The Human Sleep Project

Study objectives: Sleep research has been hindered by existing polysomnography (PSG) datasets being typically single-center, age-specific, or epidemiological data with limited scale and health-relevant diversity, reducing generalizability. The goal here is to assemble a large multi-center clinical PSG dataset, enabling scalable and generalizable research in sleep medicine and clinical neuroscience. Methods: The Human Sleep Project (HSP) dataset, 119,234 overnight sleep recordings from more than 90,000 unique patients, integrates clinical PSG data collected from five major academic medical centers across the United States (sites are de-identified and referenced by cohort ID). The studies include a standard attended polysomnography montage at a minimum, as well as both clinical annotations and automatically generated standard annotations. The data are organized according to the Brain Imaging Data Structure (BIDS) standard and linked with de-identified demographic and electronic health record (EHR) information. Results: The resulting HSP dataset spans the full human lifespan (infancy to age >90 years), and links PSG data to diagnoses across 22 distinct ICD-10 clinical categories, including neurology, cardiology, and endocrinology. The aggregated data reveal consistent, age-dependent changes in sleep architecture, e.g., with increased age, a decrease in total sleep time and N3, and an increase in the stage shift derived Sleep Fragmentation Index (SFI). The standardization process successfully harmonized technical and scoring heterogeneity across sites, providing a consistent resource for large-scale analysis. Conclusions: The Human Sleep Project releases harmonized signals, manual and automated annotations, and per-session quality metadata for 119,234 overnight sleep recordings (115,129 full polysomnograms and 4,105 home sleep apnea tests) across five centers, enabling reproducible sleep research at a scale not previously available.