光容积图
计算机科学
生物医学工程
血糖自我监测
血糖监测
近红外光谱
医学
人工智能
连续血糖监测
糖尿病
1型糖尿病
电信
无线
量子力学
物理
内分泌学
作者
Aminah Hina,Wala Saadeh
出处
期刊:Sensors
[MDPI AG]
日期:2022-06-27
卷期号:22 (13): 4855-4855
被引量:49
摘要
The past few decades have seen ongoing development of continuous glucose monitoring (CGM) systems that are noninvasive and accurately measure blood glucose levels. The conventional finger-prick method, though accurate, is not feasible for use multiple times a day, as it is painful and test strips are expensive. Although minimally invasive and noninvasive CGM systems have been introduced into the market, they are expensive and require finger-prick calibrations. As the diabetes trend is high in low- and middle-income countries, a cost-effective and easy-to-use noninvasive glucose monitoring device is the need of the hour. This review paper briefly discusses the noninvasive glucose measuring technologies and their related research work. The technologies discussed are optical, transdermal, and enzymatic. The paper focuses on Near Infrared (NIR) technology and NIR Photoplethysmography (PPG) for blood glucose prediction. Feature extraction from PPG signals and glucose prediction with machine learning methods are discussed. The review concludes with key points and insights for future development of PPG NIR-based blood glucose monitoring systems.
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