Numerical methods for a personalized autonomous transcutaneous gas monitoring device

Published : 10 January 2019

Respiratory diseases do affect the gas exchange between blood and exhaled air, and thus the blood concentration of biomarkers. Measuring gas skin emanations of volatile blood components such as carbon dioxide allows a continuous monitoring of their concentration. The laboratory LS2P dedicated to wearable devices for healthcare is developing an innovative wristband device based on optical infrared measurement to quantify the partial pressure of transcutaneous carbon dioxide (PtCO2). The subject of this Ph. D. thesis is to study digital signal processing methods to improve the autonomy of these devices and to allow a personalized follow-up at home of the patient. This requires in particular to study a new generation of autonomous devices based on self-awareness techniques combining optical and fluidic models. Research works will address the building of a numerical model of the device and of its interaction with the human body, the development of the associated simulation software, the study of statistical signal processing methods and compress sensing algorithms. The Ph. D. candidate should be skilled in signal processing, applied mathematics or biomedical engineering.

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