6 papers
Learning transferable human physiology from two million hours of sleep with SleepFM-2
Rahul Thapa, Christopher Sun, William Theodor Lehn-Schioler +14
Sleep provides a nightly window into health by capturing coordinated activity across the brain, heart, muscles and respiratory system. We introduce SleepFM-2, a sleep foundation mo…
Agentic AI-enabled discovery across large-scale sleep physiology
Rahul Thapa, Umaer Hanif, Robin Guillard +10
Sleep occupies roughly one-third of human life, yet many aspects of its physiology remain poorly understood. Large polysomnography (PSG) datasets offer new opportunities to study s…
Pretraining on Sleep Data Improves non-Sleep Biosignal Tasks
William Lehn-Schiøler, Magnus Ruud Kjær, Phillip Hempel +7
Sleep foundation models have recently demonstrated strong performance on in-domain polysomnography tasks, including sleep staging, apnea detection, and disease risk prediction. In…
Stanford Sleep Bench: Evaluating Polysomnography Pre-training Methods for Sleep Foundation Models
Magnus Ruud Kjaer, Rahul Thapa, Gauri Ganjoo +7
Polysomnography (PSG), the gold standard test for sleep analysis, generates vast amounts of multimodal clinical data, presenting an opportunity to leverage self-supervised represen…
Frequency-Aware Masked Autoencoders for Human Activity Recognition using Accelerometers
Niels R. Lorenzen, Poul J. Jennum, Emmanuel Mignot +1
Wearable accelerometers are widely used for continuous monitoring of physical activity. Supervised machine learning and deep learning algorithms have long been used to extract mean…
Automatic Detection of Cortical Arousals in Sleep and their Contribution to Daytime Sleepiness
Andreas Brink-Kjaer, Alexander Neergaard Olesen, Paul E. Peppard +4
Cortical arousals are transient events of disturbed sleep that occur spontaneously or in response to stimuli such as apneic events. The gold standard for arousal detection in human…