Automated polysomnography for experimental animal research
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Updated
Nov 12, 2024 - Python
Automated polysomnography for experimental animal research
A compact U-Net-inspired convolutional neural network with 740,551 parameters, designed to predict non-apnea sleep arousals from full-length multi-channel polysomnographic recordings at 5-millisecond resolution. Achieves similar performance to DeepSleep with lower computational cost.
EEGLAB-compatible analysis software for manual / visual sleep stage scoring, signal processing and event marking of polysomnographic (PSG) data for MATLAB.
Method for detecting sleep spindles using EEGlab functions and datasets
Official implementation of our paper "ENHANCING HEALTHCARE WITH EOG: A NOVEL APPROACH TO SLEEP STAGE CLASSIFICATION"
Competitive apnea detector for polysomnographic data
Official implementation of our paper "Transparency in Sleep Staging: Deep Learning Method for EEG Sleep Stage Classification with Model Interpretability"
Forked from https://bitbucket.org/yehezkel/edf-parser
Detecting events in sleeping tinnitus patients
Source code for the paper "Automatic Actigraphy and Polysomnography Sleep Scoring using Deep Learning".
Document and code that generates the Sleep Statistics defined at the Surrey Sleep Research Centre
ScoreREM: A user friendly Matlab-GUI for rapid eye movement (REM) sleep microstructure annotation and quantification
ScoreREM: A user friendly Matlab-GUI for rapid eye movement (REM) sleep microstructure annotation and quantification
Extracts information from polysomnography reports generated by Compumedics Profusion and Natus Embla RemLogic software, and then exports the data to an Excel file.
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