Optimal EEG Electrode Set for Emotion Recognition from Brain Signals: An Empirical Quest

Abstract: The human brain is a complex organ, still completely undiscovered, that controls almost all the parts of the body. Apart from survival, the human brain stimulates emotions. Recent research indicates that brain signals can be very effective for emotion recognition. However, which parts of the brain exhibit most emotions is still underexplored. In this study, we empirically analyze the contribution of each part of the brain in exhibiting emotions. We use the DEAP dataset to find the most optimal electrode set, eventually leading to the effective brain part associated with emotions. We use Fast Fourier Transformation for effective feature extraction and a 1D-CNN with residual connection for classification. Though 32 electrodes from the DEAP dataset got an accuracy of 97.34%, only 12 electrodes (F7, P8, O1, F8, C4, T7, PO3, Fp1, Fp2, O2, P3, and Fz) achieved 95.69% accuracy. This study also shows that adding more than ten electrodes does not improve performance significantly. Moreover, the frontal lobe is the most important for recognizing emotion.

Authors

Rumman Ahmed Prodhan^{1[0000-0002-6865-185X]}, Sumya Akter^{1[0000-0001-7114-1845]}, Md. Akhtaruzzaman Adnan^{1[0000-0003-4137-0844]}, Tanmoy Sarkar Pias^{2*[0000-0002-7325-9844]}

1. University of Asia Pacific, Dhaka 1205, Bangladesh
   Email: rumman153@gmail.com, sumyaakter601@gmail.com, adnan.cse@uap-bd.edu
2. Virginia Tech, Blacksburg, VA 24061, United States
   Email: tanmoysarkar@vt.edu

*Corresponding Author

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Recommended citation: Prodhan, R. A., Akter, S., Adnan, M. A., & Pias, T. S. (2024). Optimal EEG Electrode Set for Emotion Recognition from Brain Signals: An Empirical Quest. In *4th International Conference on Activity and Behavior Computing* (pp. 67-88), October 27-29, 2022, London, United Kingdom. CRC Press.