deepsleepnet and CareSleepNet
About deepsleepnet
akaraspt/deepsleepnet
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
This project helps sleep researchers and clinicians automatically categorize sleep stages from raw, single-channel EEG data. It takes raw EEG recordings as input and outputs the corresponding sleep stages, enabling faster and more consistent sleep analysis. Researchers and clinicians studying sleep disorders or sleep patterns would use this.
About CareSleepNet
wjq-learning/CareSleepNet
[JBHI 2024] CareSleepNet: A Hybrid Deep Learning Network for Automatic Sleep Staging
This tool helps automate the process of sleep staging from raw physiological signals. You input overnight polysomnography (PSG) data, and it outputs an automatic classification of sleep stages (Wake, N1, N2, N3, REM). This is intended for sleep researchers, clinicians, or technicians who analyze sleep patterns.
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