Longitudinal, EEG-based assessment of sleep in people with epilepsy: An automated sleep staging algorithm non-inferior to human raters.

ABSTRACT:

Objective

There is an unmet need in epilepsy management for tools that measure sleep objectively over long timespans. Subcutaneous EEG is well-suited for the task, but it requires a reliable automatic algorithm. Here, we present and evaluate such an algorithm, and we show clinical examples of how it produces important information.

Methods

A mix of scalp EEG and subcutaneous EEG was used to develop an algorithm to output sleep stages and common sleep parameters. The algorithm was tested on unseen data from 11 healthy subject and 12 people with epilepsy (PwE). Lastly, data (>3months) from three exemplary PwE were analyzed for sleep.

Results

The algorithm proved non-inferior at sleep stage segmentation on data from PwE compared to human raters using scalp EEG. It reached

SUBMITTER: Helge AW 

PROVIDER: S-EPMC11833292 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature