Abstract
Speckle pattern analysis become a widespread method for remote sensing of various biomedical parameters. This technique is based on tracking the secondary speckle patterns reflected from a human skin illuminated by a laser beam. Speckle pattern variations can be translated into the corresponding partial carbon dioxide (CO2) state (High or Normal) in the bloodstream. We present a novel approach for remote sensing of human blood carbon dioxide partial pressure (PCO2) based on speckle pattern analyses combined with machine learning approach. The blood CO2 partial pressure is an important indicative parameter for a variety of malfunctions in the human body.
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