Emotion Detection from EEG Signals Using Machine Deep Learning Models

• Published in: Bioengineering (Basel) Vol. 11; no. 8; p. 782
• Main Authors: Fernandes, João Vitor Marques Rabelo, Alexandria, Auzuir Ripardo de, Marques, João Alexandre Lobo, Assis, Débora Ferreira de, Motta, Pedro Crosara, Silva, Bruno Riccelli dos Santos
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.08.2024; MDPI
• Subjects: Accuracy; Algorithms; Artificial neural networks; Asymmetry; Brain; Brain research; Datasets; Deep learning; EEG; Electric properties; electroencephalogram; Electroencephalography; emotion detection; Emotion recognition; Emotions; graph convolutional neural networks; Graph neural networks; Human-computer interface; Learning algorithms; Machine learning; Neural networks; Power spectral density; Real time; Sensory integration; Signal processing; Support vector machines; Visual stimuli; Voice recognition; deep learning; emotion detection; graph convolutional neural networks; machine learning; emotion recognition; electroencephalogram

Detecting emotions is a growing field aiming to comprehend and interpret human emotions from various data sources, including text, voice, and physiological signals. Electroencephalogram (EEG) is a unique and promising approach among these sources. EEG is a non-invasive monitoring technique that reco...