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http://hdl.handle.net/10553/132169
Title: | Towards Bi-Hemispheric Emotion Mapping Through EEG: A Dual-Stream Neural Network Approach | Authors: | Freire Obregón, David Sebastián Hernández Sosa, José Daniel Santana Jaria, Oliverio Jesús Lorenzo Navarro, José Javier Castrillón Santana, Modesto Fernando |
UNESCO Clasification: | 120304 Inteligencia artificial | Issue Date: | 2024 | Journal: | 2024 Ieee 18Th International Conference On Automatic Face And Gesture Recognition, Fg 2024 | Conference: | 18th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2024) | Abstract: | Emotion classification through EEG signals plays a significant role in psychology, neuroscience, and humancomputer interaction. This paper addresses the challenge of mapping human emotions using EEG data in the Mapping Human Emotions through EEG Signals FG24 competition. Subjects mimic the facial expressions of an avatar, displaying fear, joy, anger, sadness, disgust, and surprise in a VR setting. EEG data is captured using a multi-channel sensor system to discern brain activity patterns. We propose a novel two-stream neural network employing a Bi-Hemispheric approach for emotion inference, surpassing baseline methods and enhancing emotion recognition accuracy. Additionally, we conduct a temporal analysis revealing that specific signal intervals at the beginning and end of the emotion stimulus sequence contribute significantly to improve accuracy. Leveraging insights gained from this temporal analysis, our approach offers enhanced performance in capturing subtle variations in the states of emotions. | URI: | http://hdl.handle.net/10553/132169 | ISBN: | 979-8-3503-9494-8 | DOI: | 10.1109/FG59268.2024.10581965 | Source: | 2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition, FG 2024[EISSN ], (Enero 2024) |
Appears in Collections: | Actas de congresos |
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