Near-infrared Spectroscopy Sensor Research Articles

Early feasibility study with an implantable near-infrared spectroscopy sensor for glucose, ketones, lactate and ethanol.

To evaluate the safety and performance of an implantable near-infrared (NIR) spectroscopy sensor for multi-metabolite monitoring of glucose, ketones, lactate, and ethanol. This is an early feasibility study (GLOW, NCT04782934) including 7 participants (4 with type 1 diabetes (T1D), 3 healthy volunteers) in whom the YANG NIR spectroscopy sensor (Indigo) was implanted for 28 days. Metabolic challenges were used to vary glucose levels (40-400 mg/dL, 2.2-22.2 mmol/L) and/or induce increases in ketones (ketone drink, up to 3.5 mM), lactate (exercise bike, up to 13 mM) and ethanol (4-8 alcoholic beverages, 40-80g). NIR spectra for glucose, ketones, lactate, and ethanol levels analyzed with partial least squares regression were compared with blood values for glucose (Biosen EKF), ketones and lactate (GlucoMen LX Plus), and breath ethanol levels (ACE II Breathalyzer). The effect of potential confounders on glucose measurements (paracetamol, aspartame, acetylsalicylic acid, ibuprofen, sorbitol, caffeine, fructose, vitamin C) was investigated in T1D participants. The implanted YANG sensor was safe and well tolerated and did not cause any infectious or wound healing complications. Six out 7 sensors remained fully operational over the entire study period. Glucose measurements were sufficiently accurate (overall mean absolute (relative) difference MARD of 7.4%, MAD 8.8 mg/dl) without significant impact of confounders. MAD values were 0.12 mM for ketones, 0.16 mM for lactate, and 0.18 mM for ethanol. The first implantable multi-biomarker sensor was shown to be well tolerated and produce accurate measurements of glucose, ketones, lactate, and ethanol. Clinical trial identifier: NCT04782934.

Reference Ranges for Regional Cerebral Oxygen Saturation with Masimo O3® after Birth and Differences with Other Devices.

Cerebral oximetry using near-infrared spectroscopy (NIRS) is a noninvasive optical technology widely used in neonatology. The present study aimed to define reference ranges for cerebral tissue oxygen saturation (crSO2) with a new four-wavelength NIRS device, Masimo O3® oximeter, during immediate transition after birth and compare values with those obtained previously with NIRO 200NX®. This was a prospective observational study using Masimo O3 device to measure crSO2 and regional cerebral fractional tissue oxygen extraction (cFTOE) in healthy term newborns delivered by primary cesarean section, during the 15 minutes after cord clamping. The neonates who required any medical support were excluded. The NIRS sensor was placed on the right forehead. Peripheral oxygen saturation and heart rate were continuously measured by pulse oximetry. Previous studies which established centiles for crSO2 with NIRO 200NX were used for comparison. A total of 44 newborns were included. The median crSO2 and cFTOE (interquartile range) at 2, 5, and 7 minutes was 54% (49-54), 71% (64-86), and 79% (73-84) and 0,25 (0,18-0,33), 0,19 (0,15-0,23), and 0,16 (0,12-0,21), respectively, with no further changes afterwards. The crSO2 measurements were significantly higher with Masimo O3 compared with NIRO-200NX. The present observational study presented reference ranges for crSO2 and cFTOE measured with Masimo O3 oximeter during the immediate neonatal transition. Values obtained with O3 were higher than those obtained with other oximeters. For this reason, crSO2 is device-specific so there must be known reference values for each oximeter to define therapeutic interventions based on crSO2 and assess cerebral oxygenation in clinical studies. · Masimo O3 uses four wavelengths to measure regional oxygen saturation value.. · O3 values of crSO2 and cFTOE differ with other neonatal oximeters at birth.. · Knowledge of reference range of O3 at birth is essential to guide resuscitation..

Second sensor to improve near-infrared spectroscopy flap monitor utility: A prospective study.

This study assesses whether use of continuous noninvasive near-infrared spectroscopy (NIRS) sensor on head and neck free flap (FF) with a second sensor on nonoperated tissue improves distinction between systemic hypoperfusion and FF compromise. Single-institution, prospective study of patients undergoing head and neck FF reconstruction from December 2018 to April 2020. FFs were continuously monitored using NIRS on a monitor paddle with a second (control) sensor on the shoulder. Crude StO2 and percent change in StO2 were compared between the FF and control sensors on each patient, and percent change and percent difference between the control and the monitor paddle were documented to assess for congruity. Sentinel events (e.g., hypotension and hematoma) were documented to assess the association with change in StO2. These events and timing of StO2 changes were noted to assess associations with change in StO2. A total of 48 patients had complete data. Donor sites included 35 soft-tissue FFs and 13 fibula FFs. Average StO2 was 73.7 ± 5.5 for FFs and 71.4 ± 5.0 for control sensors. There were seven sentinel events during the study. At the time of the events, StO2 dropped significantly more for the FF than the control sensor (FF = 52.2% drop; control = 6.2% drop; p = .016). NIRS signal denoted change prior to changes in implantable arterial Doppler in all cases. The addition of a second sensor when using NIRS as a primary modality for FF monitoring may improve distinction between FF compromise events and systemic hypoperfusion. By increasing accuracy of the monitor, there is a potential for decreased resident burden and decreased use of higher level of care nursing, which could reduce overall costs.

Is It Possible to Measure the Quality of Sugarcane in Real-Time during Harvesting Using Onboard NIR Spectroscopy?

In-field quality prediction in agricultural products is mainly based on near-infrared spectroscopy (NIR). However, initiatives applied to sugarcane quality are only observed under laboratory-controlled conditions. This study proposed a framework for NIR spectroscopy sensing to measure sugarcane quality during a real harvest operation. A platform was built to support the system composed of the NIR sensor and external lighting on the elevator of a sugarcane harvester. Real-time data were acquired in commercial fields. Georeferenced samples were collected for calibration, validation, and adjustment of the multivariate models by partial least squares (PLS) regression. In addition, subsamples of defibrated cane were NIR-acquired for the development of calibration transfer models by piecewise direct standardization (PDS). The method allowed the adjustment of the spectra collected in real time to predict the quality properties of soluble solids content (Brix), apparent sucrose in juice (Pol), fiber, cane Pol, and total recoverable sugar (TRS). The results of the relative mean square error of prediction (RRMSEP) were from 1.80 to 2.14%, and the ratio of interquartile performance (RPIQ) was from 1.79 to 2.46. The PLS-PDS models were applied to data acquired in real-time, allowing estimation of quality properties and identification of the existence of spatial variability in quality. The results showed that it is possible to monitor the spatial variability of quality properties in sugarcane in the field. Future studies with a broader range of quality attribute values and the evaluation of different configurations for sensing devices, calibration methods, and data processing are needed. The findings of this research will enable a valuable spatial information layer for the sugarcane industry, whether for agronomic decision-making, industrial operational planning, or financial management between sugar mills and suppliers.

Compensatory movement detection by using near-infrared spectroscopy technology based on signal improvement method.

Compensatory movements usually occur in stroke survivors with hemiplegia, which is detrimental to recovery. This paper proposes a compensatory movement detection method based on near-infrared spectroscopy (NIRS) technology and verifies its feasibility using a machine learning algorithm. We present a differential-based signal improvement (DBSI) method to enhance NIRS signal quality and discuss its effect on improving detection performance. Ten healthy subjects and six stroke survivors performed three common rehabilitation training tasks while the activation of six trunk muscles was recorded using NIRS sensors. After data preprocessing, DBSI was applied to the NIRS signals, and two time-domain features (mean and variance) were extracted. An SVM algorithm was used to test the effect of the NIRS signal on compensatory behavior detection. Classification results show that NIRS signals have good performance in compensatory detection, with accuracy rates of 97.76% in healthy subjects and 97.95% in stroke survivors. After using the DBSI method, the accuracy improved to 98.52% and 99.47%, respectively. Compared with other compensatory motion detection methods, our proposed method based on NIRS technology has better classification performance. The study highlights the potential of NIRS technology for improving stroke rehabilitation and warrants further investigation.

An automated system of soil sensor-based site-specific seeding for silage maize: A proof of concept

Despite recent studies of map-based site-specific seeding (SSS) revealing improved agronomic and economic outcomes over uniform rate seeding (URS), to our best knowledge no visible and near infrared spectroscopy (vis-NIRS) sensor-based SSS studies exist to date. This study aimed to develop and evaluate an automated sensor-based SSS technology for silage maize (Zea mays L.) production. An on-line visible and near-infrared reflectance spectroscopy (vis-NIRS) sensor was installed in front of a tractor to provide real-time input data to control the seed rate using a precision seeding machine mounted at the back of the tractor. A LabVIEW-based software was developed and used to predict soil fertility index using on-line vis-NIR spectra, which was then used to calculate the seed rate and transfer it to the controller of the seeding machine. The agronomic and economic benefits of SSS were compared with URS under a one-site-year experiment. Results showed that the proposed sensor-based SSS technology was 87.5% efficient in controlling the desired seed rates, according to the soil fertility status. In parallel with the observed spatial similarity between predicted soil fertility index and actual seed rates, a strong linear association (R2 = 0.80) was also achieved. As a result, SSS improved silage yield by 1.4 t ha−1 (4.4%), while sowing a lower seed rate (86.4 kSeeds ha−1) than the URS (90 kSeeds ha−1). This improved gross margin by 91 € ha−1, of which only 7 € ha−1 was attributed to savings on seed cost. The proposed sensor-based SSS technology was technically sound and thus transforms within-field fertility variations into agro-economic benefits effectively.

The effect of severe intensity bouts on muscle oxygen saturation responses in trained cyclists.

Near-infrared spectroscopy (NIRS) quantifies muscle oxygenation (SmO2) during exercise. Muscle oxygenation response to self-paced, severe-intensity cycling remains unclear. Observing SmO2 can provide cycling professionals with the ability to assess muscular response, helping optimize decision-making. We aimed to describe the effect of self-paced severe intensity bouts on SmO2, measured noninvasively by a wearable NIRS sensor on the vastus lateralis (VL) muscle, and examine its reliability. We hypothesized a greater desaturation response with each bout, whereas, between trials, good reliability would be observed. Fourteen recreationally trained, and trained cyclists completed a ramp test to determine the power output (PO) at the respiratory compensation point (RCP). Athletes completed two subsequent visits of 50-minute sessions that included four severe-intensity bouts done at 5% above RCP PO. Muscle oxygenation in the VL was monitored using a wearable NIRS device. Measures included mean PO, heart-rate (HR), cadence, and SmO2 at bout onset, during work (work SmO2), and ΔSmO2. The bouts were compared using a one-way repeated measures ANOVA. For significant differences, a Fisher's least square difference post-hoc analysis was used. A two-way repeated measures ANOVA was used using trial and bout as main factors. Intraclass correlations (ICC) were used to quantify relative reliability for mean work, and standard error of the measurement (SEM) was used to quantify absolute agreement of mean work SmO2. Both PO and cadence showed no effect of bout or trial. Heart-rate at bout 2 (168 ± 8 bpm) and 4 (170 ± 7 bpm) were higher than bout 1 (160 ± 6 bpm). Onset SmO2 (%) response significantly increased in the final two bouts of the session. Mean work SmO2 increased across bouts, with the highest value displayed in bout 4 (36 ± 22%). ΔSmO2 showed a smaller desaturation response during bout 4 (27 ± 10%) compared to bout 3 (31 ± 10%). Mean work SmO2 ICC showed good reliability (ICC = 0.87), and SEM was 12% (CI 9-15%). We concluded that a non-invasive, affordable, wearable NIRS sensor demonstrated the heterogeneous muscle oxygenation response during severe intensity cycling bouts with good reliability in trained cyclists.

Cardiac and cerebral hemodynamics with umbilical cord milking compared with early cord clamping: A randomized cluster crossover trial

ObjectiveA large, randomized cluster cross-over trial (N = 1730) comparing intact umbilical cord milking (UCM) to early cord clamping (ECC) in non-vigorous near-term/term newborns demonstrated a reduction in cardiorespiratory interventions at birth and less moderate to severe hypoxic ischemic encephalopathy. We evaluated changes in cerebral tissue oxygenation (StO2), pulse oximetry (SpO2), pulse rate and fraction of inspired oxygen (FiO2) during the first 10 min of life in a subset of infants enrolled in the parent trial. Study designInfants enrolled in the Milking in Non-Vigorous Infants trial that had StO2 monitoring at birth were included in the sub-study conducted at 3 hospitals the US and Canada. A near-infrared spectroscopy sensor, pulse oximeter and electrocardiogram electrodes were placed. Pulse rate, StO2, SpO2, and FiO2 were collected for the first 10 min after birth. Longitudinal models were used to compare effects of UCM and ECC. ResultsThirty-four infants had StO2 data. Fifteen of these infants received UCM and 19 had ECC. Infants receiving UCM had similar heart rates, SpO2, and StO2 values, but were exposed to less FiO2 over the first 10 min of life than infants with ECC (0.26 ± 0.12 vs. 0.81 ± 0.05 at 10 min). ConclusionNon-vigorous term/near term infants who received UCM at birth required lower FiO2 after delivery when compared to infants who umbilical cords were clamped soon after birth while achieving similar peripheral and cerebral oxygenation. Cord milking may be a potential option for placental transfusion in non-vigorous near term/term infants when delayed cord clamping cannot be performed.

Rapid Characterization of Black Tea Taste Quality Using Miniature NIR Spectroscopy and Electronic Tongue Sensors.

The taste of tea is one of the key indicators in the evaluation of its quality and is a key factor in its grading and market pricing. To objectively and digitally evaluate the taste quality of tea leaves, miniature near-infrared (NIR) spectroscopy and electronic tongue (ET) sensors are considered effective sensor signals for the characterization of the taste quality of tea leaves. This study used micro-NIR spectroscopy and ET sensors in combination with data fusion strategies and chemometric tools for the taste quality assessment and prediction of multiple grades of black tea. Using NIR features and ET sensor signals as fused information, the data optimization based on grey wolf optimization, ant colony optimization (ACO), particle swarm optimization, and non-dominated sorting genetic algorithm II were employed as modeling features, combined with support vector machine (SVM), extreme learning machine and K-nearest neighbor algorithm to build the classification models. The results obtained showed that the ACO-SVM model had the highest classification accuracy with a discriminant rate of 93.56%. The overall results reveal that it is feasible to qualitatively distinguish black tea grades and categories by NIR spectroscopy and ET techniques.

Measuring Motor Unit Discharge, Myofiber Vibration, and Haemodynamics for Enhanced Myoelectric Gesture Recognition

It is of great significance to recognize hand gestures via measuring biological signals from forearm muscles for portable human–machine interaction (HMI). Decreasing the number of sensor nodes is imperative for practical HMI applications. However, it would be an enormous challenge to maintain gesture recognition performance for traditional myoelectric interface with sparse-site sensing. To overcome this drawback, we present a novel HMI predicting more than ten hand and wrist motions relying on only two hybrid mini-grid surface electromyography (sEMG), mechanomyography (MMG), and near-infrared spectroscopy (NIRS) sensor nodes. Beyond the time domain (TD) features of sEMG, additional information containing movement intention is measured from motor unit (MU) action potential trains (MUAPts) according to the decomposition of four-channel arrayed sEMG. Furthermore, low-frequency myofiber vibration and haemodynamics are extracted from MMG and NIRS, respectively. Experiments are performed on 13 healthy subjects to recognize 12 hand and wrist gestures. The results indicate that combining motor unit discharge feature yields consistently higher ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${p} &lt; 0.01$ </tex-math></inline-formula> ) classification accuracy (CA) (91.6%) than traditional TD features of sEMG (87.8%) using linear discrimination analysis (LDA) classifier. Additionally, both MMG and NIRS features are demonstrated effective supplementary to distinguish muscular activation patterns, producing significantly enhanced (4.2%–11.2%, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${p} &lt; 0.05$ </tex-math></inline-formula> ) recognition performance with the fused information. The outcomes of this study are promising for the HMI applications such as controlling prosthetic hand and wearable device.

Cerebral Oxygenation during Neonatal Intubation with Nasal High Flow: A Sub-Study of the SHINE Randomized Trial

Introduction: Nasal high flow (nHF) improves the likelihood of successful neonatal intubation on the first attempt without physiological instability. The effect of nHF on cerebral oxygenation is unknown. The aim of this study was to compare cerebral oxygenation during endotracheal intubation in neonates receiving nHF and those receiving standard care. Methods: A sub-study of a multicentre randomized trial of nHF during neonatal endotracheal intubation. A subset of infants had near-infrared spectroscopy (NIRS) monitoring. Eligible infants were randomly assigned to nHF or standard care during the first intubation attempt. NIRS sensors provided continuous regional cerebral oxygen saturation (rScO₂) monitoring. The procedure was video recorded, and peripheral oxygen saturation and rScO₂ data were extracted at 2-second intervals. The primary outcome was the average difference in rScO₂ from baseline during the first intubation attempt. Secondary outcomes included average rScO₂ and rate of change of rScO₂. Results: Nineteen intubations were analyzed (11 nHF; 8 standard care). Median (interquartile range [IQR]) postmenstrual age was 27 (26.5–29) weeks, and weight was 828 (716–1,135) g. Median change in rScO₂ from baseline was −1.5% (−5.3 to 0.0) in the nHF group and −9.4% (−19.6 to −4.5) in the standard care group. rScO₂ fell more slowly in infants managed with nHF compared with standard care: median (IQR) rScO₂ change −0.08 (−0.13 to 0.00) % per second and −0.36 (−0.66 to −0.22) % per second, respectively. Conclusions: In this small sub-study, regional cerebral oxygen saturation was more stable in neonates who received nHF during intubation compared with standard care.

Accuracy of Tissue Oxygen Saturation Measurements of a Textile-Based NIRS Sensor.

Pressure injuries (PI) are dangerous tissue lesions that heal very slowly and pose a high risk of serious infections. They are caused by pressure applied to the tissue, which stops blood circulation and therefore induces hypoxia, i.e., low tissue oxygen saturation (StO2). PI cause severe suffering and are expensive to treat. Hence it is essential to prevent them with a device that detects a dangerous situation, e.g., by measuring StO2 using near-infrared spectroscopy (NIRS). For such a device to be wearable without causing PI, it must not introduce pressure points itself. This can be achieved by integrating optical fibers into a textile to transport light to and from the tissue.The aim of this paper is to investigate the accuracy of StO2 measurements using a NIRS device based only on textile-integrated optical fibers.Bundles of fibers were stitched into a textile in such a way that loops of <1 mm diameters were formed at the stitching locations. Detection points (DPs) on the fabric consisted of 8 fibers with 3 loops each. Emission points (EPs) were made from 4 fibers with 3 loops each. All fiber ends of a DP were connected to an avalanche photodiode. One end of each fiber belonging to an EP was connected to an LED (740nm, 810nm, or 880nm; 290, 560, or 610mW).To verify the accuracy of this textile-based sensor, we placed it on a subject's forearm and compared the derived StO2 during arterial occlusion to the values of a gold-standard NIRS device (ISS Imagent), which was placed on the forearm too.We found that our textile-based sensor repeatedly measured StO2 values over a range of 40% with a deviation of <10% from the reference device.By showing the ability to measure StO2 using textile-integrated optical fibers accurately, we have reached a significant milestone on our way to building a wearable device to monitor tissue health and prevent PI.

Evaluation of distal skin temperature and tissue oxygen saturation determined by near-infrared spectroscopy for predicting ultrasound-guided lateral infraclavicular block success.

Changes in tissue oxygen saturation determined by near-infrared spectroscopy (NIRS) may help predict and determine the success of a lateral infraclavicular (LIC) block.We investigated whether evaluation of tissue oxygen saturation determined by NIRS couldbe an indicator of LIC block success. Forty patients scheduled for hand or forearm surgery under LIC block were studied. NIRS sensors were placed on the ventral aspect of both mid-forearms, and the contralateral hand was used as the control group. NIRS values were recorded before the block andat regular intervals during the following 30 min. NIRS values were significantly higher in the successfully blocked patients whencompared to the complete failure, partial failure, and contralateral hand groups at the 10thmin. In the successfully blocked patients, NIRS values (mean ± SD [change in %]) increasedby 11.09 ± 4.86 (16.03%), 15.00 ± 4.53 (21.76%), 16.35 ± 5.14 (23.77%), 16.38 ± 4.88(23.85%), 16.67 ± 5.04 (24.29%), and 16.96 ± 5.71 (24.78%), respectively, from baselineto 5, 10, 15, 20, 25, and 30 min. ΔTs values were significantly higher in the successfullyblocked patients than in the complete failure patients and contralateral hand at the 30thmin. However, there was no statistically significant difference when comparing ΔTs values ofsuccessful block and partial failure block patients at the 30th min. We conclude that measurement of tissue oxygen saturation by NIRS withinthe scope of evaluation of the lateral infraclavicular block is a rapid, effective, and applicabletechnique.

Laryngoscopy mediated stress response induces opposite effects on cerebral and paraspinal oxygen saturation

Background: Intraoperative sympathetic stimulation induces a cascade of metabolic and hormonal changes. It increases perfusion of vital organs, but also causes vasoconstriction of blood vessels supplying less vital organs, potentially leading to organ injury. To date, it is unknown how an endogenous stress reaction affects the spinal cord blood supply. Near-infrared spectroscopy (NIRS) can be applied paravertebrally to monitor the oxygenation of the collateral network, which contributes to the spinal cord blood supply. It has already been demonstrated that regional cerebral oxygen saturation (rScO2) increases following sympathetic stimulation. Objectives: We hypothesized that laryngoscopy would cause an increase in cerebral and paraspinal regional tissue saturations (rScO2 and rSpsO2, respectively). Design: Retrospective analysis of a previous conducted randomized trial. Setting: Laryngoscopy in the operating room. Methods: Data of 28 patients, scheduled for arterial dilation of the lower limb, were retrospectively analyzed. Before induction of anesthesia, standard monitoring, BIS and 8 NIRS sensors were applied (two on the forehead, six bilaterally on the back at T3-T4, T9-T10 and L1-L2). Sympathetic stimulation was induced by laryngoscopy. Main outcome measures: Changes in rStO2 following sympathetic stimulation induced by laryngoscopy. Results: Following laryngoscopy, rScO2 significantly increased and rSpsO2 significantly decreased at T9-T10 and L1-L2. The relative changes (regional tissue oxygen saturation (rStO2) after intubation-rStO2 before intubation)/ rStO2 before intubation), at cerebral level, T9-T10 and L1-L2 were 9%, -5% and -3%, respectively (p &lt; 0.01). rSpsO2 at T3-T4 did not change significantly. Changes (Δ) in mean arterial pressure following laryngoscopy were weakly correlated with ΔrScO2 and moderately correlated with ΔrSpsO2 at T9-T10 and L1-L2. Conclusions: Intraoperative sympathetic stimulation may decrease the oxygen supply to the spinal cord. Trial registration: The trial was registered at ClinicalTrials.gov (NCT 03767296).

Development of a Wireless Multichannel Near-Infrared Spectroscopy Sensor System for Monitoring Muscle Activity

Near-infrared spectroscopy (NIRS) technology is a noninvasive technology that can detect the hemoglobin concentration in the shallow tissue of humans in the form of an optical signal and determine the muscle’s activation state based on the change of hemoglobin concentration. It has a broad application prospect in the biomedical and physiological signal analysis. There are specific requirements for the structure of NIRS sensors for different application scenarios. The muscle synergy theory explains that body movements are often accompanied by the cooperation of many different muscles. Therefore, a multichannel NIRS system is necessary for motion recognition. This article presents a distributed multichannel NIRS system. The wireless communication avoids the interference of signal lines, and the equipped upper computer system can display NIRS signals in real time. Our NIRS sensors have three different wavelengths of near-infrared light (750, 800, and 850 nm) and two photodiodes, which can effectively improve the sampling accuracy of the signal. Experimental verification and evaluation prove that our system’s performance and reliability are better than those of other NIRS systems. Finally, cuff occlusion and hand motion experiments demonstrated that blood flow and oxygen consumption are the two main factors that cause hemoglobin concentration changes. We offer a new scheme for NIRS signal analysis that uses the common mode and difference mode of Hb and HbO2, and the results demonstrate its superior performance. In future work, we will discuss the application and effect of the NIRS system in rehabilitation training.

Estimation of the sensory properties of black tea samples using non-destructive near-infrared spectroscopy sensors

The quality characteristics of black tea are routinely assessed before it is purchased, blended and marketed to ensure its quality and value. Although some of these quality characteristics can be measured analytically, others need to be determined as sensory scores following cupping tests conducted by tea experts. However, most of these analyses (especially the sensory ones) require high training and expertise, are time-consuming and prone to human error. Therefore, in this study, non-destructive spectral sensors were combined with chemometric methods to rapidly measure the results of the cupping test (appearance, body, colour and overall quality) and some other important sensory quality attributes (bulk density, cellulose, water extract and moisture) of black tea samples. A total of 54 black tea samples from Türkiye were analysed in three different NIRS (near-infrared spectroscopy) devices (MicroNIR™ 1700, Matrix-F FT-NIR and NIRS DS 2500). Partial Least Squares Regression (PLSR) and Principal Components Regression (PCR) with stepwise variable elimination were used as regression algorithms to develop the NIR calibrations. As a result, PLSR provided slightly superior estimates with Rcv2 between 0.83 and 0.97 and RPDcv between 2.47 and 5.79 for sensory traits. For analytical traits, model statistics for PLSR ranged between 0.66-0.89 and 1.72–3.08 for Rcv2 and RPDcv, respectively. These results suggest that PLSR combined with FT-NIR technology may be promising for rapid and economical evaluation of sensory (cupping test) scores and related properties for its use in the tea industry.

Optical Monitoring of Breathing Patterns and Tissue Oxygenation: A Potential Application in COVID-19 Screening and Monitoring.

The worldwide outbreak of the novel Coronavirus (COVID-19) has highlighted the need for a screening and monitoring system for infectious respiratory diseases in the acute and chronic phase. The purpose of this study was to examine the feasibility of using a wearable near-infrared spectroscopy (NIRS) sensor to collect respiratory signals and distinguish between normal and simulated pathological breathing. Twenty-one healthy adults participated in an experiment that examined five separate breathing conditions. Respiratory signals were collected with a continuous-wave NIRS sensor (PortaLite, Artinis Medical Systems) affixed over the sternal manubrium. Following a three-minute baseline, participants began five minutes of imposed difficult breathing using a respiratory trainer. After a five minute recovery period, participants began five minutes of imposed rapid and shallow breathing. The study concluded with five additional minutes of regular breathing. NIRS signals were analyzed using a machine learning model to distinguish between normal and simulated pathological breathing. Three features: breathing interval, breathing depth, and O2Hb signal amplitude were extracted from the NIRS data and, when used together, resulted in a weighted average accuracy of 0.87. This study demonstrated that a wearable NIRS sensor can monitor respiratory patterns continuously and non-invasively and we identified three respiratory features that can distinguish between normal and simulated pathological breathing.

Domain Adaptation for In-Line Allergen Classification of Agri-Food Powders Using Near-Infrared Spectroscopy.

The addition of incorrect agri-food powders to a production line due to human error is a large safety concern in food and drink manufacturing, owing to incorporation of allergens in the final product. This work combines near-infrared spectroscopy with machine-learning models for early detection of this problem. Specifically, domain adaptation is used to transfer models from spectra acquired under stationary conditions to moving samples, thereby minimizing the volume of labelled data required to collect on a production line. Two deep-learning domain-adaptation methodologies are used: domain-adversarial neural networks and semisupervised generative adversarial neural networks. Overall, accuracy of up to 96.0% was achieved using no labelled data from the target domain moving spectra, and up to 99.68% was achieved when incorporating a single labelled data instance for each material into model training. Using both domain-adaptation methodologies together achieved the highest prediction accuracies on average, as did combining measurements from two near-infrared spectroscopy sensors with different wavelength ranges. Ensemble methods were used to further increase model accuracy and provide quantification of model uncertainty, and a feature-permutation method was used for global interpretability of the models.

Efficient monitoring for the nutrient changes in stir-fried Moutan Cortex using non-destructive near-infrared spectroscopy sensors

Now, almost all solutions are moving toward miniaturization of devices. Stir-frying, as a food processing process, presents field analysis challenges to the NIR foundation. Therefore, in this paper, Moutan Cortex, a functional food product that requires strict control of stir-frying degree, with a variety of biological activities such as antioxidant, anti-inflammatory and protection of cardiovascular system, was investigated to realize the qualitative and quantitative analysis of the product on site through miniaturized spectrometer NIR-S-G1. TANGO FT-NIR, a precision benchtop instrument, was applied as a reference to observe the field analysis performance of the instrument. The results show that the handheld device can accurately judge the products of different stir-frying degrees by SVM model with the accuracy rate of 100%. At the same time, it can accurately and quantitatively monitor the four main components in the process. Also combinations of optimization algorithms (Competitive Adaptive Weighted sampling, variable combination population analysis combined with iteratively retaining informative variables and genetic algorithm) and regression models (Partial least squares regression and Support Vector Machine) were investigated to perform a better result. Therefore, this work provided a reference for the field analysis of NIR technology from qualitative and quantitative analysis in this specific analytical application.

Monitoring of intraoperative femoral oxygenation predicts acute kidney injury after pediatric cardiac surgery.

Cardiopulmonary bypass-associated acute kidney injury (CPB-AKI) is a pediatric cardiac surgery postoperative complication that is associated with a longer duration of mechanical ventilation and length of hospital stay. Identifying an early predictor of CPB-AKI is critical. Near infrared spectroscopy (NIRS), which can provide real-time monitoring of regional tissue oxygen saturation (rSO2) during CPB, may predict CPB-AKI in an early phase of surgical treatment. This study analyzed clinical data from 87 children who underwent an elective surgical repair of ventricular septal defect (VSD) from January 2013 to March 2019. NIRS sensors were placed on the patients' forehead, abdomen, and thighs. The pediatric modified risk, injury, failure, loss, and end-stage (p-RIFLE) score was determined for each patient postoperatively. The incidence of AKI based on the p-RIFLE classification was 11.5% at the end of surgery, 23.0% at 24 h after surgery, and 5.7% at 48 h after surgery. The AKI incidence rate was highest at 24 h after surgery. Multiple regression analysis revealed that femoral oxygenation (rSO2) during CPB, CPB time, oxygen delivery index (DO2i), and lactate at the end of CPB were independent risk factors for AKI. Receiver-operating characteristic curve analysis indicated that femoral oxygenation of 74% or less predicted AKI development within 24 h after surgery. In conclusion, rSO2 measured at the thigh during CPB is highly predictive of CPB-AKI.