Audio-Polygraphy Dataset for Sleep Apnea Analysis (APSAA)

The Audio-Polygraphy Dataset for Sleep Apnea Analysis (APSAA) provides synchronized, full-night audio and polygraph recordings from 32 subjects, along with manual annotations for labeled events in the polygraph studies.  All subjects were provided with detailed information about the study, and written informed consent was obtained from those who agreed to take part. The recordings were collected between September 2021 and April 2022 at the Sleep Unit of Dr. Sagaz Hospital in Jaén (Spain). The study was approved by the Provincial Research Ethics Committee of Jaén (Spain).

Each subject’s data is organized in a designated folder named according to the subject’s unique identification code. Inside each folder, users will find: (1) the audio recording in WAV format, (2) separate CSV files for each polygraph signal, and (3) a CSV file containing manual annotations of polygraph events. The polygraph signals included are as follows:

• Abdomen_EG: Abdominal respiratory effort.
• Flow_EG: Nasal airflow from the nasal cannula.
• Pulse_EG: Pulse rate, measured in beats per minute.
• Snore_EG: Respiratory snore pressure envelope from the nasal cannula.
• SpO2_EG: Peripheral oxygen saturation percentage.
• Thermistor_EG: Oronasal thermal airflow.
• Thorax_EG: Thoracic respiratory effort.

Additionally, an automated algorithm for synchronizing audio and polygraph signals in sleep studies is provided, accessible via the following Github repository

Please note that use of the data is subject to the following conditions:

• Academic and Non-Commercial Use Only: The database is provided strictly for academic and non-commercial research purposes.

• Proper Acknowledgment: You agree to properly acknowledge the source of the database in any publication or work that makes use of it.

• No Redistribution: Redistribution, sharing, or selling of the database to third parties is not permitted without our explicit written consent.

If you use this dataset or the associated repository in your research, please cite it as follows:

Gonzalez-Martinez, F., De La Torre-Cruz, J., Carabias-Orti, J. et al. Polygraph and audio synchronization applied to apnea event analysis based on non-negative matrix factorization. J AUDIO SPEECH MUSIC PROC. 2025, 24 (2025). https://doi.org/10.1186/s13636-025-00410-9

Funding: This work was supported in part under grant 1257914 funded by Programa Operativo FEDER Andalucia 2014&ndas