2 papers with code • 4 benchmarks • 1 datasets
Using multiple modalities such as EEG+EOG, EEG+HR instead of just relying on EEG (polysomnography)
We employ the Montreal Archive of Sleep Studies (MASS) database consisting of 200 subjects as the source domain and study deep transfer learning on three different target domains: the Sleep Cassette subset and the Sleep Telemetry subset of the Sleep-EDF Expanded database, and the Surrey-cEEGrid database.
Ranked #1 on Multimodal Sleep Stage Detection on Sleep-EDF-SC
We developed a framework to compare automated approaches to a consensus of multiple human scorers.
Ranked #1 on Sleep Stage Detection on DODH