YASA (Yet Another Spindle Algorithm): a Python package to analyze polysomnographic sleep recordings.
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Updated
Sep 27, 2026 - Python
YASA (Yet Another Spindle Algorithm): a Python package to analyze polysomnographic sleep recordings.
[TNSRE 2021] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"
Sleep stage detection using ECG
An open-source sleep stage classification Python package
[IEEE JBHI] "MultiChannelSleepNet: A Transformer-Based Model for Automatic Sleep Stage Classification With PSG"
[TNSRE 2023] Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation
Official implementation of our MICCAI 2022 paper "mulEEG: A Multi-View Representation Learning on EEG Signals"
This is an official implementation for "Intra- and inter-epoch temporal context network (IITNet) using sub-epoch features for automatic sleep scoring on raw single-channel EEG".
[AAAI 2024] Generalizable Sleep Staging via Multi-Level Domain Alignment
Notebooks for training the classifier of YASA sleep staging
EEGLAB-compatible analysis software for manual / visual sleep stage scoring, signal processing and event marking of polysomnographic (PSG) data for MATLAB.
ICLR 2023 paper - ManyDG - Dataset processing and mode codes
Sleep staging from ECG, assisted with EEG
Official implementation of "A Knowledge Distillation Framework for Enhancing Ear-EEG based Sleep Staging with Scalp-EEG Data"
[JBHI 2024] CareSleepNet: A Hybrid Deep Learning Network for Automatic Sleep Staging
The Neural Interface Foundation Challenge — NeurIPS 2026 Sydney. An open-source brain-decoding benchmark with four tracks across EEG, EMG, sleep, and BCI.
Neural-networks based sleep staging in tensorflow, and evalutation with Fourier-transform based surrogates.
Desktop app for scoring mouse sleep from EEG, EMG, and norepinephrine recordings — visualize, auto-score with a neural network, correct by hand, and export sleep statistics.
a python framework to process and visualize BioSignal channel data in Real-time.
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