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.
477 stars. No commits in the last 6 months.
Use this if you need an automated method to score sleep stages from single-channel EEG signals for research or clinical analysis.
Not ideal if you require a smaller, more efficient model with better performance, in which case you should look into TinySleepNet.
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477
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161
Language
Python
License
Apache-2.0
Category
Last pushed
Jul 19, 2024
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0
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