AIMC Topic: Respiration

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A Proactive Attack Detection for Heating, Ventilation, and Air Conditioning (HVAC) System Using Explainable Extreme Gradient Boosting Model (XGBoost).

Sensors (Basel, Switzerland)
The advent of Industry 4.0 has revolutionized the life enormously. There is a growing trend towards the Internet of Things (IoT), which has made life easier on the one hand and improved services on the other. However, it also has vulnerabilities due ...

GRASPNET: Fast spatiotemporal deep learning reconstruction of golden-angle radial data for free-breathing dynamic contrast-enhanced magnetic resonance imaging.

NMR in biomedicine
The purpose of the current study was to develop a deep learning technique called Golden-angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic contrast-enhanced 4D MRI acquired with golden-angle radial k-space trajectories...

Clinical applicability of deep learning-based respiratory signal prediction models for four-dimensional radiation therapy.

PloS one
For accurate respiration gated radiation therapy, compensation for the beam latency of the beam control system is necessary. Therefore, we evaluate deep learning models for predicting patient respiration signals and investigate their clinical feasibi...

Multi-Level Classification of Driver Drowsiness by Simultaneous Analysis of ECG and Respiration Signals Using Deep Neural Networks.

International journal of environmental research and public health
The high number of fatal crashes caused by driver drowsiness highlights the need for developing reliable drowsiness detection methods. An ideal driver drowsiness detection system should estimate multiple levels of drowsiness accurately without interv...

A meta-learning algorithm for respiratory flow prediction from FBG-based wearables in unrestrained conditions.

Artificial intelligence in medicine
The continuous monitoring of an individual's breathing can be an instrument for the assessment and enhancement of human wellness. Specific respiratory features are unique markers of the deterioration of a health condition, the onset of a disease, fat...

Prediction of the position of external markers using a recurrent neural network trained with unbiased online recurrent optimization for safe lung cancer radiotherapy.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: During lung cancer radiotherapy, the position of infrared reflective objects on the chest can be recorded to estimate the tumor location. However, radiotherapy systems have a latency inherent to robot control limitations tha...

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

Advanced materials (Deerfield Beach, Fla.)
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...

Contactless monitoring of human respiration using infrared thermography and deep learning.

Physiological measurement
. 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...

Non-Contact Spirometry Using a Mobile Thermal Camera and AI Regression.

Sensors (Basel, Switzerland)
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...

Real-time 3D motion estimation from undersampled MRI using multi-resolution neural networks.

Medical physics
PURPOSE: To enable real-time adaptive magnetic resonance imaging-guided radiotherapy (MRIgRT) by obtaining time-resolved three-dimensional (3D) deformation vector fields (DVFs) with high spatiotemporal resolution and low latency (  ms). Theory and M...