Enhancing calibration models for non-invasive near-infrared spectroscopical blood glucose determination

Fischbacher, Christoph; Jagemann, Kay-Uwe; Danzer, Klaus; Müller, Ulrich A.; Papenkordt, L; Schuler, Joshua

doi:10.1007/s002160050539

Cited by 73 publications

(36 citation statements)

References 5 publications

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“…Other factors, such as temperature, blood perfusion, tissue compression, blood oxygenation, cutaneous water, and other metabolites or medications that affect tissue blood dynamics are not considered. The wavelengths used in this study (590 -935 nm) do not correspond to any near-infrared glucose absorption bands as did those used in previous studies (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15). Spectral bands in this wavelength range correspond to blood absorption and thus reflect hemodynamic changes in cutaneous tissue.…”

Section: Discussionmentioning

confidence: 87%

“…The wavelengths used were shorter than those reported in other studies (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) and did not correspond to any glucose infrared absorption bands. Probe design allowed measurement of optical properties down to a depth of 2 mm in the skin, where temperature can be controlled and varied (23)(24)(25)(26).…”

Section: Noninvasive (Ni)mentioning

confidence: 87%

“…Most proposed NI methods for glucose determinations are based on monitoring extremely weak nearinfrared glucose absorption spectral features (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15), which overlap with other overtone and combination bands of water, hemoglobin, protein, and fats (1 ). A second approach is to use the effect of glucose on the tissue scattering coefficient (16 -20 ), which is a nonspecific effect that is common to other soluble analytes.…”

Section: Noninvasive (Ni)mentioning

confidence: 99%

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Monitoring Blood Glucose Changes in Cutaneous Tissue by Temperature-modulated Localized Reflectance Measurements

2003

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Background: Most proposed noninvasive methods for glucose measurements do not consider the physiologic response of the body to changes in glucose concentration. Rather than consider the body as an inert matrix for the purpose of glucose measurement, we exploited the possibility that noninvasive measurements of glucose can be approached by investigating their effects on the skin's thermo-optical response. Methods: Glucose concentrations in humans were correlated with temperature-modulated localized reflectance signals at wavelengths between 590 and 935 nm, which do not correspond to any near-infrared glucose absorption wavelengths. Optical signal was collected while skin temperature was modulated between 22 and 38°C over 2 h to generate a periodic set of cutaneous vasoconstricting and vasodilating events, as well as a periodic change in skin light scattering. The method was tested in a series of modified meal tolerance tests involving carbohydrate-rich meals and no-meal or highprotein/no-carbohydrate meals. Results: The optical data correlated with glucose values. Changes in glucose concentrations resulting from a carbohydrate-rich meal were predicted with a model based on a carbohydrate-meal calibration run. For diabetic individuals, glucose concentrations were predicted with a standard error of prediction <1.5 mmol/L and a prediction correlation coefficient 0.73 in 80% of the cases. There were run-to-run differences in predicted glucose concentrations. Non-carbohydrate meals showed a high degree of scatter when predicted by a carbohydrate meal calibration model. Conclusions: Blood glucose concentrations alter thermally modulated optical signals, presumably through physiologic and physical effects. Temperature changes

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Section: Discussionmentioning

confidence: 87%

Section: Noninvasive (Ni)mentioning

confidence: 87%

Section: Noninvasive (Ni)mentioning

confidence: 99%

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Monitoring Blood Glucose Changes in Cutaneous Tissue by Temperature-modulated Localized Reflectance Measurements

2003

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“…The in vivo determination of blood glucose by NIR spectroscopy has recently received great interest. [1][2][3][4][5][6][7][8][9][10][11][12][13] Over the years, several NIR spectral regions have been examined for the determination of glucose, [1][2][3] and several capillary-rich locations in the body have been used to collect in vivo spectra such as tongue, 2 forearm, 2 webbing between the thumb and forefinger, 2 eye, 2 finger 4,5 and oral mucosa. 6 Various NIR systems for noninvasive measurements of blood glucose have been developed.…”

Section: Introductionmentioning

confidence: 99%

“…Heise et al 7,8 presented results through a diffuse reflectance measurement in the 1111 -1835 nm range with an optimized diffuse reflectance accessory. Jagemann et al 9 and Fischbacher et al 10 reported some studies on the NIR spectra recorded with fiber-optic probe.…”

Section: Introductionmentioning

confidence: 99%

Removal of Interference Signals Due to Water from in vivo Near-Infrared (NIR) Spectra of Blood Glucose by Region Orthogonal Signal Correction (ROSC)

Liang

Kasemsumran

et al. 2004

ANAL. SCI.

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A novel chemometric method, region orthogonal signal correction (ROSC), is proposed and applied to pretreat nearinfrared (NIR) spectra of blood glucose measured in vivo. Water is the most serious interference component in such kinds of noninvasive measurements, because it shows very high absorbance in the spectra. In the present study, the spectra of blood glucose in the range of 1212 -1889 nm are used, in which the absorption of water around 1440 nm is very high. ROSC aims at removing the interference signal due to water from the spectra by selecting a set of spectra with a special region of 1404 -1454 nm that mainly contain information about the variation of the interference component, water, and calculating the orthogonal components to the concentrations of glucose that will be removed. The difference between ROSC and orthogonal signal correction (OSC) is that ROSC uses a special region of spectra for the estimation of scores and loading weights of orthogonal components to pretreat the spectra in other regions, while OSC only uses one fixed region of spectra to calculate loadings, scores and weights of OSC components and removes the OSC components in the same region. A clear advantage of ROSC is that it is more interpretable than OSC, because one can select a spectral region to remove the variation of a special component such as water. Another chemometric method, moving window partial least squares (MWPLSR), is also used to select informative regions of glucose from the NIR spectra of blood glucose measured in vivo, leading to improved PLS models. Results of the application of ROSC demonstrate that ROSCpretreated spectra including the whole spectral region of 1212 -1889 nm or an informative region of 1600 -1730 nm selected by MWPLSR provide very good performance of the PLS models. Especially, the later region yields a model with RMSECV of 15.8911 mg/dL for four PLS components. ROSC is a potential chemometric technique in the pretreatment of various spectra.

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Correlation weighted successive projections algorithm as a novel method for variable selection in QSAR studies: investigation of anti‐HIV activity of HEPT derivatives

Kompany‐Zareh

Akhlaghi

2007

Journal of Chemometrics

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Correlation weighted successive projections algorithm (CWSPA), as a modified version of successive projections algorithm (SPA), is proposed for selection of descriptors in the non-linear quantitative structure-activity relationship (QSAR) study of a series of 1-[2-hydroxyethoxy-methyl]-6-(phenylthio)thymine] (HEPT) derivatives, as non-nucloside reverse transcriptase inhibitors (NNRTIs). In the proposed procedure the correlation coefficient of each descriptor with the activities (r g ) was an additional criterion for selection of descriptors. The extent of contribution of r in the selection of variables, m, was also optimized and r 4 g -CWSPA was the selected condition (m ¼ 4). Three layer radial basis function networks (RBFNs) and molecular descriptors derived solely from molecular structure were used to construct the non-linear QSAR models. Utilizing r 4 g -CWSPA a limited number of uncorrelated and informative descriptors were selected. The relative standard error percent in anti-HIV activity predictions for the training set by the application of cross-validation (RSECV%) was 9.77%, and for prediction set (RSEP%) was 8.61% when the selected number of descriptors were 20. The obtained model outperforms those given in the literature in both the fitting and predicting stages. RBFN analysis yielded predicted activities in an acceptable agreement with the experimentally obtained values (cross-validation r ¼ 0.924, prediction r ¼ 0.939). Compared to SPA, r m g -CWSPA resulted in a lower RSECV% and RSEP% values using lower number of selected variables. The results show that considering the correlation of variables to the independent variables increase the performance of selection, as a result, the quality of the set of selected variables. Finally, a simple procedure for selection of variables using r 4 g -CWSPA was proposed in which there was no need to test all possible initial descriptors. The results from the simple procedure were comparable to the procedure in which all of the possible initial descriptors were tested. The proposed method was successfully validated by five different training and test sets.

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Enhancing calibration models for non-invasive near-infrared spectroscopical blood glucose determination

Cited by 73 publications

References 5 publications

Monitoring Blood Glucose Changes in Cutaneous Tissue by Temperature-modulated Localized Reflectance Measurements

Monitoring Blood Glucose Changes in Cutaneous Tissue by Temperature-modulated Localized Reflectance Measurements

Removal of Interference Signals Due to Water from in vivo Near-Infrared (NIR) Spectra of Blood Glucose by Region Orthogonal Signal Correction (ROSC)

Correlation weighted successive projections algorithm as a novel method for variable selection in QSAR studies: investigation of anti‐HIV activity of HEPT derivatives

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