DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

YASA (Yet Another Spindle Algorithm): a Python package to analyze polysomnographic sleep recordings.

U-Time: A Fully Convolutional Network for Time Series Segmentation

TinySleepNet: 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

Sleep As Android integration for Home Assistant

An open-source sleep stage classification Python package

Dreamento (DReam ENgenieering TOolbox): a Python-based software for dream engineering while monitoring/analyzing real-time EEG data.

EEGLAB-compatible analysis software for manual / visual sleep stage scoring, signal processing and event marking of polysomnographic (PSG) data for MATLAB.

Helper functions for the SNORE project

A ML model that scans the driver for drowsiness and alerts them incase of danger while driving. Alerts are send via Telegram message and audio cue. Also includes various features such as information of where you last fell asleep, analysis of trip, and recommendations based on when you should take rest and when you were most drowsy.

End-to-end Sleep Staging with Raw Single Channel EEG, BHI 19

Sleep stage automatic classifier using CNNs and LSTMs to process frequency signals of brain activity recorded via ElectroEncephaloGram EEG. Undergraduate thesis

Luna software for sleep EEG analysis (base)

Example conversion of Angular to Cordova

View your sleep diary

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.

Documentation and code for manipulating sleep diaries

Stay Awake, Arrive Safely: Your Guardian Against Drowsy Driving

sleep scoring based on intracranial recordings