A comparative analysis of emotion recognition from EEG signals using temporal features and hyperparameter-tuned machine learning techniques

Classifying emotions based on EEG signals is really important for enhancing our interactions with computers, monitoring mental health and creating applications in affective computing field. This study explores improving emotion recognition performance by applying traditional machine learning classif...

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Vydáno v:	MethodsX Ročník 15; s. 103468
Hlavní autoři:	Hasan, Rabita, Islam, Sheikh Md. Rabiul
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Netherlands Elsevier B.V 01.12.2025 Elsevier
Témata:	Boosted EEG Emotion Classification Using Differential Entropy and Higuchi's Fractal Dimension DEAP dataset EEG signals Emotion classification Feature extraction Machine learning Feature extraction EEG signals Boosted EEG Emotion Classification Using Differential Entropy and Higuchi's Fractal Dimension Emotion classification Machine learning DEAP dataset
ISSN:	2215-0161, 2215-0161
On-line přístup:	Získat plný text
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