This study presents an approach for glucose correction in handheld devices by reducing the effects of hematocrit. The hematocrit values are estimated from the transduced current curves which are produced during the chemical reactions of glucose measurement process in the handheld devices. | Journal of Science and Technology 54 (3A) (2016) 91-97 GLUCOSE CORRECTION IN HANDHELD DEVICES BY REDUCING THE EFFECT OF HEMATOCRIT Huynh Trung Hieu1, *, Bui Dinh Tien1, Yonggwan Won2 1 Industrial University of Ho Chi Minh City, 12 Nguyen Van Bao, Go Vap, Ho Chi Minh City, Vietnam 2 Chonnam National University, Gwangju 500-757, Korea * Email: hthieu@ Received: 15 June 2015; Accepted for publication: 27 July 2016 ABSTRACT This study presents an approach for glucose correction in handheld devices by reducing the effects of hematocrit. The hematocrit values are estimated from the transduced current curves which are produced during the chemical reactions of glucose measurement process in the handheld devices. The hematocrit estimation is performed by applying the single-hidden layer feedforward neural network which is trained by the non-iterative learning algorithm. The experimental results show that the proposed approach can improve the accuracy of glucose measurement by using the handheld devices. Keywords: glucose measurement, handheld device, neural network, hematocrit, glucose correction. 1. INTRODUCTION Diabetes mellitus is characterized by the inadequate ability of the pancreas to handle the blood glucose concentration. This is one of the leading diseases worldwide with the long-term complications including hypoglycemia diabetic ketoacidosis, hyperosmolar, retinopathy, cardiovascular, nephropathy (kidneys), and neuropathy (nerves and feet). The current treatment methods for insulin dependent diabetes such as continuous infusion of insulin or subcutaneous insulin injection require frequently evaluating the variation of glucose concentration. The major tools for managing the glucose concentration are the point-of-care (POC) or handheld blood glucose meters. These meters are easy to use and relatively cheap, however they are inaccuracy in various clinical abnormalities. Many studies reported that the hematocrit is one of the most highly affecting factors
