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Emotional State Recognition with EEG Signals Using Subject Independent Approach

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Data Science and Big Data Analytics

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 16))

Abstract

EEG signals vary from human to human and hence it is very difficult to create a subject independent emotion recognition system. Even though subject dependent methodologies could achieve good emotion recognition accuracy, the subject-independent approaches are still in infancy. EEG is reliable than facial expression or speech signal to recognize emotions, since it can not be fake. In this paper, a Multilayer Perceptron neural network based subject-independent emotion recognition system is proposed. Performance evaluation of the proposed system, on the benchmark DEAP dataset shows good accuracy compared to the state of the art subject independent methods.

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Author information

Authors and Affiliations

  1. Department of Computer Science & Engineering, Indira Gandhi Delhi Technical University for Woman, New Delhi, India

    Pallavi Pandey & K. R. Seeja

Authors
  1. Pallavi Pandey
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  2. K. R. Seeja
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Corresponding author

Correspondence to Pallavi Pandey .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Sri Aurobindo Institute of Technology, Indore, Madhya Pradesh, India

    Durgesh Kumar Mishra

  2. School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

  3. Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India

    Aynur Unal

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Pandey, P., Seeja, K.R. (2019). Emotional State Recognition with EEG Signals Using Subject Independent Approach. In: Mishra, D., Yang, XS., Unal, A. (eds) Data Science and Big Data Analytics. Lecture Notes on Data Engineering and Communications Technologies, vol 16. Springer, Singapore. https://doi.org/10.1007/978-981-10-7641-1_10

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