Abstract
The occipital lobe of human brain is responsible for visual perception and the prefrontal lobe is responsible for emotion recognition. A novel approach to understand the interrelation between the occipital lobe and pre-frontal lobe for human emotions is presented in this paper. Electroencephalogram is an important and efficient tool for emotion recognition. In this paper data acquisition is performed using 10–20 electrode placement system. Data are acquired from occipital lobe as well as from pre-frontal lobe corresponding to five different emotional videos. The raw EEG data from occipital lobe and pre-frontal lobe are pre-processed using surface Laplacian filtering. After removal of artifacts and noise, feature extraction is performed using wavelet transform and the feature power spectral density is considered further. Feature mapping between occipital lobe and pre-frontal lobe is performed for different emotions. The work has been performed in MATLAB. The present work shows faster convergence of the weights of the proposed Type 1 Fuzzy neural network compared to the back-propagation neural network which indicates better perceptual ability.
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Chaki, S., Mukherjee, A., Chatterjee, S. (2021). Emotion Recognition from Feature Mapping Between Two Different Lobes of Human Brain Using EEG. In: Pan, I., Mukherjee, A., Piuri, V. (eds) Proceedings of Research and Applications in Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 1355. Springer, Singapore. https://doi.org/10.1007/978-981-16-1543-6_19
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DOI: https://doi.org/10.1007/978-981-16-1543-6_19
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