This is an online service for automated analysis of nocturnal pulse oximetry in children aged 2-18 years. AI models are used for Sleep and Wake staging, and to predict the presence or absence, and severity of sleep disordered breathing.

Learn more about the machine learning model used, including peer-reviewed validation studies.

Substantial emphasis is placed on explainable AI to build clinician trust and confidence. Measures of uncertainty, global and local explanation methods, and data visualisation accompany AI-generated predictions. Furthermore, models use clinically relevant oximetric features that are familiar to sleep paediatricians.

Accepted uploads are exported oximetry data in a delimited text format. Most popular oximetry extraction and analysis tools allow for the exporting of oximetry data. Note: EDF files must be converted to text format.

No oximetry data on-hand? Sample oximetry data are available for you to try.

This service is currently for academic and non-commercial purposes only. It is not approved for clinical use.

This model was trained and evaluated on children aged 2-18 years. Performance cannot be guaranteed in children aged less than 2 years, or in adults.

Oximetry data sampled at 0.5Hz, with a Masimo SET averaging time of 2-4 seconds, were used for model training. Oximetry data sampled at a rate above or below 0.5Hz must be decimated or interpolated (with care), respectively. These processes are not performed through this service, they must be completed prior to upload. Oximetry data collected using prolonged averaging times may result in unreliable predictions.

Testing has been performed on Masimo and Nonin oximeters, and performance cannot be guaranteed on other oximeter makes.