ArticleScientific data2021
PSG-Audio, a scored polysomnography dataset with simultaneous audio recordings for sleep apnea studies.
Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Fine-Grained and Lightweight OSA Detection: A CRNN-Based Model for Precise Temporal Localization of Respiratory Events in Sleep Audio.Diagnostics (Basel, Switzerland) · 2026Article
- Polysomnography Dataset for Sleep Analysis in Ischemic Stroke Patients.Scientific data · 2026Article
- Identification of Comorbidities in Obstructive Sleep Apnea Using Diverse Data and a One-Dimensional Convolutional Neural Network.Sensors (Basel, Switzerland) · 2026Observational
- Estimating Sleep-Stage Distribution from Respiratory Sounds via Deep Audio Segmentation.Sensors (Basel, Switzerland) · 2025Article
- Deep learning approaches for image-based snoring sound analysis in the diagnosis of obstructive sleep apnea-hypopnea syndrome: A systematic review.World journal of radiology · 2025Article
- Non-Contact Screening of OSAHS Using Multi-Feature Snore Segmentation and Deep Learning.Sensors (Basel, Switzerland) · 2025Article
- A multimodal dataset for training deep learning models aimed at detecting and analyzing sleep apnea.Scientific data · 2025Article
- ApneaWhisper: Transformer-Based Audio Segmentation for Fine-Grained Non-Invasive Sleep Apnea Detection.Nature and science of sleep · 2025Article
- SiCRNN: A Siamese Approach for Sleep Apnea Identification via Tracheal Microphone Signals.Sensors (Basel, Switzerland) · 2024Article
- A multi-task learning model using RR intervals and respiratory effort to assess sleep disordered breathing.Biomedical engineering online · 2024Article
- Identification of OSAHS patients based on ReliefF-mRMR feature selection.Physical and engineering sciences in medicine · 2024Article
- HEAR4Health: a blueprint for making computer audition a staple of modern healthcare.Frontiers in digital health · 2023Review
- Tidal Volume Level Estimation Using Respiratory Sounds.Journal of healthcare engineering · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The sleep apnea syndrome is a chronic condition that affects the quality of life and increases the risk of severe health conditions such as cardiovascular diseases. However, the prevalence of the syndrome in the general population is considered to be heavily underestimated due to the restricted number of people seeking diagnosis, with the leading cause for this being the inconvenience of the current reference standard for apnea diagnosis: Polysomnography. To enhance patients' awareness of the syndrome, a great endeavour is conducted in the literature. Various home-based apnea detection systems are being developed, profiting from information in a restricted set of polysomnography signals. In particular, breathing sound has been proven highly effective in detecting apneic events during sleep. The development of accurate systems requires multitudinous datasets of audio recordings and polysomnograms. In this work, we provide the first open access dataset, comprising 212 polysomnograms along with synchronized high-quality tracheal and ambient microphone recordings. We envision this dataset to be widely used for the development of home-based apnea detection techniques and frameworks.
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