Improvements on noninvasive blood glucose biosensors using wavelets for quick fault detection

Abstract

Noninvasive blood glucose sensors are still under development stage considering that they are far from being suitable for use in anartificial pancreas. The latter has three main parts: the blood glucose sensor, the insulin pump and the controller. However, for the biosensor analyzed here, some common failures such as signal shifts and unreal picks were found. They must be taken into account, for computing the correct insulin dosage for diabetic persons. Hence, a fault detection system based on discrete wavelets transform (DWT) is applied here. The main idea is, when the fault occurs, to do a proper measurement compensation for sending the corrected value to the predictive functional controller (PFC) algorithm. The study is done by reproducing the fault on the blood glucose measurements. They are obtained from a mathematical model of the endocrine system of an adult diabetic patient. This model was approved by the FDA in 2008. Then, the simulation environment includes faulty blood glucose measurements and a fault diagnosis and identification (FDI) system based on DWT. The FDI system gives to the PFC algorithm the correct information to turn it into a fault-tolerant controller (FTC). The main goal is to deliver the correct insulin dosage to the patient.