The Boston Children’s Hospital sleep corpus: a collection of 15695 annotated pediatric polysomnograms

Sleep is a fundamental biological process essential to health, particularly during early life when sleep patterns are developing and sleep disorders are common. Yet pediatric sleep research is hindered by a lack of large-scale, high-quality polysomnography (PSG) datasets. To address this need, we introduce the Boston Children's Hospital (BCH) Sleep Corpus-the largest pediatric PSG dataset available-comprising 15 695 overnight recordings from 12 640 unique patients (median age ~ 6 years). The dataset includes 16.7 million annotated sleep stages, 2.25 million respiratory, arousal, and limb movement events, and over 11 000 patient diagnoses linked through de-identified electronic health records. Each PSG has a median duration of 8.9 hours, totaling 139 208 hours of EEG data. Sleep staging follows American Academy of Sleep Medicine guidelines and reveals age-related trends: REM sleep decreases from 33.5% in neonates to 16.3% in teenagers, while N2 sleep increases from 21.7% to 35.4%. Central apneas decline with age, while obstructive hypopneas and respiratory effort related arousals events rise. Limb movements are not scored in <1 yr but remain at around 30 per PSG across older age groups. We also present age- and region-specific EEG spectral norms and respiratory event trends across the pediatric age range. The dataset is organized in Brain Imaging Data Structure (BIDS) format and publicly available via the Brain Data Science Platform. The dataset provides a valuable resource for improving our scientific understanding of pediatric sleep and developing automated PSG analysis with artificial intelligence tools.

Authors

Institutions

Publication Details

Journal
SLEEP
Published
2025-09-16
DOI
https://doi.org/10.1093/sleep/zsaf273
Primary Topic
Sleep and Wakefulness Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Boston Children’s Hospital sleep corpus: a collection of 15695 annotated pediatric polysomnograms

Manohar Ghanta, Wolfgang Ganglberger, Ayan Mitra, Samuel T. Waters et al.
SLEEP
Sleep and Wakefulness Research
article

The Boston Children’s Hospital sleep corpus: a collection of 15695 annotated pediatric polysomnograms

Manohar Ghanta, Wolfgang Ganglberger, Ayan Mitra, Samuel T. Waters, Lynn Marie Trotti, Michael Brandon Westover, ROBERT JOSEPH THOMAS, Bruce D. Nearing, Zuzana Koscova, Samaneh Nasiri, Chad J. Robichaux, Ayush Tripathi, Umakanth Katwa, Haoqi Sun, Gari D. Clifford, Rebecca C. Fitzgerald, Kiran Maski, Matthew A. Reyna, Emmanuel Mignot, Valdery Moura, Dennis Hwang, Gauri Ganjoo, Niels Turley, Zhiyong Zhang, Qiao Li, Arnav Gupta, Katie L Stone, Aditya Gupta, Christine Tsien Silvers, Bharath Gunapati, Callison Alcott
article en

Abstract

Sleep is a fundamental biological process essential to health, particularly during early life when sleep patterns are developing and sleep disorders are common. Yet pediatric sleep research is hindered by a lack of large-scale, high-quality polysomnography (PSG) datasets. To address this need, we introduce the Boston Children's Hospital (BCH) Sleep Corpus-the largest pediatric PSG dataset available-comprising 15 695 overnight recordings from 12 640 unique patients (median age ~ 6 years). The dataset includes 16.7 million annotated sleep stages, 2.25 million respiratory, arousal, and limb movement events, and over 11 000 patient diagnoses linked through de-identified electronic health records. Each PSG has a median duration of 8.9 hours, totaling 139 208 hours of EEG data. Sleep staging follows American Academy of Sleep Medicine guidelines and reveals age-related trends: REM sleep decreases from 33.5% in neonates to 16.3% in teenagers, while N2 sleep increases from 21.7% to 35.4%. Central apneas decline with age, while obstructive hypopneas and respiratory effort related arousals events rise. Limb movements are not scored in <1 yr but remain at around 30 per PSG across older age groups. We also present age- and region-specific EEG spectral norms and respiratory event trends across the pediatric age range. The dataset is organized in Brain Imaging Data Structure (BIDS) format and publicly available via the Brain Data Science Platform. The dataset provides a valuable resource for improving our scientific understanding of pediatric sleep and developing automated PSG analysis with artificial intelligence tools.

SLEEP
Boston Children's Hospital (US), Georgia Institute of Technology (US), Amazon (United States) (US), Beth Israel Deaconess Medical Center (US), Harvard University (US), Emory University (US), Palo Alto University (US), University of California, San Francisco (US), California Pacific Medical Center (US), Harvard University Press (US), Massachusetts General Hospital (US), Pacific Medical (China) (CN), San Bernardino County Department of Public Health (US), Boston Children's Museum (US), Stanford University (US)
Openalex Percentile: Top 75%
Sleep and Wakefulness Research
DOISourceOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.