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Peer-reviewedCC BY 4.0PLOS One

Polysomnography harmonization schemes: A multi-institutional sleep research resource

  • Yujin Han1
  • Gayeon Ryu2
  • Yeongdon Kim3
  • Hangsik Shin
  1. 1Department of Medical Informatics and Statistics, Brain Korea 21 Project, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
  2. 2Department of Medical Science, Graduate School, University of Ulsan, Seoul, Republic of Korea
  3. 3Institute of Digital Healthcare, University of Ulsan College of Medicine, Seoul, Republic of Korea
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Abstract

Sleep disorders are associated with cardiovascular diseases and cognitive decline worldwide, highlighting the need for effective therapeutic strategies. Polysomnography (PSG) is the gold standard diagnostic tool for sleep disorders. However, long examination times, high costs, specialized biosignal equipment and controlled settings requirements hinder large-scale data collection. As artificial intelligence applications in sleep research expand, structural heterogeneity in PSG data across institutions complicates multi-center integration, increases preprocessing burden, and limits reproducible large-scale algorithm validation. We investigated biosignals, sleep parameters, and demographic features from eight publicly available PSG datasets. A set of schemas for PSG harmonization is proposed to formalize unified structural specifications aligned with established clinical guidelines. These schemas systematically integrate heterogeneous biosignals, derived sleep parameters, and demographic features to achieve consistent attribute selection and uniform preprocessing across datasets. When applied to construct an integrated dataset, the schemas demonstrated stable demographic and clinical distributions through repeated sampling. By addressing schema-level interoperability, the proposed framework facilitates consistent algorithm evaluation and comparison and provides a structured reference for reproducible, large-scale sleep research.

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Cite

BibTeXRIS
BibTeX
@article{han2026polysomnography,
  title = {{Polysomnography harmonization schemes: A multi-institutional sleep research resource}},
  author = {Yujin Han and Gayeon Ryu and Yeongdon Kim and Hangsik Shin},
  journal = {PLOS One},
  year = {2026},
  month = nov,
  doi = {10.1371/journal.pone.0361116},
  url = {https://doi.org/10.1371/journal.pone.0361116},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Polysomnography harmonization schemes: A multi-institutional sleep research resource
AU  - Yujin Han
AU  - Gayeon Ryu
AU  - Yeongdon Kim
AU  - Hangsik Shin
PY  - 2026
DA  - 2026/11/05
JO  - PLOS One
DO  - 10.1371/journal.pone.0361116
UR  - https://doi.org/10.1371/journal.pone.0361116
AB  - Sleep disorders are associated with cardiovascular diseases and cognitive decline worldwide, highlighting the need for effective therapeutic strategies. Polysomnography (PSG) is the gold standard diagnostic tool for sleep disorders. However, long examination times, high costs, specialized biosignal equipment and controlled settings requirements hinder large-scale data collection. As artificial intelligence applications in sleep research expand, structural heterogeneity in PSG data across institutions complicates multi-center integration, increases preprocessing burden, and limits reproducible large-scale algorithm validation. We investigated biosignals, sleep parameters, and demographic features from eight publicly available PSG datasets. A set of schemas for PSG harmonization is proposed to formalize unified structural specifications aligned with established clinical guidelines. These schemas systematically integrate heterogeneous biosignals, derived sleep parameters, and demographic features to achieve consistent attribute selection and uniform preprocessing across datasets. When applied to construct an integrated dataset, the schemas demonstrated stable demographic and clinical distributions through repeated sampling. By addressing schema-level interoperability, the proposed framework facilitates consistent algorithm evaluation and comparison and provides a structured reference for reproducible, large-scale sleep research.
SN  - 1932-6203
ER  -