Toward Sleep Apnea Detection with Lightweight Multi-scaled Fusion Network
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Updated
Mar 20, 2025 - Python
Toward Sleep Apnea Detection with Lightweight Multi-scaled Fusion Network
Docker Image for Open Source CPAP Analysis Reporter (OSCAR)
😴 DeepSleep2 is 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.
A CPAP/BiPAP data visualizer for sleep apnea and UARS.
Free, open-source airway analysis for ResMed CPAP/BiPAP data
Tool to import .edf files (particularly from CPAP machines) to influxdb or victoriametrics.
Screening Solution for Obstructive Sleep Apnea.
Repository for the Machine Learning for Smart Health System course offered by Dr. Juber Rahman at Omdena School platform. Join the course here https://omdena.com/omdena-school/
Sleep Apnea Classification using Deep Learning on ECG Signals
A real-time medical device prototype that uses Deep Learning (TinyML) to detect sleep apnea events from raw ECG signals directly on a microcontroller. This project demonstrates the end-to-end pipeline from training a 1D-CNN in Python to deploying optimized C code on bare-metal hardware.
Sleep Apnea Detection with One-Dimensional Convolutional Neural Networks From Single-Lead Electrocardiogram
Deep Learning based Sleep Apnea Detection using ECG Spectrograms and CNN-BiLSTM Architecture
Public transparency repository for the beyond-AHI hypoxic metrics OSA systematic review and meta-analysis submission package
Master MVA - Parsimonious Representations Project
📊 An open clinical dataset on AI-assisted Orofacial Myofunctional Therapy for Obstructive Sleep Apnea and Primary Snoring, following FAIR principles.
Production-ready ML pipeline for sleep apnea detection from ECG signals (AUROC: 0.755). Features HRV/QRS extraction, signal quality gating, and patient-level AHI estimation on 70 PhysioNet patients.
Explainable Machine Learning for ECG-Based Sleep Apnea Detection: Quantifying Cross-Dataset Generalisability
A python app to help users of ResMed CPAP Machines track their data and keep on top of replacement due dates
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