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A Review of Feature Extraction Techniques for EEG-Based Emotion Recognition System

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Soft Computing: Theories and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1381))

Abstract

Emotional recognition based on electroencephalogram (EEG) signals is an important area of research in the field of compatible computing. There exist many feature extraction methods to extract EEG features, but it is dependent on the extensive knowledge of the EEG domain. The existing research has studied various feature extractions used for studying EEG for the understanding of emotions for decision-making. The major limitation is that there exists less research to provide details of EEG features in a single research. The major studies are selected based on the search string. With the help of a search string, we are reviewing only 50 studies. Therefore, the current study aims to review the mechanisms for the removal of the sensory perception element from the EEG and suggests the use of multiple strategies as part of EEG-based emotional recognition.

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Authors and Affiliations

  1. Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

    Rupali Gill & Jaiteg Singh

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  1. Rupali Gill
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  2. Jaiteg Singh
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Correspondence to Rupali Gill .

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Editors and Affiliations

  1. Department of Computer Science, Shobhit University Gangoh, Gangoh, Uttar Pradesh, India

    Tarun K. Sharma

  2. Gwangju Institute of Science and Technology, Gwangju, Korea (Republic of)

    Chang Wook Ahn

  3. Department of Instrumentation and Control Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India

    Om Prakash Verma

  4. Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, Delhi, India

    Bijaya Ketan Panigrahi

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Gill, R., Singh, J. (2021). A Review of Feature Extraction Techniques for EEG-Based Emotion Recognition System. In: Sharma, T.K., Ahn, C.W., Verma, O.P., Panigrahi, B.K. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1381. Springer, Singapore. https://doi.org/10.1007/978-981-16-1696-9_8

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