AIMC Topic: Oximetry
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Automatic classification of apnea/hypopnea events through sleep/wake states and severity of SDB from a pulse oximeter.
Physiological measurement
Aug 11, 2015
This study proposes a method of automatically classifying sleep apnea/hypopnea events based on sleep states and the severity of sleep-disordered breathing (SDB) using photoplethysmogram (PPG) and oxygen saturation (SpO2) signals acquired from a pulse...
Reducing the incidence of oxyhaemoglobin desaturation during rapid sequence intubation in a paediatric emergency department.
BMJ quality & safety
Jul 16, 2015
OBJECTIVES: Rapid sequence intubation (RSI) is the standard for definitive airway management in emergency medicine. In a video-based study of RSI in a paediatric emergency department (ED), we reported a high degree of process variation and frequent a...
Respiratory gas exchange during robotic-assisted laparoscopic radical prostatectomy.
Journal of clinical anesthesia
Jul 3, 2015
STUDY OBJECTIVE: Robotic-assisted laparoscopic prostatectomy requires patients to be secured in a steep Trendelenburg position for several hours. Added to the CO2 pneumoperitoneum that is created, this positioning invariably restricts diaphragmatic a...
An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping method.
The Journal of infection
Dec 23, 2014
OBJECTIVES: To classify higher-risk influenza patients within 10 s, we developed an infectious disease and fever screening radar system.
A Comparative Analysis of Federated and Centralized Learning for SpO2 Prediction in Five Critical Care Databases.
Studies in health technology and informatics
Aug 22, 2024
This study explores the potential of federated learning (FL) to develop a predictive model of hypoxemia in intensive care unit (ICU) patients. Centralized learning (CL) and local learning (LL) approaches have been limited by the localized nature of d...
Machine learning-based prediction of cerebral oxygen saturation based on multi-modal cerebral oximetry data.
Health informatics journal
Jan 1, 2024
This study develops machine learning-based algorithms that facilitate accurate prediction of cerebral oxygen saturation using waveform data in the near-infrared range from a multi-modal oxygen saturation sensor. Data were obtained from 150,000 observ...
A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2023
Characterization of sleep stages is essential in the diagnosis of sleep-related disorders but relies on manual scoring of overnight polysomnography (PSG) recordings, which is onerous and labor-intensive. Accordingly, we aimed to develop an accurate d...
Deep-Learning Model Based on Convolutional Neural Networks to Classify Apnea-Hypopnea Events from the Oximetry Signal.
Advances in experimental medicine and biology
Jan 1, 2022
Automated analysis of the blood oxygen saturation (SpO) signal from nocturnal oximetry has shown usefulness to simplify the diagnosis of obstructive sleep apnea (OSA), including the detection of respiratory events. However, the few preceding studies ...
Toward accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in three dimensions.
Journal of biomedical optics
Aug 1, 2020
SIGNIFICANCE: Two-dimensional (2-D) fully convolutional neural networks have been shown capable of producing maps of sO2 from 2-D simulated images of simple tissue models. However, their potential to produce accurate estimates in vivo is uncertain as...
Reducing False Alarm Rates in Neonatal Intensive Care: A New Machine Learning Approach.
Advances in experimental medicine and biology
Jan 1, 2020
UNLABELLED: In neonatal intensive care units (NICUs), 87.5% of alarms by the monitoring system are false alarms, often caused by the movements of the neonates. Such false alarms are not only stressful for the neonates as well as for their parents and...
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