AIMC Topic: Respiratory Rate

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Detection of respiratory rate using a classifier of waves in the signal from a FBG-based vital signs sensor.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Monitoring of changes in respiratory rate provides information on a patient's psychophysical state. This paper presents a respiratory rate detection method based on analysis of signals from a fiber Bragg grating (FBG)-based ...

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...

Noninvasive prediction of Blood Lactate through a machine learning-based approach.

Scientific reports
We hypothesized that blood lactate concentration([Lac]) is a function of cardiopulmonary variables, exercise intensity and some anthropometric elements during aerobic exercise. This investigation aimed to establish a mathematical model to estimate [L...

Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

Journal of clinical monitoring and computing
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...

Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor.

IEEE journal of biomedical and health informatics
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
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
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
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
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
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...