AIMC Topic: Oximetry

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Predicting polysomnographic severity thresholds in children using machine learning.

Pediatric research
BACKGROUND: Approximately 500,000 children undergo tonsillectomy and adenoidectomy (T&A) annually for treatment of obstructive sleep disordered breathing (oSDB). Although polysomnography is beneficial for preoperative risk stratification in these chi...

Artificial neural network analysis of the oxygen saturation signal enables accurate diagnostics of sleep apnea.

Scientific reports
The severity of obstructive sleep apnea (OSA) is classified using apnea-hypopnea index (AHI). Accurate determination of AHI currently requires manual analysis and complicated registration setup making it expensive and labor intensive. Partially for t...

Convolutional Neural Networks for Spectroscopic Analysis in Retinal Oximetry.

Scientific reports
Retinal oximetry is a non-invasive technique to investigate the hemodynamics, vasculature and health of the eye. Current techniques for retinal oximetry have been plagued by quantitatively inconsistent measurements and this has greatly limited their ...

Analysis of parameters affecting blood oxygen saturation and modeling of fuzzy logic system for inspired oxygen prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Fraction of Inspired Oxygen is one of the arbitrary set ventilator parameters which has critical influence on the concentration of blood oxygen. Normally mechanical ventilators providing respiratory assistance are tuned manu...

Novel pediatric-automated respiratory score using physiologic data and machine learning in asthma.

Pediatric pulmonology
OBJECTIVES: Manual clinical scoring systems are the current standard used for acute asthma clinical care pathways. No automated system exists that assesses disease severity, time course, and treatment impact in pediatric acute severe asthma exacerbat...

A Supervised Approach to Robust Photoplethysmography Quality Assessment.

IEEE journal of biomedical and health informatics
Early detection of Atrial Fibrillation (AFib) is crucial to prevent stroke recurrence. New tools for monitoring cardiac rhythm are important for risk stratification and stroke prevention. As many of new approaches to long-term AFib detection are now ...

Measuring Oxygen Saturation With Smartphone Cameras Using Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Arterial oxygen saturation ([Formula: see text]) is an indicator of how much oxygen is carried by hemoglobin in the blood. Having enough oxygen is vital for the functioning of cells in the human body. Measurement of [Formula: see text] is typically e...

A Novel Artificial Neural Network Based Sleep-Disordered Breathing Screening Tool.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: This study evaluated a novel artificial neural network (ANN) based sleep-disordered breathing (SDB) screening tool incorporating nocturnal pulse oximetry with demographic, anatomic, and clinical data. The tool was compatible with 6 ...

Evaluation of Machine-Learning Approaches to Estimate Sleep Apnea Severity From At-Home Oximetry Recordings.

IEEE journal of biomedical and health informatics
Complexity, costs, and waiting list issues demand a simplified alternative for sleep apnea-hypopnea syndrome (SAHS) diagnosis. The blood oxygen saturation signal (SpO) carries useful information about SAHS and can be easily acquired from overnight ox...

Design and Construction of a Microcontroller-Based Ventilator Synchronized with Pulse Oximeter.

Journal of medical systems
This study aims to introduce a novel device with which mechanical ventilator and pulse oximeter work in synchronization. Serial communication technique was used to enable communication between the pulse oximeter and the ventilator. The SpO2 value and...