Surrey cEEGrid sleep data set

作者：Kaare B. Mikkelsen, James K. Ebajemito, María Ángeles Bonmatí-Carrión, Nayantara Santhi, Victoria L Revell, Giuseppe Atzori, Laura Birch, Ciro della Monica, Stefan Debener, Derk‐Jan Dijk, Annette Sterr, Maarten De Vos · 发表于：UC San Diego · 年份：2026 · DOI：10.82901/nemar.on005207.v1.0.0 · 研究领域：Computer science、Artificial intelligence、Speech recognition、Psychology、Machine learning、Audiology、Physical medicine and rehabilitation

This dataset comprises nightly electroencephalogram (EEG) recordings from 20 healthy participants collected during a wearable sleep monitoring study in spring 2017. The collection includes both full polysomnography (PSG) and cEEGrid measurements, with most subjects having recordings from the same night using both modalities. The data are formatted according to the Brain Imaging Data Structure (BIDS) and were previously used to develop machine learning approaches for automated sleep-wake staging.