An open-source, high-performance tool for automated sleep staging

By R. Vallat, Matthew P. Walker. eLife, 2021

307 citations recorded by the source corpus.

The clinical and societal measurement of human sleep has increased exponentially in recent years. However, unlike other fields of medical analysis that have become highly automated, basic and clinical sleep research still relies on human visual scoring. Such human-based evaluations are time-consuming, tedious, and can be prone to subjective bias. Here, we describe a novel algorithm trained and validated on +30,000 hr of polysomnographic sleep recordings across heterogeneous populations around the world. This tool offers high sleep-staging accuracy that matches human scoring accuracy and interscorer agreement no matter the population kind. The software is designed to be especially easy to use, computationally low-demanding, open source, and free. Our hope is that this software facilitates the broad adoption of an industry-standard automated sleep staging software package.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Physiology

View Paper: https://www.semanticscholar.org/paper/0c4202286cf0f986c7e9919d8198845f9e08c8c8

Citations in the corpus

• The development of aperiodic neural activity in the human brain (2024, unknown): “Furthermore, our study lays the groundwork for investigating memory dysfunction in psychiatric disorders, many of which emerge during adolescence and young adulthood, and which show deviations in aperiodic activity from healthy populations 23–26 .”