German University Releases Open-Source AI Model AnySleep for Second-Level Sleep Analysis

A research team at the University of Applied Sciences Aachen (FH Aachen) in Germany has developed AnySleep, an open-source artificial intelligence model designed to analyze human sleep data. The findings were recently published in npj Digital Medicine, a peer-reviewed journal belonging to the Nature Portfolio.

Traditional sleep analysis typically records brain activity via electroencephalography (EEG) and divides nightly data into 30-second segments to assign sleep stages. This coarse granularity often misses brief wake events or subtle changes in brain activity that last only a few seconds. AnySleep processes nocturnal measurement data to map shorter intervals on a second-by-second basis, creating a more detailed overall picture of sleep phases. Study author Stephan Bialonski noted that if the evaluation interval is too long, these changes are not adequately considered, leading to inaccurate results.

The model was trained on sleep data from approximately 20,000 subjects, varying widely in age, living conditions, and health status. While AnySleep has already succeeded in identifying differences in sleep structures between healthy individuals and those with diseases, providing clues to certain clinical patterns, Bialonski emphasized that the technology is not yet suitable for making medical diagnoses. The project continues in cooperation with several hospitals.

The source code for AnySleep is publicly accessible and can theoretically be installed on any computer. Additionally, FH Aachen offers a browser interface called SomnoBot, allowing users to utilize the AI tool without coding knowledge. According to the press release, sensitive data never leaves the local computer, making the work data protection-compliant even in strict clinical research environments.