Noninvasive Blood Glucose Monitoring Systems Using Near-Infrared Technology-A Review

被引:54
作者
Hina, Aminah [1 ]
Saadeh, Wala [1 ]
机构
[1] Lahore Univ Management & Sci, Dept Elect Engn, Lahore 54792, Pakistan
关键词
noninvasive glucose monitoring; Photoplethysmography (PPG); near-infrared (NIR); machine learning (ML) methods; IN-VIVO; SPECTROSCOPY; EXTRACTION; BIOSENSOR; ACCURACY; FRUCTOSE; SUCROSE; SENSORS; SIGNAL; TOOL;
D O I
10.3390/s22134855
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
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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页数:22
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