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Found 2 papers, 2 papers with code
Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism
This study is the first to consolidate a more transparent feature-relevance calculation for a successful EEG-based facial emotion recognition using a within-subject-trained CNN in typically-developed and ASD individuals.
Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity
This result is consistent with recent neuroscience studies on emotion recognition, which found an association between these band suppressions and the behavioral deficits observed in individuals with ASD.
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