AIMC Topic: Exhalation

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Deep-Learning-Based Blood Glucose Detection Device Using Acetone Exhaled Breath Sensing Features of α-FeO-MWCNT Nanocomposites.

ACS applied materials & interfaces
Owing to the correlation between acetone in human's exhaled breath (EB) and blood glucose, the development of EB acetone gas-sensing devices is important for early diagnosis of diabetes diseases. In this article, a noninvasive blood glucose detection...

Ppb-Level Ammonia Sensor for Exhaled Breath Diagnosis Based on UV-DOAS Combined with Spectral Reconstruction Fitting Neural Network.

ACS sensors
Ammonia (NH) in exhaled breath (EB) has been a biomarker for kidney function, and accurate measurement of NH is essential for early screening of kidney disease. In this work, we report an optical sensor that combines ultraviolet differential optical ...

User authentication system based on human exhaled breath physics.

PloS one
This work, in a pioneering approach, attempts to build a biometric system that works purely based on the fluid mechanics governing exhaled breath. We test the hypothesis that the structure of turbulence in exhaled human breath can be exploited to bui...

Ultra-sensitive analysis of exhaled biomarkers in ozone-exposed mice via PAI-TOFMS assisted with machine learning algorithms.

Journal of hazardous materials
Ground-level ozone ranks sixth among common air pollutants. It worsens lung diseases like asthma, emphysema, and chronic bronchitis. Despite recent attention from researchers, the link between exhaled breath and ozone-induced injury remains poorly un...

COPD stage detection: leveraging the auto-metric graph neural network with inspiratory and expiratory chest CT images.

Medical & biological engineering & computing
Chronic obstructive pulmonary disease (COPD) is a common lung disease that can lead to restricted airflow and respiratory problems, causing a significant health, economic, and social burden. Detecting the COPD stage can provide a timely warning for p...

Exhaled breath signal analysis for diabetes detection: an optimized deep learning approach.

Computer methods in biomechanics and biomedical engineering
In this study, a flexible deep learning system for breath analysis is created using an optimal hybrid deep learning model. To improve the quality of the gathered breath signals, the raw data are first pre-processed. Then, the most relevant features l...

A pilot study for the prediction of liver function related scores using breath biomarkers and machine learning.

Scientific reports
Volatile organic compounds (VOCs) present in exhaled breath can help in analysing biochemical processes in the human body. Liver diseases can be traced using VOCs as biomarkers for physiological and pathophysiological conditions. In this work, we pro...

A Machine-Learning Model for Lung Age Forecasting by Analyzing Exhalations.

Sensors (Basel, Switzerland)
Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadvantages that this can entail. This limits their use and consequently, the supervision of patients. R...

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...

Few-shot learning for deformable image registration in 4DCT images.

The British journal of radiology
OBJECTIVES: To develop a rapid and accurate 4D deformable image registration (DIR) approach for online adaptive radiotherapy.