ArticleF1000Research2026
Advancing Diabetic Care Through Non-Invasive Glucose Monitoring Using Optical Sensors and IoT Technologies.
Article in F1000Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Diabetic Patients must monitor their Blood Glucose (BG) continually to control their glycemia at least twice a day using a finger prick. Patients visit a laboratory every three months for glycated hemoglobin (HbA1c). According to the World Health Organization (WHO), the constitution of Iraqi diabetes patients is 13.9%. An Internet of Things (IoT) based framework for non-invasive BG monitoring is recently developed. We aim to enhance the Continuous Glucose Monitoring (CGM). Starting with a review of IoT technologies and some of CGM commercial devices recommended by ISO 15197 standard. A questionnaire sheet is distributed to determine how much patients in Iraq knew about their health situation and whether they are interested in using new IoT technologies. Women patients are volunteered to check their BG using both finger prick (FP) and a CGM device for comparing. The suggested method is to connect CGM to a smart device to show alarm messages when needed. The results show how important to introduce patients about new technologies. A CGM and FP results are checked for similarity using statistical package. The findings demonstrated that, significantly at P < 0.05, there were no differences between both methods based on the standard Ambulatory Glucose Profile (AGP) report. This study shows how Iraqi's patients feel when using a CGM and new IoT technologies. CGM output is accurate but appeared every 15 min which may be uncomfortable. A method is suggested to transfer CGM output to a smart device to be controlled by algorithms, where an alarm message is showed every 8 h when BG is normal or a colored alarm will appear. GMI% will be calculated every two weeks using data stored in the cloud to estimate HbA1c level depending on Markov chain. This figures how BG changes in a shorter timeframe, helping in fine-tune diabetes management plans.
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