Virtual sensor for diabetes meter in u-health service

Abstract

The existing home glucose meters have enabled patients to conduct the self-management of diabetes mellitus by displaying their blood glucose value. However, obtaining a more accurate risk level of diabetes mellitus requires consideration not only of the patient’s blood pressure and obesity, but also their first-degree relatives with diabetes. Therefore, in this study, we designed and suggested an intelligent sensor algorithm in order to analyze the risk level of diabetes for IoT-based u-health services. This algorithm is expected to enhance the effectiveness of the patient’s self-management provided that it functions effectively in a virtual sensor for diabetes. Finally, based on the findings of the experiment, its effectiveness was confirmed in the proposed model. © 2014 SERSC.