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Electroencephalograph (EEG) Based Emotion Recognition System: A Review

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Innovations in Electronics and Communication Engineering

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 33))

Abstract

Brain–computer interfacing is recent technology through which we can communicate with the outside world using the brain signals. This technology plays an important role in the biomedical field. BCI can be used to identify various human emotions. These emotions play an important role in human psychology. Recognition of emotion is subject of interest for both psychologists and engineers. Many researchers are doing a lot of work in the same field. The objective of this paper is to present study of various stages involved in electroencephalography (EEG) signal analysis for human emotion detection. The review gives an explanation of each method like EEG signal acquisition, signal preprocessing, feature extraction, and signal classification.

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Author information

Authors and Affiliations

  1. Sathyabama University, Chennai, Tamil Nadu, India

    Kalyani P. Wagh & K. Vasanth

Authors
  1. Kalyani P. Wagh
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  2. K. Vasanth
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Corresponding author

Correspondence to K. Vasanth .

Editor information

Editors and Affiliations

  1. Guru Nanak Institutions, Ibrahimpatnam, Telangana, India

    H. S. Saini

  2. Guru Nanak Institutions Technical Campus, Ibrahimpatnam, Telangana, India

    Ravi Kishore Singh

  3. Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, USA

    Vishal M. Patel

  4. Department of Electronics and Communication Engineering, Guru Nanak Institutions Technical Campus, Ibrahimpatnam, Telangana, India

    K. Santhi

  5. Research and Development, Guru Nanak Institutions Technical Campus, Ibrahimpatnam, Telangana, India

    S.V. Ranganayakulu

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Wagh, K.P., Vasanth, K. (2019). Electroencephalograph (EEG) Based Emotion Recognition System: A Review. In: Saini, H., Singh, R., Patel, V., Santhi, K., Ranganayakulu, S. (eds) Innovations in Electronics and Communication Engineering. Lecture Notes in Networks and Systems, vol 33. Springer, Singapore. https://doi.org/10.1007/978-981-10-8204-7_5

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  • DOI: https://doi.org/10.1007/978-981-10-8204-7_5

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