meiyor/SincNet-for-Autism-EEG-based-Emotion-Recognition
This project describes the necessary code to implement an EEG-based emotion recognition using SincNet [Ravanelli & Bengio 2018] including data from individuals diagnosed with Autism (ASD). For more details and data request send an email to the authors and contributors Juan Manuel Mayor Torres (juan.mayortorres@unitn.it) and Mirco Ravanelli (Mila)
This project helps researchers analyze brainwave (EEG) data to understand how individuals, including those with Autism Spectrum Disorder (ASD), recognize emotions. It takes raw or preprocessed EEG recordings as input and produces insights into emotional responses, identifying accuracy metrics and distinct brainwave frequency patterns. Neuroscientists, clinical researchers, and psychologists studying emotion and neurodevelopmental disorders would find this useful.
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Use this if you are a researcher with EEG data from individuals, particularly those with ASD, and want to identify and interpret emotion recognition patterns using a robust deep learning method.
Not ideal if you need a real-time emotion detection system or if you are not working with EEG data from human participants.
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Jun 11, 2025
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