Near-infrared Spectroscopy Instrument Research Articles

Near-Infrared Sensors for Onsite and Noninvasive Quantification of Macronutrients in Breast Milk.

Breast milk is an optimal food that covers all the nutritional needs of the newborn. It is a dynamic fluid whose composition varies with lactation period. The neonatal units of hospitals have human milk banks, a service that analyzes, stores, and distributes donated human milk. This milk is used to feed premature infants (born before 32 weeks of gestation or weighing less than 1500 g) whose mothers, for some reason, cannot feed them with their own milk. Here, we aimed to develop near-infrared spectroscopy (NIRS) measures for the analysis of breast milk. For this purpose, we used a portable NIRS instrument scanning in the range of 1396–2396 nm to collect the spectra of milk samples. Then, different chemometrics were calculated to develop 18 calibration models with and without using derivatives and the standard normal variate. Once the calibration models were developed, the best treatments were selected according to the correlation coefficients (r2) and prediction errors (SECVs). The best results for the assayed macronutrients were obtained when no pre-treatment was applied to the NIR spectra of fat (r2 = 0.841, SECV = 0.51), raw protein (r2 = 0.512, SECV = 0.21), and carbohydrates (r2 = 0.741, SECV = 1.35). SNV plus the first derivative was applied to obtain satisfactory results for energy (r2 = 0.830, SECV = 9.60) quantification. The interpretation of the obtained results showed the richness of the NIRS spectra; moreover, the presence of specific bands for fat provided excellent statistics in quantitative models. These results demonstrated the ability of portable NIRS sensors in a methodology developed for the quality control of macronutrients in breast milk.

Prediction of the intramuscular fat and protein content of freeze‐dried ground meat from cattle and sheep using near‐infrared spectroscopy (NIRS)

SummaryThis study assessed the ability of near‐infrared spectroscopy to predict intramuscular fat (IMF) and protein content of freeze‐dried ground beef and sheep meat determined using the modified Soxhlet extraction and Dumas combustion, and ascertain if robust calibration models could be developed for both assays using the combined spectral data from both species. Samples were sourced from sheep and cattle slaughtered for a variety of experiments, which covered a range in age, diet fed and carcase cut. All samples were scanned using a benchtop NIRS instrument to develop calibration models, a subset of which was used for later validation. Intramuscular fat and protein content of samples ranged from 5.1 to 32.8 and 63.4 to 89.8, respectively, with combined species of the R2 values of 98.4 and 96.5 (RMSE 0.74 and 0.76) for IMF and protein respectively. Additionally, animal age and carcase cut were found to have no significant impact on the precision of prediction models. Results from our study showed that individual species as well as combined calibration models can be successfully developed for predicting IMF and protein content of freeze‐dried ground beef and sheep meat.

Model Development of Non-Destructive Coffee Beans Moisture Content Determination Using Modified Near Infrared Spectroscopy Instrument

A method of non-destructively moisture content measurement of coffee beans is using near infrared spectroscopy (NIRS) which in general can be applied to determine chemical content of various organic materials. However, the commercial NIR instrument can not measure many samples in a single time, consequently the faster measurement can not be realized. The purposes of this research was to study the performance of modified NIR instrument prototype for measuring the moisture content of Java Preanger coffee beans. Performance study of modified NIR instrument was carried out on 50 coffee bean samples for determination of sample moisture content. The reflectance spectra of samples were measured bymodified NIRS instrument and then water content of samples was determined by oven method. The spectra data and water content were calibrated by multiple linier regression method to find the best calibration model. The result of this research show that number of wavelengths chosen to predict the moisture contentof Java Preanger coffee bean accurately is 17 wavelengths. The correlation coefficient (R) moisture content based on NIRS instrument and oven method was 0.902, this suggest that the model is able to explain 90.2% the diversity of existing data. The value of standard error calibration (SEC) and standard error prediction (SEP)was almost zero meaning that the error of prediction is low. This study also reveal that the value of residual predictive deviation (RPD) is 2.32, which means the prediction model for determination of Java Preanger coffee beans moisture content is good enough.

Comparison of functional activation responses from the auditory cortex derived using multi-distance frequency domain and continuous wave near-infrared spectroscopy.

.Significance: Quantitative measurements of cerebral hemodynamic changes due to functional activation are widely accomplished with commercial continuous wave (CW-NIRS) instruments despite the availability of the more rigorous multi-distance frequency domain (FD-NIRS) approach. A direct comparison of the two approaches to functional near-infrared spectroscopy can help in the interpretation of optical data and guide implementations of diffuse optical instruments for measuring functional activation.Aim: We explore the differences between CW-NIRS and multi-distance FD-NIRS by comparing measurements of functional activation in the human auditory cortex.Approach: Functional activation of the human auditory cortex was measured using a commercial frequency domain near-infrared spectroscopy instrument for 70 dB sound pressure level broadband noise and pure tone (1000 Hz) stimuli. Changes in tissue oxygenation were calculated using the modified Beer–Lambert law (CW-NIRS approach) and the photon diffusion equation (FD-NIRS approach).Results: Changes in oxygenated hemoglobin measured with the multi-distance FD-NIRS approach were about twice as large as those measured with the CW-NIRS approach. A finite-element simulation of the functional activation problem was performed to demonstrate that tissue oxygenation changes measured with the CW-NIRS approach is more accurate than that with multi-distance FD-NIRS.Conclusions: Multi-distance FD-NIRS approaches tend to overestimate functional activation effects, in part due to partial volume effects.

DevfOLD: a toolbox for designing age-specific fNIRS channel placement.

.Significance: Near-infrared spectroscopy (NIRS) is a noninvasive technique that uses scalp-placed sensors to measure cerebral hemoglobin concentration. Commercial NIRS instruments do not allow for whole-head coverage and do not intrinsically indicate which brain areas generate the NIRS signal. Hence, the challenge is to design source–detector channel arrangement that maximizes sensitivity to a given brain region of interest (ROI). Existing methods for optimizing channel placement design have been developed using adult head models. Thus, they have limited utility for developmental research.Aim: We aim to build an application from an existing toolbox (fOLD) that guides NIRS channel configuration based on age group, stereotaxic atlas, and ROI (devfOLD).Approach: The devfOLD provides NIRS channel-to-ROI specificity computed using photon propagation simulation with realistic head models from infant, child, and adult age groups.Results: Cortical locations and user-specified specificity cut-off values influence the between-age consistency and differences in the ROI-to-channel correspondence among the example infant and adult age groups.Conclusions: The study highlights the importance of incorporating age-specific head models for optimizing NIRS channel configurations. The devfOLD toolbox is publicly shared and compatible with multiple operating systems.

The SMRI-NIRS technology: development, validation and benefit

The Sugar Milling Research Institute NPC (SMRI) has developed a simple to use near-infrared spectroscopy (NIRS) transmission-based analysis method as an alternative to conventional methods for analysis of sugarcane factory stream samples. The technology provides rapid, simultaneous analysis of refractometric dry substance (rds), polarimetric sugar, sucrose, glucose, fructose, conductivity ash contents as well as colour and pH for all streams and additionally, dry solids for final molasses and eliminates the need for sample clarification chemicals. The analyte prediction equations were developed using conventional results of samples from 14 South African factories, analysed at SMRI using SANAS/ISO17025 accredited test methods, and NIRS scans of the same samples using up to 16 different NIRS instruments. The NIRS analyte prediction equations were validated against more than 1,500 independent factory samples that had been analysed by conventional methods of analysis, including samples from factories outside South Africa. The reproducibility of the NIRS results were equivalent to existing conventional analysis reproducibility values (juice and final molasses) and previously undocumented values determined for this study for conventional raw house analysis methods. Correlation coefficients of greater than 0.97 were recorded for all major analytes and greater than 0.9 for minor analytes when predicted results were compared against conventional results. A maintenance protocol was also developed to ensure that the prediction equations remain robust and can account for sample matrix variations that can occur from season to season. The SMRI-NIRS technology was installed at all 14 South African factories and found to be robust and give equivalent results to conventional methods of analysis.

Assessment of the Analytical Performance of Three Near-Infrared Spectroscopy Instruments (Benchtop, Handheld and Portable) through the Investigation of Coriander Seed Authenticity.

The performance of three near-infrared spectroscopy (NIRS) instruments was compared through the investigation of coriander seed authenticity. The Thermo Fisher iS50 NIRS benchtop instrument, the portable Ocean Insights Flame-NIR and the Consumer Physics handheld SCiO device were assessed in conjunction with chemometric modelling in order to determine their predictive capabilities and use as quantitative tools through regression analysis. Two hundred authentic coriander seed samples and ninety adulterated samples were analysed on each device. Prediction models were developed and validated using SIMCA 15 chemometric software. All instruments correctly predicted 100% of the adulterated samples. The best models resulted in correct predictions of 100%, 98.5% and 95.6% for authentic coriander samples using spectra from the iS50, Flame-NIR and SCiO, respectively. The development of regression models highlighted the limitations of the Flame-NIR and SCiO for quantitative analysis, compared to the iS50. However, the results indicate their use as screening tools for on-site analysis of food, at various stages of the food supply chain.

The comprehensive sourcebook for modern NIR spectroscopy: A commentary on “Near-Infrared Spectroscopy Theory, Spectral Analysis, Instrumentation, and Applications”

The instrumentation, methods and applications of near-infrared spectroscopy has advanced remarkably in the last decade, in which near-infrared spectroscopy has successfully progressed at multiple directions and faced new challenges. Thus, gaps inevitably appeared in the coverage provided by renowned and handy cornerstone textbooks focused on near-infrared spectroscopy that were published in the past. A demand grew in near-infrared spectroscopy community for a new state-of-the-art textbook. With aim to satisfy such need, a go-to-book for background theory, applications and tutorial “Near-Infrared Spectroscopy Theory, Spectral Analysis, Instrumentation, and Applications” was prepared. That full-scale project, edited by Yukihiro Ozaki, Christian Huck, Satoru Tsuchikawa and Søren B. Engelsen, comprises of 23 chapters contributed by scholars and practitioners pushing the frontier of near-infrared spectroscopy. The chapters scope on newly opened pathways, major breakthroughs in basic science and applications as well as revisit several other topics. The sourcebook is intended for a wide range of readers from graduate students to scientists and engineers in both academia and industry. In this article, we sketch the main features of the newly released sourcebook with aim to help the community members in deciding whether this book should find its place in their library.

Near-infrared spectroscopy (NIRS) as an integrated approach for rapid classification and bioactive quality evaluation of intact Feronia limoni

Feronia limoni (Wood-apple) is one of the most researched plants containing bioactive compounds that have biological activity. So far, research on chemical compounds and fruit activity of F. limoni is often carried out using laboratory analysis, such as chromatographic analysis. This study aimed to assess the ability of NIRS to predict organic compounds contained in F. limoni based on its spectrum. Intact F. limoni samples were obtained from five different geographical origins in Aceh Province. Spectra data in form of absorbance spectrum were acquired using a portable sensing device NIRS instrument PSD FTNIRS i16 in wavenumbers 4000-10000 cm-1 or in the wavelength range from 1000 to 2500 nm with resolution windows of 0.02 nm and optical gain 4x. The results showed that NIRS was able to classify F. limoni samples based on geographical origins with the maximum explained variance of two PCs is 93%. Moreover, the respective wavelength related to this classification is 1090, 1270,1390, 1459, 1602,1713, 1912, and 2211 nm which corresponds to C-H, O-H, C-H-O, N-H stretching. It is related to acids, carbohydrates, and the fibre content of F. limoni samples from bent and stretched along the near-infrared region.

Maximizing Processing Value with Selective Handling Strategies: An Analysis of Soybeans Received at Iowa Elevators

Highlights Levels of protein and oil influence the marketability of soybeans Geographic differences in soybeans have economic implications for grain elevators Random errors in the receiving and analysis process mask these differences For soybeans to be marketed on protein and oil levels, errors in handling and analysis must be addressed Abstract . A better ability to understand and use geographic variations in protein and oil is one way to maximize the value potential of soybeans for handlers and processors. An Iowa cooperative had been sourcing soybeans for processing from nearby elevator locations and wanted to know whether this strategy was maximizing the net processing value of the soybeans. Random and systematic errors from testing and measurement instruments also impact marketing decisions and were investigated as part of this project. During the Fall 2018 soybean harvest, soybean samples were collected from 32 country elevator locations belonging to one Iowa-based cooperative which has its own soybean processing plant. Samples were analyzed using near-infrared spectroscopy (NIR), and protein and oil content data were entered into an Estimated Processing Value (EPV) model to determine value differences of soybeans among elevator locations. Results showed substantial variability among locations that represented a $0.23/bushel EPV spread. No significant variation was found in soybean quality over the harvest season, suggesting that marketing decisions can be made at the beginning of the season. To determine the incidence of random errors, a simulated Excel-based model was used with three test cases. The introduction of random error lowered value gaps between locations, which made the discrimination of high-value locations from average or low-value locations difficult. Although protein and oil measurement with the NIR instrument was feasible even on busy harvest season days, the validity of marketing decisions using these data depended highly on the error involved in sample analysis. Future studies should identify specific sources of error and attempt to eliminate them. Specifically, one of the largest sources of error in a commodity-based market system is in the measuring units. The ability to isolate and quantify measurement error will improve the capability of the commodity-based soybean market system to focus trade decisions on end use traits, maximizing soybean value and providing incentive for improvement. Keywords: Error analysis, Grain elevators, Selective handling, Soybean processing, Soybean value.

Effects of Sevoflurane and Propofol Anesthesia on Cerebral Oxygenation in Patients Undergoing Carotid Endarterectomy.

To compare the effects of sevoflurane and propofol anesthesia on perioperative cerebral oxygenation in patients undergoing carotid endarterectomy (CEA) under general anesthesia by using near-infrared spectroscopy (NIRS) monitoring. Institutional approval was obtained, and the perioperative data of 33 patients undergoing CEA were retrospectively evaluated. The study groups were organized according to the anesthesia drugs used for maintenance: sevoflurane (n=17) and propofol (n=16). The regional cerebral oxygen saturation (rScO < sub > 2 < /sub > ) of the ipsilateral and contralateral hemispheres was monitored continuously using a NIRS instrument and analyzed at specific time points starting from induction to the 12th hour postoperation. The data were analyzed using the appropriate tests, and a p value of < 0.05 was considered significant. Compared with those of groups with non-clamped hemispheres, the rScO < sub > 2 < /sub > values of the sevoflurane and propofol groups decreased significantly during clamping (p < 0.05) and increased to above-preoperative values after declamping (p < 0.05). When the sevoflurane and propofol groups were compared, a significant decrease in rScO < sub > 2 < /sub > was noted during extubation in the sevoflurane group (p < 0.05). In the propofol group, female patients had significantly lower rScO < sub > 2 < /sub > values compared with male patients during clamping of the carotid artery (p < 0.05). None of the observed decreases was greater than 20%, which is considered an indication for shunting. Our NIRS monitoring results indicate that sevoflurane or propofol anesthesia does not generally cause significant differences in cerebral oxygenation during and after cross-clamping in patients undergoing CEA. The finding of sex-related differences in cerebral oxygenation in patients receiving propofol and decreased oxygenation during extubation in patients receiving sevoflurane warrants further studies.

基于DMD的小型近红外光谱仪原理及优化分析

The DMD small near-infrared spectroscopy instrument is widely used in chemical composition analysis and quality inspection for its advantages of fast detection speed, high sensitivity, no damage detection, and miniaturization of portable instruments. However, as the premise of instrument design, optical optimization design of the whole spectral range is the hard work of the system. In this paper, the theoretical design method of the spectroscopic imaging system based on the small near-infrared spectrometer of DMD was studied. The method was designed by using the double-dispensing anti-aberration lens and combining the geometric aberration theory to optimize the design of a small DMD near-infrared spectrometer to reduce the aberration of the entire system. Then, the optical simulation software was used to align the direct imaging system for optical simulation. And ultimately achieve the design simulation requirements. Simulation results indicate that the whole size of the spectrometer is less than 150 mm×150 mm×150 mm, and the resolution is better than 15 nm in the range of 1000-1700 nm in the working band. Therefore, the proposed method can meet the design requirements and has broad application prospects in practical applications.

Non-Destructive Prediction of Moisture Content of Philippine Coffea arabica and Coffea liberica Green Beans Using Locally-Developed NIR Spectroscopy Instrument

Near-infrared (NIR) spectroscopy is a spectroscopic technique that uses the NIR region of the electromagnetic spectrum and analyzes the degree of absorption. It is widely used in agriculture to determine rapidly and non-destructively the internal or external qualities of agricultural products since traditional techniques are costly, labor-intensive and time-consuming. In green coffee beans, moisture content (MC) is one of the most important quality parameters; hence, rapid and reliable measurement of the attribute is essential. This study aimed to predict the MC of green coffee beans of four varieties of Coffea arabica (Typica, Caturra, Red Bourbon and Yellow Bourbon) and two accessions of Coffea liberica (Tolentino and Calabuso) using the local NIR spectrometer developed by previous researchers. Absorbance spectra of 100 samples for each variety/accession were collected and their MC was analyzed using the gravimetric method. The multivariate calibration models that considered 30 components in the region of water were established using R software by partial least squares (PLS) regression and validated using a separate set of samples. Results showed that the PLS regression model could develop multivariate models that can predict the MC of coffee beans. Among the six coffee samples, the calibration model for C. arabica – Typica obtained the highest cross-validated coefficient of determination (R 2 cv = 0.8556) with cross-validated root mean square error of prediction (RMSEPcv) of 0.6355 while C. liberica – Tolentino obtained the lowest R2 cv (0.6169) with RMSEPcv of 1.128.

Industrial-scale continuous on-line analysis of liquid hog manure by NIRS

The objective of the work was to use near-infrared spectroscopy (NIRS) to identify the pattern of distribution of the manure nutrients onto a field. The paper describes what is believed to be the first application of NIRS to continuous analysis of liquid manure on an industrial scale. The on-line analysis is accomplished without the need for a sample cell to scan the sample, or the need for sampling during manure application to the land, because the entire amount of the material is analyzed. Diode array instruments were used for continuous scanning of the manure as it was being applied. Because of differences among the instruments in spectral data, four instruments were set up in line for the development of the industrial-level calibration. Spectral data were recorded as direct reflectance over the range of 11,100 cm−1 to 5,900 cm−1. Calibrations for total solids, nitrogen, phosphorus, and potassium were developed using the Unscrambler, with a data pre-treatment of first derivative. No outliers were removed. Values of the RPD (ratio of SD of reference data to SEP) of between 3.1 and 4 were attained for all constituents. Interpolation of blind duplicates revealed that reproducibility of NIRS predictions for all constituents was significantly superior to that of laboratory analysis by certified laboratories. This was attributed to the enormous differences in the volume of manure scanned by the NIRS instruments, relative to the volumes used in laboratory analysis. Continuous scanning and analysis of liquid manures enable mapping of nutrients as they are being applied to the land, which provides valuable information to farmers as to the purchase, and efficiency of use of fertilizers.

Exploring the potential of NIRS technology for the in situ prediction of amygdalin content and classification by bitterness of in-shell and shelled intact almonds

Amygdalin is a cyanogenic compound found in almonds which gives them their bitter taste. For the almond industry, it is important to prevent the presence of bitter almonds in batches of sweet almond that can affect their commercialization and even consumer safety. This study sought to ascertain the viability of near infrared spectroscopy (NIRS), as a fast and reliable candidate for non-destructive and in situ quantification of amygdalin levels and for classification of almonds by bitterness, when analysed in bulk. With that purpose, in-shell and shelled sweet and bitter almonds were analysed in dynamic mode using two new handheld NIRS instruments. As a first step, the amygdalin levels in in-shell and shelled almonds were determined using modified partial least squares (MPLS) and local regression algorithms. Next, classification models for bitterness were made using partial least square discriminant analysis (PLS-DA). For the discrimination between sweet and bitter almonds, two strategies to set up the optimum threshold were studied: the mean value of the discriminant variables and the value calculated using the Receiver Operating Characteristic (ROC) curves. The results for measuring amygdalin in shelled almonds showed that NIRS technology, using both regression algorithms, is a robust technology for inspection purpose at an industrial level. Additionally, excellent performances were obtained for the classification models of the two in-shell and shelled almond groups analysed in bulk with both instruments, with better results when the threshold values obtained from the ROC curves were applied.

The Effect of Freeze-Drying Pretreatment on the Accuracy of Near Infrared Spectroscopic Food Analysis to Predict the Nutritive Values of Japanese Cooked Foods.

The official testing methods for establishing nutritive values are accurate but relatively costly and time-consuming. Near infrared spectroscopy (NIRS) is potentially an alternative method that can analyze several components in a few minutes using an exclusively electronic instrument with no need for a laboratory expert. However, the accuracy of commercial NIRS spectroscopic food analyzers is not sufficient for Japanese food labeling, because of interference from moisture contained in the foods. This study aims to assess the effect of a freeze-drying pretreatment on the accuracy of NIRS food analysis. Thirty-four samples, consisting of six food items habitually consumed in Japan and cooked by different cooking methods were treated by milling then freeze-drying. They were analyzed by a commercial NIRS instrument (Calorie AnswerTM) with calibration curves developed based on other freeze-dried samples. The obtained nutritive values (energy, protein, lipid, carbohydrate and moisture) were corrected to the values before freeze-drying using the vaporized moisture content. The same samples before freeze-drying were also analyzed using the official testing methods to assess the analytical accuracy using NIRS after freeze-drying, and further analyzed using the same NIRS with the commercial calibration curves to assess the effect of freeze-drying. The accuracies were better for the freeze-dried samples than for the wet samples. The magnitude of the error in energy and carbohydrate was significantly associated with the retained moisture content in the freeze-dried sample. In conclusion, freeze-drying was an effective pretreatment for improving the accuracy of NIRS analyses of Japanese cooked foods, although it is still time-consuming and needs additional investment.

Rapid Analysis of Milk Using Low-Cost Pocket-Size NIR Spectrometers and Multivariate Analysis.

The miniaturisation of analytical devices, reduction of analytical data acquisition time, or the reduction of waste generation throughout the analytical process are important requirements of modern analytical chemistry, and in particular of green analytical chemistry. Green analytical chemistry has fostered the development of a new generation of miniaturized near-infrared spectroscopy (NIR) spectrometric systems. However, one of the drawbacks of these systems is the need for a compromise between the performance parameters (accuracy and sensitivity) and the aforementioned requirements of green analytical chemistry. In this paper, we evaluated the capabilities of two recently developed portable NIR instruments (SCiO and NeoSpectra) to achieve a rapid, simple and low-cost quantitative determination of commercial milk macronutrients. Commercial milk samples from Italy, Switzerland and Spain were chosen, covering the maximum range of variability in protein, carbohydrate and fat content, and multivariate calibration was used to correlate the recorded spectra with the macronutrient content of milk. Both SCiO and NeoSpectra can provide a fast and reliable analysis of fats in commercial milk, and they are able to correctly classify milk according to fat level. SCiO can also provide predictions of protein content and classification according to presence or absence of lactose.

NIR Spectroscopic Techniques for Quality and Process Control in the Meat Industry

Near-infrared spectroscopy (NIRS) is widely used for quality and process control in the food industry. In the meat industry, the method is still used mainly for determination of fat, water, and protein content, while new applications are emerging. In this paper, we report on how in-line NIRS can be used to detect and sort chicken breast fillets with the myopathies wooden breast and spaghetti meat from normal fillets. A total of 270 fillets were measured with 2 different near-infrared systems. The near-infrared spectra contained information about protein content and water-binding properties that showed systematic differences between the 3 quality classes. Wooden breast could be well separated fro m normal fillets (96% correct classification), while spaghetti meat was slightly more difficult to separate from both normal and wooden breast because properties measured by NIRS were overlapping between the 3 groups. Two quite similar NIRS instruments had quite different classification performance, which emphasizes the importance of optimizing spectroscopic instrumentation for different applications.

Asymmetry of peripheral vascular biomarkers in ischemic stroke patients, assessed using NIRS.

.Significance: Low-frequency oscillations (LFOs) ranging from 0.01 to 0.15 Hz are common in functional imaging studies. Some of these LFOs are non-neuronal and are correlated with autonomic physiological processes.Aim: We investigate the relationships between systemic low-frequency oscillations (sLFOs) measured at different peripheral sites during resting states in ischemic stroke patients.Approach: Twenty-seven ischemic stroke patients (ages 44 to 90; 20 male and 7 female) were recruited for the study. During the experiments, fluctuations in oxyhemoglobin concentration were measured in the left and right toes, fingertips, and earlobes using a multichannel near-infrared spectroscopy instrument. We applied cross-correlation and frequency component analyses on the sLFO data.Results: The results showed that embolization broke the symmetry of the sLFO transmission and that the damage was not limited to the local area but spread throughout the body. Among six peripheral sites, the power spectrum width of the earlobes was significantly larger than that of the fingers and toes. This indicates that the earlobes may contain more physiological information. Finally, the results of fuzzy clustering verified that sLFOs can serve as perfusion biomarkers to differentiate stroke from healthy subjects.Conclusions: The high correlation values and corresponding delays in sLFOs support the hypothesis that (1) the correlation characteristics of sLFOs in stroke patients are different from those of healthy subjects. These characteristics can reflect patient condition, to an extent. Embolization in ischemic stroke patients breaks the symmetry of the body’s sLFO transmission, disrupting the balance of blood circulation. (2) sLFOs can be used as perfusion biomarkers to differentiate ischemic stroke patients from healthy subjects. Studying these signals can explicate the overall feedback/influence of pericentral interactions. Finally, peripheral sLFOs have been shown to be an effective and accurate tool for assessing peripheral blood circulation and vascular integrity in ischemic stroke patients.

Portable, field-based neuroimaging using high-density diffuse optical tomography

Behavioral and cognitive tests in individuals who were malnourished as children have revealed malnutrition-related deficits that persist throughout the lifespan. These findings have motivated recent neuroimaging investigations that use highly portable functional near-infrared spectroscopy (fNIRS) instruments to meet the demands of brain imaging experiments in low-resource environments and enable longitudinal investigations of brain function in the context of long-term malnutrition. However, recent studies in healthy subjects have demonstrated that high-density diffuse optical tomography (HD-DOT) can significantly improve image quality over that obtained with sparse fNIRS imaging arrays. In studies of both task activations and resting state functional connectivity, HD-DOT is beginning to approach the data quality of fMRI for superficial cortical regions. In this work, we developed a customized HD-DOT system for use in malnutrition studies in Cali, Colombia. Our results evaluate the performance of the HD-DOT instrument for assessing brain function in a cohort of malnourished children. In addition to demonstrating portability and wearability, we show the HD-DOT instrument’s sensitivity to distributed brain responses using a sensory processing task and measurements of homotopic functional connectivity. Task-evoked responses to the passive word listening task produce activations localized to bilateral superior temporal gyrus, replicating previously published work using this paradigm. Evaluating this localization performance across sparse and dense reconstruction schemes indicates that greater localization consistency is associated with a dense array of overlapping optical measurements. These results provide a foundation for additional avenues of investigation, including identifying and characterizing a child’s individual malnutrition burden and eventually contributing to intervention development.