Abstract
Noninvasive blood glucose measurement with near-infrared spectroscopy suitable for home use would allow a more accuracy and frequent determination of glucose level, along with reducing the long-term health care costs of diabetic patients due to no reagents. The fundamental research results of noninvasive blood glucose sensing of our research group are introduced in this paper. They are involving the aspects as followed, the prediction results of the fundamental experiments by PLS calibration method and artificial neural networks respectively; the wavelength selection by genetic algorithm; the quantitative relation among prediction accuracy, instrumental precision and regression algorithms; and the determination of measuring mode according to the measuring wavelength range, and so on. The experiments that done with the samples from simple ones to complex ones have proved the feasibility of noninvasive blood glucose measurement methodology by near-infrared spectroscopy. In addition, the further research subjects of the fundamental problems involving human body measurement are proposed.
| Original language | English |
|---|---|
| Pages (from-to) | 457-464 |
| Number of pages | 8 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 4916 |
| DOIs | |
| State | Published - 2002 |
| Externally published | Yes |
| Event | optics in Health Care and Biomedical Optics: Diagnostics and Treatment - Shanghai, China Duration: 15 Oct 2002 → 18 Oct 2002 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Artificial neural networks
- Blood glucose
- Genetic algorithm
- Instrumental precision
- Measuring mode
- Near-infrared spectroscopy
- Noninvasive measurement
- Prediction accuracy
- Signal-to-noise ratio
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