Commercial and Scientific Solutions for Blood Glucose Monitoring-A Review

• Published in: Sensors (Basel, Switzerland) Switzerland), 2022-01, Vol.22 (2), p.425
• Main Authors: Xue, Yirui, Thalmayer, Angelika S, Zeising, Samuel, Fischer, Georg, Lübke, Maximilian
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Biosensors; Blood; Blood Glucose; blood glucose monitoring; Blood Glucose Self-Monitoring; Blood sugar; Blood sugar monitoring; Blood vessels; Cardiovascular disease; Cellulose acetate; Clarke error grid; commercial; Diabetes; diabetes mellitus; Diabetes Mellitus - diagnosis; Electromagnetism; Glucose monitoring; Humans; Hyperglycemia; Hypoglycemia; Hypoglycemia - diagnosis; Insulin resistance; machine learning; Measuring instruments; Medical equipment and supplies industry; Medical test kit industry; Methods; microwave; Monitoring; Monitoring, Physiologic; Patient monitoring equipment; Patients; Reproducibility of Results; Review; Sensors; Skin; Temperature dependence; Type 2 diabetes
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22020425

Diabetes is a chronic and, according to the state of the art, an incurable disease. Therefore, to treat diabetes, regular blood glucose monitoring is crucial since it is mandatory to mitigate the risk and incidence of hyperglycemia and hypoglycemia. Nowadays, it is common to use blood glucose meters or continuous glucose monitoring via stinging the skin, which is classified as invasive monitoring. In recent decades, non-invasive monitoring has been regarded as a dominant research field. In this paper, electrochemical and electromagnetic non-invasive blood glucose monitoring approaches will be discussed. Thereby, scientific sensor systems are compared to commercial devices by validating the sensor principle and investigating their performance utilizing the Clarke error grid. Additionally, the opportunities to enhance the overall accuracy and stability of non-invasive glucose sensing and even predict blood glucose development to avoid hyperglycemia and hypoglycemia using post-processing and sensor fusion are presented. Overall, the scientific approaches show a comparable accuracy in the Clarke error grid to that of the commercial ones. However, they are in different stages of development and, therefore, need improvement regarding parameter optimization, temperature dependency, or testing with blood under real conditions. Moreover, the size of scientific sensing solutions must be further reduced for a wearable monitoring system.