Introduction to Spectroscopy for Noninvasive Glucose Sensing

Shih, Wei‐Chuan; Bechtel, Kate L.; Feld, Michael S.; Arnold, Mark A.; Small, Gary W.

doi:10.1002/9780470567319.ch12

Cited by 4 publications

(5 citation statements)

References 69 publications

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“…NIR absorption features are significantly broader and weaker due to the fact that the underlying processes are quantum mechanically forbidden. However, substantially lower water absorption allows NIR spectroscopy to be performed on samples with high water content, e.g., biological specimen and other in situ measurements, which otherwise restricts the use of IR light. , Due to the shorter wavelength, NIR imaging has better spatial resolution than IR imaging. Since common optical materials such as glass and silica are optically transparent within the NIR range, instrument development is relatively easier than in the IR range.…”

Section: Lspr Shift Due To Refractive Index Changesmentioning

confidence: 99%

“…17 Furthermore, the surface area variation between the 350 and 600 nm diameter NPG disks has been accounted for by considering the differences in their size and monolayer coverage. The EF values are computed for the NIR absorption bands of the ODT molecules using the following equation: (1) where the N o is the number of ODT molecules in methanol solution contributing to the normal absorption, N NPGD is the number of ODT molecules from the monolayer contributing to the enhanced absorption on NPG disks, and I NPGD and I o are the intensities of the absorption band from NGP disks and ODT solution, respectively. EFs of >10 4 are estimated (see Table S1 of Supporting Information) for the C−H combination peaks at ∼2400 nm on both the 600 and 350 nm NPG disks.…”

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confidence: 99%

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Simultaneous Chemical and Refractive Index Sensing in the 1–2.5 μm Near-Infrared Wavelength Range on Nanoporous Gold Disks

et al. 2016

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Near-infrared (NIR) absorption spectroscopy provides molecular and chemical information based on overtones and combination bands of the fundamental vibrational modes in the infrared wavelengths. However, the sensitivity of NIR absorption measurement is limited by the generally weak absorption and the relatively poor detector performance compared to other wavelength ranges. To overcome these barriers, we have developed a novel technique to simultaneously obtain chemical and refractive index sensing in 1-2.5 μm NIR wavelength range on nanoporous gold (NPG) disks, which feature high-density plasmonic hot-spots of localized electric field enhancement. For the first time, surface-enhanced near-infrared absorption (SENIRA) spectroscopy has been demonstrated for high sensitivity chemical detection. With a self-assembled monolayer (SAM) of octadecanethiol (ODT), an enhancement factor (EF) of up to ∼10(4) has been demonstrated for the first C-H combination band at 2400 nm using NPG disk with 600 nm diameter. Together with localized surface plasmon resonance (LSPR) extinction spectroscopy, simultaneous sensing of sample refractive index has been achieved for the first time. The performance of this technique has been evaluated using various hydrocarbon compounds and crude oil samples.

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Section: Lspr Shift Due To Refractive Index Changesmentioning

confidence: 99%

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confidence: 99%

Simultaneous Chemical and Refractive Index Sensing in the 1–2.5 μm Near-Infrared Wavelength Range on Nanoporous Gold Disks

et al. 2016

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“…The concentration of glucose is obtained as the dot-product between this calibration vector and the noninvasive spectrum. [13][14][15] Representative PLS calibration vectors are presented in Figure 3 where these calibration vectors were generated from an analysis of sets of 40 simulated spectra for each quadrant of one male ( Figure 3A) and one female ( Figure 3B) animal. Similarities are noteworthy between these calibration vectors.…”

Section: Effect Of Fiber Relocation On Glucose Concentration Predictionsmentioning

confidence: 99%

Impact of Tissue Heterogeneity on Noninvasive Near-Infrared Glucose Measurements in Interstitial Fluid of Rat Skin

Alexeeva

Arnold

2010

J Diabetes Sci Technol

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Background: Movement of the optical interface used to collect noninvasive near-infrared spectra is known to dramatically increase prediction errors for glucose concentration measurements within the interstitial fluid of living rat skin. Prediction errors increase by more than 2.5-fold when the interface is moved before each noninvasive measurement compared to measurements where the interface position is constant throughout. Chemical heterogeneity of the skin matrix is examined as a possible mechanism for the strong sensitivity to the interface placement during noninvasive measurements conducted from transmission near-infrared absorption spectroscopy. Method: Microspectroscopy was performed over a region of the near-infrared spectrum (4000–5000 cm1) to map the concentrations of water, collagen protein, fat, and keratin protein within the skin tissue matrix through which noninvasive spectra are collected. Maps were created for multiple samples of skin excised from male and female animals. Sets of near-infrared spectra were constructed to simulate noninvasive spectra in accord with the basic tissue composition found from the microspectroscopic maps with added information corresponding to a span of glucose concentrations ranging from 5 to 35 mM and Gaussian-distributed noise. Results: Microspectroscopic maps of rat skin reveal similar patterns of heterogeneity for major chemical components of skin samples excised from both male and female animals. These maps demonstrate concentration domains with dimensions similar to the size of the fiber interface used to collect noninvasive spectra. Partial least squares calibration models generated from sets of simulated spectra demonstrate increases in prediction errors for glucose when the spectral matrix is changed in accord with the degree of chemical heterogeneity displayed in the skin maps. Prediction errors typically increase between 100 and 1000% when comparing errors generated from spectra that represent a single tissue composition versus spectra that represent a varied skin composition in accord with the distribution displayed in the skin maps. Conclusions: The distribution of the major components of skin is not uniform, but establishes domains within the skin matrix that strongly impact prediction errors for the noninvasive spectroscopic measurement of glucose within the interstitial fluid of rat dermis tissue. The observed increase in prediction error (>2.5-fold) determined from actual noninvasive measurements is within the lower range of prediction error increases demonstrated by this simulation study. These findings implicate that chemical heterogeneity within the tissue matrix is a major factor in the sensitivity of the location of the fiber interface used to collect noninvasive spectral data.

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“…2,7,14 Raman spectroscopy provides detailed quantitative information about sample composition, and is thus a promising technique for study of biological systems. [15][16][17][18][19][20][21] Glucose is a convenient analyte to study because its concentration can be conveniently altered and monitored in human volunteers.…”

Section: Experimental Methodsmentioning

confidence: 99%

“…In contrast, implicit multivariate calibration techniques such as principal component regression (PCR) and partial least squares (PLS) allow the construction of a numerical model entirely based on spectroscopic and concentration data. 2 They are powerful because virtually no prior information This is an Open Access article published by World Scienti¯c Publishing Company. It is distributed under the terms of the Creative Commons Attribution 3.0 (CC-BY) License.…”

Section: Introductionmentioning

confidence: 99%

Constrained regularization for noninvasive glucose sensing using Raman spectroscopy

Shih

2015

J. Innov. Opt. Health Sci.

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Multivariate calibration is an important tool for spectroscopic measurement of analyte concentrations. We present a detailed study of a hybrid multivariate calibration technique, constrained regularization (CR), and demonstrate its utility in noninvasive glucose sensing using Raman spectroscopy. Similar to partial least squares (PLS) and principal component regression (PCR), CR builds an implicit model and requires knowledge only of the concentrations of the analyte of interest. Calibration is treated as an inverse problem in which an optimal balance between model complexity and noise rejection is achieved. Prior information is included in the form of a spectroscopic constraint that can be obtained conveniently. When used with an appropriate constraint, CR provides a better calibration model compared to PLS in both numerical and experimental studies.

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Introduction to Spectroscopy for Noninvasive Glucose Sensing

Cited by 4 publications

References 69 publications

Simultaneous Chemical and Refractive Index Sensing in the 1–2.5 μm Near-Infrared Wavelength Range on Nanoporous Gold Disks

Simultaneous Chemical and Refractive Index Sensing in the 1–2.5 μm Near-Infrared Wavelength Range on Nanoporous Gold Disks

Impact of Tissue Heterogeneity on Noninvasive Near-Infrared Glucose Measurements in Interstitial Fluid of Rat Skin

Constrained regularization for noninvasive glucose sensing using Raman spectroscopy

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