Infrared absorption spectroscopy-based non-invasive blood glucose monitoring technology: A comprehensive review

被引：1
作者：
Li, Taixiang [1 ]
Wang, Quangui [2 ]
An, Ying [1 ]
Guo, Lin [1 ]
Ren, Linan [1 ]
Lei, Linghao [1 ]
Chen, Xianlai [1 ]
机构：
[1] Cent South Univ, Big Data Inst, Changsha, Peoples R China
[2] Hunan Longgang Intelligent Technol Co Ltd, Changsha, Peoples R China
来源：
BIOMEDICAL SIGNAL PROCESSING AND CONTROL | 2025年 / 106卷
关键词：
Non-invasive blood glucose monitoring; Infrared absorption spectroscopy; Machine learning; Multi-sensor; Photoplethysmography; Wavelength selection; VARIABLE SELECTION; PHOTOPLETHYSMOGRAPHY; OPTIMIZATION; CALIBRATION; PREDICTION; REGRESSION; CONSENSUS; SYSTEM;
D O I：
10.1016/j.bspc.2025.107750
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Diabetes, characterized by hyperglycemia, is an incurable metabolic disorder with an alarmingly high prevalence rate. Self-monitoring of blood glucose holds exceptional significance in diabetes management. However, traditional invasive blood glucose monitoring devices have imposed inconvenience and discomfort on patients. This has propelled research in non-invasive blood glucose monitoring into the forefront, offering substantial clinical utility. In this survey, we reviewed the major technologies of non-invasive blood glucose monitoring based on absorption spectroscopy, including physical methodologies, signal and data processing techniques, and the progress in commercialization. This review can serve as an introduction to the modeling principles of non-invasive blood glucose monitoring, or as a collection of technical application methods of non-invasive glucose monitoring.
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页数：21
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