A Portable and Low Cost System to Blood Glucose, Cholesterol and Urea Identification
Linked Agent
Queiroz, Alvaro Antonio Alencar, Author
Ramos, Alexandre Carlos Brandão, Author
Country of Publication
Kingdom of Bahrain
Place Published
Sakhir, Bahrain
Publisher
University of Bahrain
Date Issued
2012
Language
English
Description
Abstract :
Over the last century there has been a considerable increase in human longevity and this made a large number of people to reach a critical age for development of several diseases. As a result of this increase in life expectancy health issues related, some examples are hypercholesterolemia, hyperglycemia and increased levels of blood urea. This paper presents a portable and low cost system using Artificial Neural Networks to blood metabolites identification. The system developed is based in amperometric biosensors and is able to perform the identification of glucose, cholesterol and urea concentrations in the blood. The main goals of this system is: the identification of three types of blood metabolites with their concentrations, the low cost of the entire system and the reuse capability of the biosensor.
Keywords: artificial neural networks, chemical and biological sensors, monitoring blood metabolites
Over the last century there has been a considerable increase in human longevity and this made a large number of people to reach a critical age for development of several diseases. As a result of this increase in life expectancy health issues related, some examples are hypercholesterolemia, hyperglycemia and increased levels of blood urea. This paper presents a portable and low cost system using Artificial Neural Networks to blood metabolites identification. The system developed is based in amperometric biosensors and is able to perform the identification of glucose, cholesterol and urea concentrations in the blood. The main goals of this system is: the identification of three types of blood metabolites with their concentrations, the low cost of the entire system and the reuse capability of the biosensor.
Keywords: artificial neural networks, chemical and biological sensors, monitoring blood metabolites
Member of
Identifier
https://digitalrepository.uob.edu.bh/id/b2a3a25c-e10d-4ecd-bcc8-f8d796f8b5ee
https://digitalrepository.uob.edu.bh/id/b2a3a25c-e10d-4ecd-bcc8-f8d796f8b5ee