TF-C Pretrain SleepEEG

<p>- Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency</p> <p>- Paper link: </p> <p>- Github repo: https://github.com/mims-harvard/TFC-pretraining</p> <p>- Project website: </p> <p><br></p> <p><strong>SleepEEG </strong>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).</p> <p><br></p> <p><br></p>