St. Vincent's University Hospital / University College Dublin Sleep Apnea Database
St. Vincent's University Hospital / University College Dublin Sleep Apnea Database (Oct. 9, 2007, midnight)
The St. Vincent's University Hospital / University College Dublin Sleep Apnea Database has been contributed to PhysioNet. This database contains 25 full overnight polysomnograms with simultaneous three-channel Holter ECG, from adult subjects with suspected sleep-disordered breathing.
Pollard, T., Moody, B. E., Lehman, L., Gow, B., Fernandes, C., Xie, C., Johnson, A., Mark, R. G., & Heldt, T. (2026). PhysioNet as a global platform for biomedical research. Nature Health. https://doi.org/10.1038/s44360-026-00096-z. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC13641116/
Abstract
This database contains 25 full overnight polysomnograms with simultaneous three-channel Holter ECG, from adult subjects with suspected sleep-disordered breathing. A revised version of this database was posted on 1 September 2011.
Subjects
Subjects were randomly selected over a 6-month period (September 02 to February 03) from patients referred to the Sleep Disorders Clinic at St Vincent's University Hospital, Dublin, for possible diagnosis of obstructive sleep apnea, central sleep apnea or primary snoring. Subjects had to be above 18 years of age, with no known cardiac disease, autonomic dysfunction, and not on medication known to interfere with heart rate. Twenty-five subjects (21M, 4F) were selected (age: 50 ± 10 years, range 28-68 years; BMI: 31.6 ± 4.0 kg/m², range 25.1-42.5 kg/m²; AHI: 24.1 ± 20.3, range 1.7-90.9). Details are shown in SubjectDetails.xls.)
Signals
Polysomnograms were obtained using the Jaeger-Toennies system (Erich Jaeger GmbH, Germany). Signals recorded were: EEG (C3-A2), EEG (C4-A1), left EOG, right EOG, submental EMG, ECG (modified lead V2), oro-nasal airflow (thermistor), ribcage movements, abdomen movements (uncalibrated strain gauges), oxygen saturation (finger pulse oximeter), snoring (tracheal microphone) and body position. The files named with .rec suffixes contain these signals in EDF format.
Three-channel Holter ECGs (V5, CC5, V5R) were recorded using a Reynolds Lifecard CF system (Reynolds Medical, UK); the files named with _lifecard.edf suffixes contain these ECG signals in EDF format. The recording dates and times are not available. In record ucddb002, only two distinct ECG signals were recorded; the second ECG signal was also used as the third signal.
Annotations
Sleep stages were scored by an experienced sleep technologist according to standard Rechtschaffen and Kales rules (see the _stage.txt files). Annotations/meanings in these files are:
- 0 - Wake
- 1 - REM
- 2 - Stage 1
- 3 - Stage 2
- 4 - Stage 3
- 5 - Stage 4
- 6 - Artifact
- 7 - Indeterminate
Onset time and duration of respiratory events (obstructive, central, mixed apneas and hypopneas, and periodic breathing episodes) were annotated by the same sleep technologist (see the _respevt.txt files). Terms used in these files include:
- 1st column - Time of occurrence (time of day)
- 2nd column
- HYP - Hypopnea
- C - Central
- O - Obstructive
- M - Mixed
- 3rd column - Periodic breathing (PB)/ Cheynes-Stokes (CS)
- 9th & 10th columns - Bradycardia/ Tachycardia
Acknowledgments
These recordings were collected at St. Vincent's University Hospital Sleep Disorders Clinic, under the direction of Prof. Walter McNicholas. Dr. Liam Doherty, Dr. Silke Ryan, and Dr. John Garvey collected and assembled the clinical and demographic information, and Ms. Patricia Boyle was responsible for polysomnogram scoring and annotation. Eric Chua was responsible for de-identification and electronic archiving of records.
Contact information
Conor Heneghan, PhD
School of Electrical, Electronic and Mechanical Engineering
University College Dublin
Belfield
Dublin 4
Ireland
Email: conor.heneghan at ucd dot ie
Technical contact: Eric C.-P. Chua (eric dot chua dot 2 at gmail dot com)
Cited by
19 publications cite this project. The most recent are listed below.
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Energy-efficient real-time 4-stage sleep classification at 10-second resolution
Zahra Mohammadi, Parnian Fazel, Siamak Mohammadi. Medical & Biological Engineering & Computing, 2026. -
A Dual-Channel CBFA Network for Sleep Respiratory Event Detection Using SpO2 and Nasal Airflow
Yihao Wang, Jie Gao, Wenxiu Shu et al. International Conference on Health Big Data, 2026. -
PIANet: a parallel interactive attention network for multi-channel PSG-based sleep staging
Xiang Li, Kebin Jia, Zheng Jin. Biomedical Physics & Engineering Express, 2026. -
Analysis of federated learning on non-independent and identically distributed sleep data
Adriana Anido-Alonso, Diego Álvarez-Estévez. Physiological Measurement, 2026. -
Polysomnography Dataset for Sleep Analysis in Ischemic Stroke Patients
Suvadeep Maiti, Shivam Kumar Sharma, Sivasubramanian Mythirayee et al. Scientific Data, 2026.
Citation data from OpenAlex. Papers that use the project without citing it may be missing.
Files
Total uncompressed size: 1.3 GB.
Access the files
- Download the ZIP file (757.4 MB)
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Download with the PhysioNet Python package:
physionet download ucddb --version 1.0.0
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Download the files using your terminal:
wget -r -N -c -np https://physionet.org/files/ucddb/1.0.0/
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Download the files using AWS command line tools:
aws s3 sync --no-sign-request s3://physionet-open/ucddb/1.0.0/ DESTINATION