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Asian Conference on Intelligent Information and Database Systems

ACIIDS 2014: Intelligent Information and Database Systems pp 332–341Cite as

Factor Analysis as the Feature Selection Method in an Emotion Norm Database

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8398))

Abstract

Few studies have focused on integrating affective computing and soft computing technique for human physiology signals recognition in digital content learning system. This study develops a human affective norm (emotion and attention) recognition system for U-learning system. Eight elementary school students (4 male and 4 female) were recruited as participants to see some emotion pictures in international affective picture system (IAPS), and to collect their affective information—attention, meditation, electroencephalography (EEG), electrocardiogram (ECG), and SpO2 for developing the affective norm recognition system. These bio-physiology signals were extracted important features selection (Factor analysis) to serve as the input variables for radial basis function (RBF) neural network model. The results showed that all types of factor analysis did not perform well in our emotion norm database. Factor analysis with covariance extraction has higher accumulative variances than correlation extraction. This study suggested that future research can adopt more nonlinear feature selection methods to develop a high accuracy support vector machine based emotion recognition system.

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Author information

Authors and Affiliations

  1. National Taichung University of Education, Taichung, Taiwan

    Chih-Hung Wu & Bor-Chen Kuo

  2. National Taipei University, Taipei, Taiwan

    Gwo-Hshiung Tzeng

Authors
  1. Chih-Hung Wu
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  2. Bor-Chen Kuo
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  3. Gwo-Hshiung Tzeng
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Editor information

Editors and Affiliations

  1. Institute of Informatics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Ngoc Thanh Nguyen  & Bogdan Trawiński  & 

  2. Faculty of Engineering, Department of Computer Engineering, King Mongkut’s Institute of Technology Ladkrabang, 10520, Bangkok, Thailand

    Boonwat Attachoo

  3. Software Engineering Program, King Mongkut’s Institute of Technology Ladkrabang, 10520, Bangkok, Thailand

    Kulwadee Somboonviwat

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© 2014 Springer International Publishing Switzerland

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Wu, CH., Kuo, BC., Tzeng, GH. (2014). Factor Analysis as the Feature Selection Method in an Emotion Norm Database. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds) Intelligent Information and Database Systems. ACIIDS 2014. Lecture Notes in Computer Science(), vol 8398. Springer, Cham. https://doi.org/10.1007/978-3-319-05458-2_35

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  • DOI: https://doi.org/10.1007/978-3-319-05458-2_35

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05457-5

  • Online ISBN: 978-3-319-05458-2

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