GLUCOSE CORRECTION IN HANDHELD DEVICES BY REDUCING THE EFFECT OF HEMATOCRIT
Keywords:glucose measurement, handheld device, neural network, hematocrit, glucose correction.
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.
Authors who publish with Vietnam Journal of Science and Technology agree with the following terms:
- The manuscript is not under consideration for publication elsewhere. When a manuscript is accepted for publication, the author agrees to automatic transfer of the copyright to the editorial office.
- The manuscript should not be published elsewhere in any language without the consent of the copyright holders. Authors have the right to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of their work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are encouraged to post their work online (e.g., in institutional repositories or on their websites) prior to or during the submission process, as it can lead to productive exchanges or/and greater number of citation to the to-be-published work (See The Effect of Open Access).