Emotion extraction based on multi bio-signal using back-propagation neural network

Gilsang Yoo, Sanghyun Seo, Sungdae Hong, Hyeoncheol Kim

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


This study proposes a system that can recognize human emotional state from bio-signal. The technology is provided to improve the interaction between humans and computers to achieve an effective human–machine that is capable for intelligent interaction. The proposed method is able to recognize six emotional states, such as joy, happiness, fear, anger, despair, and sadness. These set of emotional states are widely used for emotion recognition purposes. The result shows that the proposed method can distinguish one emotion compared to all other possible emotional states. The method is composed of two steps: 1) multi-modal bio-signal evaluation and 2) emotion recognition using artificial neural network. In the first step, we present a method to analyze and fix human sensitivity using physiological signals, such as electroencephalogram, electrocardiogram, photoplethysmogram, respiration, and galvanic skin response. The experimental analysis shows that the proposed method has good accuracy performance and could be applied on many human–computer interaction devices for emotion detection.

Original languageEnglish
Pages (from-to)4925-4937
Number of pages13
JournalMultimedia Tools and Applications
Issue number4
Publication statusPublished - 2018 Feb 1

Bibliographical note

Funding Information:
This research was supported by a Korea University Grant with Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2015R1D1A1A01057975).

Publisher Copyright:
© 2016, Springer Science+Business Media New York.


  • Artificial neural network
  • Back propagation
  • Bio signal
  • Emotion extraction

ASJC Scopus subject areas

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


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