Noninvasive near-infrared blood glucose monitoring using a calibration model built by a numerical simulation method: Trial application to patients in an intensive care unit

We have applied a new methodology for noninvasive continuous blood glucose monitoring, proposed in our previous paper, to patients in ICU (intensive care unit), where strict controls of blood glucose levels are required. The new methodology can build calibration models essentially from numerical simulation, while the conventional methodology requires pre-experiments such as sugar tolerance tests, which are impossible to perform on ICU patients in most cases. The in vivo experiments in this study consisted of two stages, the first stage conducted on healthy subjects as preliminary experiments, and the second stage on ICU patients. The prediction performance of the first stage was obtained as a correlation coefficient (r) of 0.71 and standard error of prediction (SEP) of 28.7 mg/dL. Of the 323 total data, 71.5% were in the A zone, 28.5% were in the B zone, and none were in the C, D, and E zones for the Clarke error-grid analysis. The prediction performance of the second stage was obtained as an r of 0.97 and SEP of 27.2 mg/dL. Of the 304 total data, 80.3% were in the A zone, 19.7% were in the B zone, and none were in the C, D, and E zones. These prediction results suggest that the new methodology has the potential to realize a noninvasive blood glucose monitoring system using near-infrared spectroscopy (NIRS) in ICUs. Although the total performance of the present monitoring system has not yet reached a satisfactory level as a stand-alone system, it can be developed as a complementary system to the conventional one used in ICUs for routine blood glucose management, which checks the blood glucose levels of patients every few hours.     

In vivo noninvasive measurement of blood glucose by near-infrared diffuse-reflectance spectroscopy

This paper reports in situ noninvasive blood glucose monitoring by use of near-infrared (NIR) diffuse-reflectance spectroscopy. The NIR spectra of the human forearm were measured in vivo by using a pair of source and detector optical fibers separated by a distance of 0.65 mm on the skin surface. This optical geometry enables the selective measurement of dermis tissue spectra due to the skin's optical properties and reduces the interference noise arising from the stratum corneum. Oral glucose intake experiments were performed with six subjects (including a single subject with type I diabetes) whose NIR skin spectra were measured at the forearm. Partial least-squares regression (PLSR) analysis was carried out and calibration equations were obtained with each subject individually. Without exception among the six subjects, the regression coefficient vectors of their calibration models were similar to each other and had a positive peak at around 1600 nm, corresponding to the characteristic absorption peak of glucose. This result indicates that there is every possibility of glucose detection in skin tissue using our measurement system. We also found that there was a good correlation between the optically predicted values and the directly measured values of blood samples with individual subjects. The potential of noninvasive blood glucose monitoring using our methodology was demonstrated by the present study.     

Spectral simulation methodology for calibration transfer of near-infrared spectra

A spectrum simulation method is described for use in the development and transfer of multivariate calibration models from near-infrared spectra. By use of previously measured molar absorptivities and solvent displacement factors, synthetic calibration spectra are computed using only background spectra collected with the spectrometer for which a calibration model is desired. The resulting synthetic calibration set is used with partial least squares regression to form the calibration model. This methodology is demonstrated for use in the analysis of physiological levels of glucose (1-30 mM) in an aqueous matrix containing variable levels of alanine, ascorbate, lactate, urea, and triacetin. Experimentally measured data from two different Fourier transform spectrometers with different noise levels and stabilities are used to evaluate the simulation method. With the more stable instrument (A), well-performing calibration models are obtained, producing a standard error of prediction (SEP) of 0.70 mM. With the less stable instrument (B), the calibration based solely on synthetic spectra is less successful, producing an SEP value of 1.58 mM. For cases in which the synthetic spectra do not describe enough spectral variance, an augmentation protocol is evaluated in which the synthetic calibration spectra are augmented with the spectra of a small number of experimentally measured calibration samples. For instruments A and B, respectively, augmentation with measured spectra of nine samples lowers the SEP values to 0.64 and 0.85 mM.     

Development of robust calibration models using support vector machines for spectroscopic monitoring of blood glucose

Sample-to-sample variability has proven to be a major challenge in achieving calibration transfer in quantitative biological Raman spectroscopy. Multiple morphological and optical parameters, such as tissue absorption and scattering, physiological glucose dynamics and skin heterogeneity, vary significantly in a human population introducing nonanalyte specific features into the calibration model. In this paper, we show that fluctuations of such parameters in human subjects introduce curved (nonlinear) effects in the relationship between the concentrations of the analyte of interest and the mixture Raman spectra. To account for these curved effects, we propose the use of support vector machines (SVM) as a nonlinear regression method over conventional linear regression techniques such as partial least-squares (PLS). Using transcutaneous blood glucose detection as an example, we demonstrate that application of SVM enables a significant improvement (at least 30%) in cross-validation accuracy over PLS when measurements from multiple human volunteers are employed in the calibration set. Furthermore, using physical tissue models with randomized analyte concentrations and varying turbidities, we show that the fluctuations in turbidity alone causes curved effects which can only be adequately modeled using nonlinear regression techniques. The enhanced levels of accuracy obtained with the SVM based calibration models opens up avenues for prospective prediction in humans and thus for clinical translation of the technology.     

Tunable laser diode system for noninvasive blood glucose measurements

Optical sensing of glucose would allow more frequent monitoring and tighter glucose control for people with diabetes. The key to a successful optical noninvasive measurement of glucose is the collection of an optical spectrum with a very high signal-to-noise ratio in a spectral region with significant glucose absorption. Unfortunately, the optical throughput of skin is low due to absorption and scattering. To overcome these difficulties, we have developed a high-brightness tunable laser system for measurements in the 2.0-2.5 microm wavelength range. The system is based on a 2.3 microm wavelength, strained quantum-well laser diode incorporating GaInAsSb wells and AlGaAsSb barrier and cladding layers. Wavelength control is provided by coupling the laser diode to an external cavity that includes an acousto-optic tunable filter. Tuning ranges of greater than 110 nm have been obtained. Because the tunable filter has no moving parts, scans can be completed very quickly, typically in less than 10 ms. We describe the performance of the present laser system and avenues for extending the tuning range beyond 400 nm.     

Optoacoustic technique for noninvasive monitoring of blood oxygenation: a feasibility study

Replacement of invasive monitoring of cerebral venous oxygenation with noninvasive techniques offers great promise in the management of life-threatening neurologic illnesses including traumatic brain injury. We developed and built an optoacoustic system to noninvasively monitor cerebral venous oxygenation; the system includes a nanosecond Nd:YAG laser and a specially designed optoacoustic probe. We tested the system in vitro in sheep blood with experimentally varied oxygenation. Our results demonstrated that (1) the amplitude and temporal profile of the optoacoustic waves increase with blood oxygenation in the range from 24% to 92%, (2) optoacoustic signals can be detected despite optical and acoustic attenuation by thick bone, and (3) the system is capable of real-time and continuous measurements. These results suggest that the optoacoustic technique is technically feasible for continuous, noninvasive monitoring of cerebral venous oxygenation.     

Optical noninvasive monitoring of skin blood pulsations

Time-resolved detection and analysis of skin backscattered optical signals (remission photoplethysmography or PPG) provide rich information on skin blood volume pulsations and can serve for reliable cardiovascular assessment. Single- and multiple-channel PPG concepts are discussed. Simultaneous data flow from several locations on the human body allows us to study heartbeat pulse-wave propagation in real time and to evaluate vascular resistance. Portable single-, dual-, and four-channel PPG monitoring devices with special software have been designed for real-time data acquisition and processing. The prototype devices have been clinically studied, and their potential for monitoring heart arrhythmias, drug-efficiency tests, steady-state cardiovascular assessment, body fitness control, and express diagnostics of the arterial occlusions has been confirmed.     

Multivariate calibration standardization across instruments for the determination of glucose by Fourier transform near-infrared spectrometry

The transfer of multivariate calibration models is investigated between a primary (A) and two secondary Fourier transform near-infrared (near-IR) spectrometers (B, C). The application studied in this work is the use of bands in the near-IR combination region of 5000-4000 cm(-)(1) to determine physiological levels of glucose in a buffered aqueous matrix containing varying levels of alanine, ascorbate, lactate, triacetin, and urea. The three spectrometers are used to measure 80 samples produced through a randomized experimental design that minimizes correlations between the component concentrations and between the concentrations of glucose and water. Direct standardization (DS), piecewise direct standardization (PDS), and guided model reoptimization (GMR) are evaluated for use in transferring partial least-squares calibration models developed with the spectra of 64 samples from the primary instrument to the prediction of glucose concentrations in 16 prediction samples measured with each secondary spectrometer. The three algorithms are evaluated as a function of the number of standardization samples used in transferring the calibration models. Performance criteria for judging the success of the calibration transfer are established as the standard error of prediction (SEP) for internal calibration models built with the spectra of the 64 calibration samples collected with each secondary spectrometer. These SEP values are 1.51 and 1.14 mM for spectrometers B and C, respectively. When calibration standardization is applied, the GMR algorithm is observed to outperform DS and PDS. With spectrometer C, the calibration transfer is highly successful, producing an SEP value of 1.07 mM. However, an SEP of 2.96 mM indicates unsuccessful calibration standardization with spectrometer B. This failure is attributed to differences in the variance structure of the spectra collected with spectrometers A and B. Diagnostic procedures are presented for use with the GMR algorithm that forecasts the successful calibration transfer with spectrometer C and the unsatisfactory results with spectrometer B.     

Practical calibration correction method for the maintenance of an on-line near-infrared monitoring system for molten polymers

The present study has investigated a practical calibration correction method for an on-line monitoring system for molten polymers using a near-infrared (NIR) spectrometer. A partial least squares (PLS) calibration model for the ethylene (C2) content in melt polypropylene (PP) was developed for the investigation of changes in the performance of the on-line system before and after maintenance necessitated by the relocation. The predicted values for the C2 content from the spectra measured after maintenance by using the calibration model developed from the spectra collected before maintenance showed that there were some differences between the spectra obtained by the NIR spectrometer system before and after maintenance. The loadings from factor analysis suggested that the main cause for the differences in the system performance before and after maintenance was wavenumber shifts in the NIR spectra of PP in the melt state. Six popular standardization or calibration transfer methods (direct standardization (DS), piecewise direct standardization (PDS), additive correction (AD), multiplicative correction (MP), slope and bias (SB), and difference spectrum with interpolation (DSI)) were evaluated for the calibration correction of the on-line NIR monitoring system. However, the results of the evaluation showed that these standardization methods need more than two samples to obtain the high accuracy for the nonlinearity contained in the spectra set. From the standpoint of practical calibration in a real plant, the acceptable number of samples for the calibration is one or two. Moreover, recalibration using transferred spectra is not preferable because of the traceability for a calibration model. As a practical solution for a calibration correction in a real plant, a method considering wavenumber shift and path-length correction has been proposed in this study. The predicted results for the C2 content in the melt-state PP from the spectra measured after maintenance by using the proposed method have shown that the proposed method is useful for calibration correction in a real plant in spite of using only one sample.     

In vitro studies toward noninvasive glucose monitoring with optical coherence tomography

We use optical coherence tomography (OCT) to measure glucose-induced changes in Intralipid and in mouse skin samples in vitro. Mouse skin samples are cultured in a CO2 incubator before measurements are made with different amounts of added glucose concentrations. The results show that the glucose-induced changes in the OCT slope value vary between 20% and 52%/30 mM glucose in different mouse skin samples. This change is much larger than the change in 2% Intralipid (2.1%/30 mM) and in 5% Intralipid (0.86%/30 mM). Hence the results show that OCT has potential to monitor glucose-induced changes in tissues in vitro.     

温度对果糖含量近红外光谱检测模型传递的影响

以果糖溶液为研究对象,采用斜率/截距(S/B)算法,通过不同温度的果糖含量检测模型在两台不同厂家的傅里叶变换近红外光谱仪间的传递,讨论了样品温度变化对模型传递的影响.主、从仪器直接建模时,预测集的均方根偏差(RMSEP)均随温度升高呈增大的趋势,但整体变化不显著.直接预测时,预测集的RMSEP均大于0.86,效果不理想;采用S/B算法传递后,预测结果得到改善,主、从仪器相同温度光谱间的传递结果优于不同温度光谱间的传递,15℃、22℃和28℃时相同温度光谱间传递后的RMSEP分别为0.317、0.389和0.416,差异显著.实验结果表明,进行模型传递时,样品温度变化会对模型传递产生较大影响;保证样品温度一致下,选择合适温度有利于取得最佳传递效果.     

Design of a mechanical-tunable filter spectrometer for noninvasive glucose measurement

The development of an accurate and reliable noninvasive near-infrared (NIR) glucose sensor hinges on the success in addressing the sensitivity and the specificity problems associated with the weak glucose signals and the overlapping NIR spectra. Spectroscopic hardware parameters most relevant to noninvasive blood glucose measurement are discussed, which include the optical throughput, integration time, spectral range, and the spectral resolution. We propose a unique spectroscopic system using a continuously rotating interference filter, which produces a signal-to-noise ratio of the order of 10(5) and is estimated to be the minimum required for successful in vivo glucose sensing. Using a classical least-squares algorithm and a spectral range between 2180 and 2312 nm, we extracted clinically relevant glucose concentrations in multicomponent solutions containing bovine serum albumin, triacetin, lactate, and urea.     

Comparison of combination and first overtone spectral regions for near-infrared calibration models for glucose and other biomolecules in aqueous solutions

Partial least squares calibration models are compared for the measurement of glucose, lactate, urea, ascorbate, triacetin, and alanine in aqueous solutions from single-beam spectra collected over the first overtone (6500-5500 cm(-1)) and the combination (5000-4000 cm(-1)) regions of the near-infrared spectrum. Spectra are collected under two sets of conditions with one designed for combination spectra and the other designed for first overtone spectra. As part of the optimization of conditions, an exponential function is presented that accurately characterizes the strong dependency between spectral quality and sample thickness. Sample thickness set for the first overtone and combination spectra are 7.5 and 1.5 mm, respectively. Independent calibration models are established for each solute from both combination and first overtone spectra. Direct comparison reveals superior performance by models generated from combination spectra, particularly for glucose and urea. Standard error of prediction (SEP) values are 1.12 and 0.45 mM for glucose models generated from first overtone and combination spectra, respectively. SEP values for urea are 7.33 and 0.10 mM for first overtone and combination spectra, respectively. Such high SEP values for urea with first overtone spectra correspond to an inability to quantify urea from these spectra because of a lack urea-specific molecular absorption features in this spectral region. Net analyte signal (NAS) is used to quantify the degree of selectivity provided within the first overtone and combination spectral regions. The superior selectivity of combination spectra is confirmed by comparing the length of the NAS vectors for each matrix component.     

Multivariate sensitivity for the interpretation of the effect of spectral pretreatment methods on near-infrared calibration model predictions

Predictions obtained from a multivariate calibration model are sensitive to variations in the spectra such as baseline shifts, multiplicative effects, etc. Many spectral pretreatment methods have been developed to reduce these distortions, and the best method is usually the one that minimizes the prediction error for an independent test set. This paper shows how multivariate sensitivity can be used to interpret spectral pretreatment results. Understanding why a particular pretreatment method gives good or bad results is important for ruling out chance effects in the conventional process of "trial and error", thus obtaining more confidence in the finally selected model. The principles are exemplified using the transmission near-infrared spectroscopic prediction of oxygenates in ampules of the standard reference material gasoline. The pretreatment methods compared are the multiplicative signal correction, first-derivative method, and second-derivative method. It is shown that for this application the first- and second-derivative methods are successful in removing the background. However, differentiating the spectra substantially reduces multivariate net analyte signal (in the worst case by a factor of 21). Consequently, a significantly smaller multivariate sensitivity is obtained which leads to increased spectral error propagation resulting in a larger uncertainty in the regression vector estimate and larger prediction errors. Differentiating spectra also increases the spectral noise (each time by a factor 2(1/2)) but this effect, which is well-known, is of minor importance for the current application.     

In vivo near-infrared spectroscopy of rat skin tissue with varying blood glucose levels

We have performed in vivo measurements of near-infrared rat skin absorption in the 4000-5000-cm(-1) spectral range (2.0-2.5-microm wavelength) during a glucose clamp experiment in order to identify the presence of glucose-specific spectral information. Spectra were collected during an initial 3-h period where the animal's blood glucose concentration was held at its normal value. The blood glucose level was then increased above 30 mM by venous infusion of glucose and held for 2 h, after which it was allowed to return to normal. Spectra were recorded continuously during the procedure and are analyzed to identify spectral changes associated with changes in glucose concentration. Because the change in absorbance due to an increase in glucose concentration is small compared to changes due to other variations (e.g., the thickness of the skin sample), a simple subtraction of absorbance spectra from the hyperglycemic and euglycemic phases is not instructive. Instead, a set of principal components is established from the euglycemic period where the glucose concentration is constant. We then examine the change in absorbance during the hyperglycemic period that is orthogonal to these principal components. We find that there are significant similarities between these orthogonal variations and the net analyte signal of glucose, which suggests that glucose spectral information is present. The analysis described here provides a procedure by which the analytical significance of a multivariate calibration can be evaluated.     

Ultrasound-triggered noninvasive regulation of blood glucose levels using microgels integrated with insulin nanocapsules

Diabetes is a serious public health problem affecting 422 million people worldwide.Traditional diabetes management often requires multiple daily insulin injections,associated with pain and inadequate glycemia control.Herein,we have developed an ultrasound-triggered insulin delivery system capable of pulsatile insulin release that can provide both long-term sustained and fast on-demand responses.In this system,insulin-loaded poly(lactic-co-glycolic acid) (PLGA) nanocapsules are encapsulated within chitosan microgels.The encapsulated insulin in nanocapsules can passively diffuse from the nanoparticle but remain restricted within the microgel.Upon ultrasound treatment,the stored insulin in microgels can be rapidly released to regulate blood glucose levels.In a chemically-induced type 1 diabetic mouse model,we demonstrated that this system,when activated by 30 s ultrasound administration,could effectively achieve glycemic control for up to one week in a noninvasive,localized,and pulsatile manner.     

A methodology for monitoring system performance

Monitoring and improving manufacturing processes involves identifying, investigating and eliminating problems responsible for inefficiencies in production operations. While statistical process control tools, such as control charts, are available for process monitoring at the operational level, methods for evaluating system performance from more strategic and tactical levels are limited. The traditional control charts that monitor a single process parameter at a time may not be appropriate in situations where interrelationships among various system measures exist. Although multivariate process control techniques allow for simultaneous monitoring of several process parameters, they require assumptions of independence and multivariate normality of data. In addition, their application has mostly been at an operational level. In order to assist managers in monitoring and improving manufacturing system performance, this paper proposes an individual control chart that monitors an integrated performance index generated from a non-parametric method, which effectively considers multiple performance measures and the relationships between them. The primary advantages of this method are that a single integrated measure can be monitored, does not require assumptions of independence and multivariate normality of data, and allows for the integration of decision-maker's input when the system measures that are monitored have unequal importance.     

Low-cost approaches to robust temperature compensation in near-infrared calibration and prediction situations

The traditional way of handling temperature shifts and other perturbations in calibration situations is to incorporate the non-relevant spectral variation in the calibration set by measuring the samples at various conditions. The present paper proposes two low-cost approaches based on simulation and prior knowledge about the perturbations, and these are compared to traditional methods. The first approach is based on augmentation of the calibration matrix through adding simulated noise on the spectra. The second approach is a correction method that removes the non-relevant variation from new spectra. Neither method demands exact knowledge of the perturbation levels. Using the augmentation method it was found that a few, in this case four, selected samples run under different conditions gave approximately the same robustness as running all the calibration samples under different conditions. For the carbohydrate data set, all robustification methods investigated worked well, including the use of pure water spectra for temperature compensation. For the more complex meat data set, only the augmentation method gave comparable results to the full global model.     

Moisture sorption as a potential condition marker for historic silks: noninvasive determination by near-infrared spectroscopy

Given their ephemeral nature, the preservation of historic silks can be problematic. Rapid, on-site condition monitoring would offer significant benefits to conservators and museum curators concerned with continued access to collections. In this paper, near-infrared spectroscopy (NIR) is investigated as a noninvasive approach to the characterization of silk fabrics and particularly for determining the moisture content of silks as a potential age-related marker. Bands within the NIR spectrum of silk are assigned to contributions from water and the silk fibroin polymer. The water bands may be deconvolved to show separate contributions from bound and structural water. When silk is exposed to deuterium oxide, the water OH NIR bands are rapidly lost. The accompanying changes in the amide-related NIR absorptions reflect differential accessibility of regions within the semi-crystalline fibroin aggregate. NIR spectra were recorded while silk was maintained at a range of relative humidity; complementary gravimetry provided absolute reference data for moisture sorption. A single spectral parameter, the intensity of the water combination band, is sufficient to indicate the relative moisture content of silk and allows distinction of unaged and heat, light, and humidity aged silks. The results confirm that NIR has significant potential for on-site studies at collections in support of the preservation and access of our silk heritage.