},
pages={360-366},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005208403600366},
isbn={978-989-758-068-0},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)
TI - Arousal Recognition Method using Electroencephalography Signals to Construct Emotional Database
SN - 978-989-758-068-0
AU - Niu, Y.
AU - Zhang, H.
AU - Warisawa, S.
AU - Yamada, I.
PY - 2015
SP - 360
EP - 366
DO - 10.5220/0005208403600366

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