AIMC Topic: Respiratory Rate

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A Deep-Learning-Assisted On-Mask Sensor Network for Adaptive Respiratory Monitoring.

Advanced materials (Deerfield Beach, Fla.) May 16, 2022
Wearable respiratory monitoring is a fast, non-invasive, and convenient approach to provide early recognition of human health abnormalities like restrictive and obstructive lung diseases. Here, a computational fluid dynamics assisted on-mask sensor n...
Humans Respiration Signal-To-Noise Ratio Respiratory Rate Deep Learning Monitoring, Physiologic
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Contactless monitoring of human respiration using infrared thermography and deep learning.

Physiological measurement Mar 17, 2022
. To monitor the human respiration rate (RR) using infrared thermography (IRT) and artificial intelligence, in a completely contactless, automated, and non-invasive manner.. The human breathing signals (BS) were obtained using IRT, by plotting the ch...
Humans Thermography Artificial Intelligence Respiratory Rate Deep Learning Respiration
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Deep learning for predicting respiratory rate from biosignals.

Computers in biology and medicine Mar 2, 2022
In the past decade, deep learning models have been applied to bio-sensors used in a body sensor network for prediction. Given recent innovations in this field, the prediction accuracy of novel models needs to be evaluated for bio-signals. In this pap...
Electrocardiography Electromyography Respiratory Rate Neural Networks, Computer Deep Learning
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Towards a Contactless Stress Classification Using Thermal Imaging.

Sensors (Basel, Switzerland) Jan 27, 2022
Thermal cameras capture the infrared radiation emitted from a body in a contactless manner and can provide an indirect estimation of the autonomic nervous system (ANS) dynamics through the regulation of the skin temperature. This study investigates t...
Humans Algorithms Support Vector Machine Autonomic Nervous System Diagnostic Imaging Respiratory Rate
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Non-Contact Spirometry Using a Mobile Thermal Camera and AI Regression.

Sensors (Basel, Switzerland) Nov 15, 2021
Non-contact physiological measurements have been under investigation for many years, and among these measurements is non-contact spirometry, which could provide acute and chronic pulmonary disease monitoring and diagnosis. This work presents a feasib...
Artificial Intelligence Respiration Spirometry Humans Exhalation Respiratory Rate
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eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19.

PloS one Sep 24, 2021
We present an interpretable machine learning algorithm called 'eARDS' for predicting ARDS in an ICU population comprising COVID-19 patients, up to 12-hours before satisfying the Berlin clinical criteria. The analysis was conducted on data collected f...
Critical Illness Female Risk Factors Aged SARS-CoV-2 Humans Machine Learning COVID-19 Respiratory Distress Syndrome Male Oxygen Aged, 80 and over Middle Aged Adult Models, Biological Adolescent Medical Records Systems, Computerized Respiratory Rate
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Determining respiratory rate from photoplethysmogram and electrocardiogram signals using respiratory quality indices and neural networks.

PloS one Apr 8, 2021
Continuous and non-invasive respiratory rate (RR) monitoring would significantly improve patient outcomes. Currently, RR is under-recorded in clinical environments and is often measured by manually counting breaths. In this work, we investigate the u...
Photoplethysmography Electrocardiography Respiratory Rate Humans Neural Networks, Computer
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Remote Patient Monitoring Using Radio Frequency Identification (RFID) Technology and Machine Learning for Early Detection of Suicidal Behaviour in Mental Health Facilities.

Sensors (Basel, Switzerland) Jan 24, 2021
Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and gain patient related information in clinics. RPM can be achieved with noninvasive digital technology without hindering a patient's daily activities and...
Radio Frequency Identification Device Humans Machine Learning Monitoring, Physiologic Respiratory Rate Technology
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Non-Invasive Sheep Biometrics Obtained by Computer Vision Algorithms and Machine Learning Modeling Using Integrated Visible/Infrared Thermal Cameras.

Sensors (Basel, Switzerland) Nov 6, 2020
Live sheep export has become a public concern. This study aimed to test a non-contact biometric system based on artificial intelligence to assess heat stress of sheep to be potentially used as automated animal welfare assessment in farms and while in...
Sheep Respiratory Rate Algorithms Computers Artificial Intelligence Animals Machine Learning
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Predicting dairy cattle heat stress using machine learning techniques.

Journal of dairy science Oct 31, 2020
The objectives of the study were to use a heat stress scoring system to evaluate the severity of heat stress on dairy cows using different heat abatement techniques. The scoring system ranged from 1 to 4, where 1 = no heat stress; 2 = mild heat stres...
Hot Temperature Dairying Respiratory Rate Cattle Heat Stress Disorders Lactation Machine Learning Temperature Cattle Diseases Body Temperature Female Bayes Theorem Milk Animals
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