sleep-disorders

Source code for the deep learning models employed in OSAS study

View your sleep diary

An overview of CRD-related projects that are currently being worked on

This repository offers a pipeline for classifying insomnia using EEG, EMG, EOG, and ECG signals, featuring early and late fusion, signal preprocessing, feature extraction, and machine learning models for accurate detection.

Use Emacs Org-mode to graph your sleep pattern.

A report for use by sleep doctors

Documentation and code for manipulating sleep diaries

Analyse your sleep diary

A complete pipeline for comparing cardiac variability measures derived from ECG signals and PPG signals during sleep.

Analysis of BMI and its relationship with sleep disorders, blood pressure, and smoking using the NHANES 2017-2018 dataset, with R for statistical Modeling.

💤This project aims to develop an automated method for detecting sleep disorders from heart rate signals.

The Sleep Health and Lifestyle Dataset comprises 400 rows and 13 columns, covering a wide range of variables related to sleep and daily habits. It includes details such as gender, age, occupation, sleep duration, quality of sleep, physical activity level, stress levels, BMI category, blood pressure, heart rate, daily steps, and sleep disorders.

Link to DagsHub repository :

Sleep Disorder Prediction with Multinomial Logistic Regression

This project predicts the likelihood of sleep disorders based on various health and lifestyle factors.

Track leg movements during sleep from a Wear OS watch worn at the ankle. Measures the rhythm of periodic limb movements (PLMS) linked to restless legs syndrome and PLMD. Open source, no account, no network. Not a medical device.

Sleep Health & Lifestyle Analysis Tool: An AI-powered desktop application that analyzes biometric data to predict sleep quality and detect potential sleep disorders using machine learning models.

Network Pathway analysis approach to understanding the comorbidity of Sleep disorders with Autism Spectrum Disorder