TF-C Pretrain SleepEEG
datasetposted on 2022-05-31, 02:16 authored by Xiang ZhangXiang Zhang, Ziyuan ZhaoZiyuan Zhao, Theodoros Tsiligkaridis, Marinka Zitnik
- Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency
- Paper link:
- Github repo: https://github.com/mims-harvard/TFC-pretraining
- Project website:
SleepEEG contains 153 whole-night sleeping Electroencephalography (EEG) recordings that monitored by sleep cassette. The data is collected from 82 healthy subjects. The 1-lead EEG signal is sampled at 100 Hz. We segment the EEG signals into segments (window size is 200) without overlapping and each segment forms a sample. Every sample is associated with one of the five sleeping patterns/stages: Wake (W), Non-rapid eye movement (N1, N2, N3) and Rapid Eye Movement (REM).