Authors:
Fernando Tadeo
and
Mustapha Ait Rami
Affiliation:
Universidad de Valladolid, Spain
Keyword(s):
Compartmental models, Observers, Linear Programming, Kinetic models.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Bioinformatics
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
This paper presents a technique to estimate the states of biological systems that cannot be directly measured, by using available measurements of other states that affect them. More precisely, the proposed technique makes it possible to derive, at each moment, the possible range of variation of these unmeasured states. It is based on having a compartmental model of the system (which might include uncertain parameters), and then solving a Linear Programming problem. A practical example, based on the kinetic model of drug distribution through the human body, is provided to show its applicability.