AIMC Topic: Respiratory Rate
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Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.
Journal of clinical monitoring and computing
Sep 27, 2018
A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majority are difficult to identify even in a post-incident analysis. Changes in some patients' physiolog...
Humans
Machine Learning
Software
Systole
Respiratory Rate
Heart Arrest
Intensive Care Units, Pediatric
Sensitivity and Specificity
Monitoring, Physiologic
Infant
Blood Pressure
Child, Preschool
Oxygen
Child
Signal Processing, Computer-Assisted
Critical Illness
Heart Rate
Infant, Newborn
Critical Care
Reproducibility of Results
Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor.
IEEE journal of biomedical and health informatics
Jul 20, 2018
OBJECTIVE: Utilizing passive radio frequency identification (RFID) tags embedded in knitted smart-garment devices, we wirelessly detect the respiratory state of a subject using an ensemble-based learning approach over an augmented Kalman-filtered tim...
Real-time apnea-hypopnea event detection during sleep by convolutional neural networks.
Computers in biology and medicine
Jun 28, 2018
Sleep apnea-hypopnea event detection has been widely studied using various biosignals and algorithms. However, most minute-by-minute analysis techniques have difficulty detecting accurate event start/end positions. Furthermore, they require hand-engi...
Predicting heat stress index in Sasso hens using automatic linear modeling and artificial neural network.
International journal of biometeorology
Mar 17, 2018
There is an increasing use of robust analytical algorithms in the prediction of heat stress. The present investigation therefore, was carried out to forecast heat stress index (HSI) in Sasso laying hens. One hundred and sixty seven records on the the...
Adaptive neuro-fuzzy inference system for breath phase detection and breath cycle segmentation.
Computer methods and programs in biomedicine
Apr 14, 2017
BACKGROUND: The monitoring of the respiratory rate is vital in several medical conditions, including sleep apnea because patients with sleep apnea exhibit an irregular respiratory rate compared with controls. Therefore, monitoring the respiratory rat...
Cognitive bio-radar: The natural evolution of bio-signals measurement.
Journal of medical systems
Aug 30, 2016
In this article we discuss a novel approach to Bio-Radar, contactless measurement of bio-signals, called Cognitive Bio-Radar. This new approach implements the Bio-Radar in a Software Defined Radio (SDR) platform in order to obtain awareness of the en...
Prediction of Ventricular Tachycardia One Hour before Occurrence Using Artificial Neural Networks.
Scientific reports
Aug 26, 2016
Ventricular tachycardia (VT) is a potentially fatal tachyarrhythmia, which causes a rapid heartbeat as a result of improper electrical activity of the heart. This is a potentially life-threatening arrhythmia because it can cause low blood pressure an...
Remote triage support algorithm based on fuzzy logic.
Journal of the Royal Army Medical Corps
Jul 14, 2016
OBJECTIVES: This paper presents a remote triage support algorithm as a part of a complex military telemedicine system which provides continuous monitoring of soldiers' vital sign data gathered on-site using unobtrusive set of sensors.
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.
Enhanced Driver Stress Prediction from Multiple Biosignals via CNN Encoder-Decoder Model.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
In this work, we present PhysioFuseNet, a novel framework designed to enhance driver stress state classification. PhysioFuseNet integrates a CNN-based encoder-decoder model with multimodal biosignal fusion. Using a driving simulator, different multim...
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