In many functional magnetic resonance imaging (fMRI) studies, respiratory signals are unavailable or do not have acceptable quality due to issues with subject compliance, equipment failure or signal error. In large databases, such as the Human Connec...
Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activity at the body's center of mass and on the chest, respectively. Since their inception, their potenti...
Real-time tracking of a target volume is a promising solution for reducing the planning margins and both dosimetric and geometric uncertainties in the treatment of thoracic and upper-abdomen cancers. Respiratory motion prediction is an integral part ...
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...
. 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...
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...
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...
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...
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...
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...
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