Breath Sample

Breath sample analysis is emerging as a powerful non-invasive diagnostic tool, leveraging the unique volatile organic compound (VOC) profiles and even the physical properties of exhaled breath to detect diseases and authenticate individuals. Current research heavily utilizes machine learning algorithms, including support vector machines, deep learning models, and gradient boosted trees, to analyze breath data obtained through various sensing technologies, such as magnetic respiratory sensing and laser spectroscopy. These methods show promise in diagnosing respiratory illnesses like COVID-19 and lung cancer with high accuracy, potentially revolutionizing point-of-care diagnostics and personalized medicine through rapid, non-invasive screening. Furthermore, breath analysis is being explored for biometric authentication, exploiting the unique characteristics of individual breathing patterns.