Least squares minimization to estimate the transport of alcohol in the human body
Abstract
Experimental measurements of transdermal vapor alcohol concentration are used to estimate alcohol concentration in the body using an inverse problem approach. First we propose a model for the transport of alcohol from blood compartments to the skin surface and use the transdermal measurements to estimate the signal obtained by a breathalyzer which is the standard for blood alcohol concentration. Later we couple our skin model to a body model of the human body. The human body is divided in several compartments to facilitate the description of the transport of alcohol in the human body from ingestion to elimination. The adjoint method is used for the computation of the least squares functional gradient. Parameters of the model are estimated using real breathalyzer and a transdermal alcohol skin device data applied to individuals in a hospital. The parameter values obtained are used to predict the evolution of alcohol concentration for patients in the field. Kalman filtering techniques can be used to correct predictions in real time.
The text for this item is currently unavailable.