Sleep Data

Sleep data analysis is a rapidly evolving field focused on improving sleep staging accuracy, understanding the relationship between sleep and other health metrics, and developing personalized sleep interventions. Current research utilizes diverse machine learning approaches, including convolutional neural networks, ensemble methods, and large language models, often incorporating multimodal data from wearables, EEG, and even WiFi signals to enhance prediction accuracy and robustness. These advancements hold significant promise for improving the diagnosis and treatment of sleep disorders, personalizing healthcare, and advancing our understanding of sleep's crucial role in overall health and well-being.