The Human Sleep Project: A Multi-Center Clinical Polysomnography Dataset Across the Human Lifespan

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ID: 323838
2026
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Abstract
Abstract Study Objectives Sleep research has been limited by the lack of large, diverse polysomnography (PSG) datasets. Existing resources are often single-center, age-specific, or epidemiological in nature, restricting generalizability and large-scale clinical research. The objective of this study was to create a large, multi-center clinical PSG dataset to support scalable and broadly representative research in sleep medicine and clinical neuroscience. Methods The Human Sleep Project (HSP) dataset comprises 119,234 overnight sleep recordings from more than 90,000 unique patients collected across five major U.S. institutions: Stanford University, Massachusetts General Brigham (MGB), Emory University, Beth Israel Deaconess Medical Center (BIDMC), and Boston Children’s Hospital (BCH). Each study includes at least a standard attended PSG montage, along with clinical annotations and standardized automated sleep annotations. Data were harmonized using the Brain Imaging Data Structure (BIDS) framework and linked to de-identified demographic and electronic health record (EHR) data. Results The HSP spans the full human lifespan, from infancy to individuals over 90 years old, and includes diagnoses across 22 ICD-10 clinical categories. Analysis of the aggregated data demonstrates expected age-related trends in sleep architecture, including reduced total sleep time and N3 sleep and increased sleep fragmentation with advancing age. Standardization procedures successfully addressed technical and scoring variability across sites, creating a consistent and high-quality resource for large-scale analyses. Conclusions The Human Sleep Project provides harmonized physiological signals, manual and automated annotations, and quality metadata for 119,234 sleep studies, including 115,129 PSGs and 4,105 home sleep apnea tests, enabling reproducible sleep research at an unprecedented scale.
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Authors
Journal Sleep & breathing = Schlaf & Atmung
Year 2026
DOI
10.1093/sleep/zsag215
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