24 skills found
raphaelvallat / YasaYASA (Yet Another Spindle Algorithm): a Python package to analyze polysomnographic sleep recordings.
akaraspt / DeepsleepnetDeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
nickmmark / Brain Eeg GraphArduino EEG interface for lucid dreaming
emadeldeen24 / AttnSleep[TNSRE 2021] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"
MousaviSajad / SleepEEGNetSleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach
akaraspt / TinysleepnetTinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College London respectively
skjerns / AutoSleepScorerAn open-source sleep stage classification Python package
wonambi-python / WonambiPackage to analyze EEG, ECoG and other electrophysiology formats. It allows for visualization of the results and for a GUI that can be used to score sleep stages.
dlcjfgmlnasa / NeuroNet[Arxiv] NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG
drasros / Sleep Staging ShhsCode for the paper "A Convolutional neural network for sleep stage scoring from raw single-channel EEG"
predict-idlab / Sleep LinearDo not sleep on traditional machine learning for sleep stage scoring
dlcjfgmlnasa / SynthSleepNet[IEEE TCYB] Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid Self-Supervised Learning Framework
flower-kyo / Tinysleepnet PytorchTinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG
stuartfogel / CountingSheepPSGEEGLAB-compatible analysis software for manual / visual sleep stage scoring, signal processing and event marking of polysomnographic (PSG) data for MATLAB.
anasimtiaz / Sleep DatasetsSleep datasets obtained using PSG for automatic sleep stage scoring.
thucdx / TSleepAutomated Sleep Stage Scoring using Deep Learing
biomedical-signal-processing / Deepsleepnet LiteDeepSleepNet-Lite: A Simplified Automatic Sleep Stage Scoring Model With Uncertainty Estimates
EdithChorev / Automatic Sleep ScoringThe goal is to create an automatic (preferably online) scoring of sleep stage scoring using raw EEG signals
baroquerock / Sleep Stages ScoringNo description available
abhisheksahu-iitk / Sleep Quality AnalysisSleep stage classification is one of the critical methodologies for the diagnosis of sleep-related diseases and complications. The conventional method of categorization is quite clumsy and timeconsuming. This project aims to devise a deep learning and machine learning model for automatic classification of sleep stage, hence, removing the barrier of conventional method and expert ubiquity. In this work, we have considered a database that carries 197-night sleep polysomnographic data. Moreover, we aimed to classify this data into stages W, N1, N2, N3 and N4 as mentioned in the AASM standard. In addition to that, we have selected the EEG FpzCz channel because of its better quality and used an epoch time of 30 seconds for signal processing. We have used four machine learning and deep learning methods, namely CNN-CNN, CNN-LSTM, Random Forest, and XGBoosting, with 82%, 87%, 51%, and 59%, respectively. This report has depicted a roadmap of the EEG-based sleep stage scoring method by implementing the state of art methods. In conclusion, using better signal processing techniques will increase the overall performance and accuracy of the model.
