5 papers
EEGAgent: A Unified Framework for Automated EEG Analysis Using Large Language Models
Sha Zhao, Mingyi Peng, Haiteng Jiang +3
Scalable and generalizable analysis of brain activity is essential for advancing both clinical diagnostics and cognitive research. Electroencephalography (EEG), a non-invasive moda…
EMOD: A Unified EEG Emotion Representation Framework Leveraging V-A Guided Contrastive Learning
Yuning Chen, Sha Zhao, Shijian Li +1
Emotion recognition from EEG signals is essential for affective computing and has been widely explored using deep learning. While recent deep learning approaches have achieved stro…
SPICED: A Synaptic Homeostasis-Inspired Framework for Unsupervised Continual EEG Decoding
Yangxuan Zhou, Sha Zhao, Jiquan Wang +4
Human brain achieves dynamic stability-plasticity balance through synaptic homeostasis. Inspired by this biological principle, we propose SPICED: a neuromorphic framework that inte…
Wearable Music2Emotion : Assessing Emotions Induced by AI-Generated Music through Portable EEG-fNIRS Fusion
Sha Zhao, Song Yi, Yangxuan Zhou +6
Emotions critically influence mental health, driving interest in music-based affective computing via neurophysiological signals with Brain-computer Interface techniques. While prio…
Personalized Sleep Staging Leveraging Source-free Unsupervised Domain Adaptation
Yangxuan Zhou, Sha Zhao, Jiquan Wang +5
Sleep staging is crucial for assessing sleep quality and diagnosing related disorders. Recent deep learning models for automatic sleep staging using polysomnography often suffer fr…