MindMelody combines real-time EEG emotion decoding with an LLM for intervention planning and a hierarchical controller for generating affect-aware music in a continuous feedback loop.
Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks,
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A survey organizes deep learning techniques including feature alignment, adversarial learning, feature disentanglement, and contrastive learning to tackle cross-subject generalization in EEG decoding while formalizing evaluation protocols.
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MindMelody: A Closed-Loop EEG-Driven System for Personalized Music Intervention
MindMelody combines real-time EEG emotion decoding with an LLM for intervention planning and a hierarchical controller for generating affect-aware music in a continuous feedback loop.
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Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods
A survey organizes deep learning techniques including feature alignment, adversarial learning, feature disentanglement, and contrastive learning to tackle cross-subject generalization in EEG decoding while formalizing evaluation protocols.