ResMed CPAP data collection service for Home Assistant. Collects therapy data via ez Share WiFi SD card with OSCAR-compatible metrics.
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Updated
Aug 7, 2026 - C++
ResMed CPAP data collection service for Home Assistant. Collects therapy data via ez Share WiFi SD card with OSCAR-compatible metrics.
Toward Sleep Apnea Detection with Lightweight Multi-scaled Fusion Network
Docker Image for Open Source CPAP Analysis Reporter (OSCAR)
Free, open-source airway analysis for ResMed CPAP/BiPAP data
😴 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.
Tool to import .edf files (particularly from CPAP machines) to influxdb or victoriametrics.
A CPAP/BiPAP data visualizer for sleep apnea and UARS.
A standalone, high-performance desktop analytics application for in-depth analysis. Now supporting more device models.
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
Import Apple Watch sleep data into OSCAR sleep apnea software by converting Apple Health exports to Dreem-compatible CSV files.
Command-line analyzer for Wellue O2Ring overnight pulse-oximetry CSV exports: SpO2 statistics, ODI (3%/4%), desaturation events, nadir, and CSV/JSON/Excel reports. Supported by Night Time Comfort.
Audio-based snore and sleep apnea detection on smartphones — two CNN baselines with multi-seed bootstrap validation.
Curated list of tools, devices, datasets and open-source software for tracking and analyzing sleep: pulse oximetry, PAP therapy, wearables, EEG, and the metrics behind them.
Prototype of EEG-based sleep-apnea risk prediction using by a compact RR-CNN.
A Fuzzy Expert System for AstronoHybrid fuzzy expert system for sleep apnea detection from ECG signals using calibrated ML ensemble and interpretable fuzzy logic (XAI).mical Object Classification Using SDSS Photometric Data
EEG-based sleep apnea detection using 1D-CNN trained in MATLAB, implemented in Verilog on Xilinx Zynq-7000 FPGA - Final Year B.E. Project, CEG Anna University 2025
Sleep Apnea Detection with One-Dimensional Convolutional Neural Networks From Single-Lead Electrocardiogram
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.
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