ArticleJournal of healthcare engineering2021
Complexity and Entropy Analysis to Improve Gender Identification from Emotional-Based EEGs.
Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Neural Dynamics Associated with Biological Variation in Normal Human Brain Regions.Entropy (Basel, Switzerland) · 2024Article
- Sex differences of signal complexity at resting-state functional magnetic resonance imaging and their associations with the estrogen-signaling pathway in the brain.Cognitive neurodynamics · 2024Article
- Musical Emotions Recognition Using Entropy Features and Channel Optimization Based on EEG.Entropy (Basel, Switzerland) · 2022Article
- An integrated entropy-spatial framework for automatic gender recognition enhancement of emotion-based EEGs.Medical & biological engineering & computing · 2022Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent (Hur) and amplitude-aware permutation entropy (AAPE) features were extracted from the EEG dataset.
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Registered trials
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