08.09.2026journal-article
Frontiers in Neurology
Multimodal physiological signal learning for clinical sleep respiratory event recognition
Automatic recognition of sleep-related breathing events is of great significance for auxiliary sleep disorder screening, clinical interpretation, and long-term physiological monitoring. To address the limitations of existing methods in complementary modeling of multimodal physiological signals, event-related feature aggregation, and imbalanced class learning, this study proposes a multimodal state-space representation learning framework for sleep-related breathing event recognition. The framework takes the neurophy …