6 papers
SleepVLM: A Rule-Grounded Vision-Language Model for Auditable Sleep Staging
Guifeng Deng, Pan Wang, Mengfan Niu +9
Sleep staging is essential for sleep assessment and disorder diagnosis. In recent years, automatic sleep staging systems have achieved accuracy approaching that of human experts, b…
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…
CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding
Jiquan Wang, Sha Zhao, Zhiling Luo +5
Electroencephalography (EEG) is a non-invasive technique to measure and record brain electrical activity, widely used in various BCI and healthcare applications. Early EEG decoding…
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…
Generalizable Sleep Staging via Multi-Level Domain Alignment
Jiquan Wang, Sha Zhao, Haiteng Jiang +3
Automatic sleep staging is essential for sleep assessment and disorder diagnosis. Most existing methods depend on one specific dataset and are limited to be generalized to other un…
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…