George B. Moody PhysioNet Challenges

For the past 27 years, PhysioNet and Computing in Cardiology have co-hosted a series of annual challenges, now called the George B. Moody PhysioNet Challenges, to tackle clinically interesting but unsolved questions.

The George B. Moody PhysioNet Challenge 2026 invites teams to develop and implement open-source algorithms for using PSGs to predict future diagnoses of cognitive impairment. Sleep is a fundamental physiological process that is deeply intertwined with human health. Traditionally, clinicians use sleep studies to diagnose obstructive sleep apnea, insomnia, and other sleep disorders. However, sleep studies can also reveal other chronic conditions that cause, are caused by, or are correlated with physiological changes in sleep. These findings can provide context to sleep disorders and inform the early diagnosis and treatment of other health conditions. The PhysioNet Challenge 2026 invites teams to develop algorithmic approaches for using polysomnography (PSG), which records various physiological signals during sleep studies, to predict future diagnoses of cognitive impairment.

Please check the below links for information about current and past Challenges, including important details about scoring and test data for previous Challenges.

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Current Challenge

Past Challenges

Supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under NIH grant number R01EB030362.

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