Near-infrared Spectroscopy Research Articles

Near-infrared Spectral Homogeneity of the Didymos System Before and After the DART Impact* * Based on observations made with the Italian Telescopio Nazionale Galileo (TNG) operated on the island of La Palma by the Fundación Galileo Galilei of the Istituto Nazionale di Astrofisica (INAF) at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias

We spectroscopically characterized the Didymos system, target of the Double Asteroid Redirection Test (DART)/Light Italian Cubesat for Imaging of Asteroids (LICIACube) space mission, close in time to the DART impact event, during six nights between 2022 August and November at Telescopio Nazionale Galileo. Here, we show that near-infrared (NIR) spectra (0.75–2.25 μm) look mostly similar within the same night and between different nights. They are in good agreement with the only spectrum previously available in the literature, observed almost 20 years before those reported in this paper. During one of the observing nights we also obtain spectroscopy information on the ejecta tail induced by the DART impact. The spectrum of the ejecta tail is also very similar to Didymos/Dimorphos itself. All of these aspects seem to suggest that the Didymos system in the NIR looks mostly homogeneous, with very subtle spectral variations.

Growth, first-principles calculations and optical properties of a novel near-infrared Ho: NLGW laser crystal

A rigid structure was constructed using an isotopic doping strategy, and a novel near-infrared 1 at% Ho3+: NaLa0.93Gd0.06(WO4)2 (Ho: NLGW) laser crystal with a size of Φ 18 mm × 30 mm was successfully grown by the Czochralski method. X-ray rocking curves and Rietveld refinement indicate that the grown crystal possesses high crystalline quality and crystallizes in the I41/a space group with lattice parameters: a = b = 5.3518 Å, c = 11.6438 Å and V = 333.5051 Å3. The Ho: NLGW crystal exhibits a low coefficient of thermal expansion (8.472 × 10−6 K−1), and the c-axis thermal conductivity increases from 1.235 W/(m × K) to 1.404 W/(m × K). The thermal properties of the Ho: NLGW crystal surpass those of other Ho3+-doped tungstate series and mainstream near-infrared laser crystals, suggesting that it is easier to obtain excellent laser gain. For revealing the excellent thermal properties, the elastic moduli of the NLW and NLGW crystals have been calculated by first principles. With the introduction of Gd3+, the structural stiffness of the NLW as a whole has been increased to optimize the mechanical properties in each axial direction and to obtain the reason for the larger Debye temperature. Finally, the transmission, absorption and near-infrared emission spectra of the Ho: NLGW crystal were investigated. The crystal exhibits a high transmittance of 88.5 % and an emission cross-section of 0.84 × 10−20 cm2 calculated according to the J-O theory. Experimental results indicate that the grown Ho: NLGW crystal can achieve large laser output more easily and are expected to be an excellent medium for 2 μm solid-state lasers.

Enhancing forensic blood detection using hyperspectral imaging and advanced preprocessing techniques

Bloodstains are pivotal in forensic investigations as they can provide crucial DNA information about individuals involved in a crime. Traditional methods for bloodstain detection, including chemical tests and forensic lights, have limitations such as non-specificity to human blood and susceptibility to false positives. In forensic blood detection, molecular spectroscopy is crucial for identifying the unique spectral fingerprints of blood, which arise from its molecular composition. Hyperspectral imaging (HSI) leverages this principle by capturing a wide spectrum of light for each pixel in an image, allowing for the detailed analysis of various substances. HSI has emerged as a promising alternative, offering non-contact, rapid, and cost-effective detection of bloodstains by analyzing the visible and near-infrared electromagnetic spectrum. This study explores the application of HSI for blood detection, addressing challenges such as spectral mixing, time-related changes in bloodstain spectra, and data complexity. The study introduces a novel framework to optimize HSI data, enhancing the accuracy and efficiency of bloodstain classification, called the Fast Extraction (FE) framework. It includes two stages. The main method in the first one is the Enhancing Transformation Reduction (ETR) method to reduce the dimension and complexity of the HSI. The second stage contains a compatible classification model to enhance feature extraction and classification. Our approach is validated using the HyperBlood datasets and many evaluation methods, demonstrating superior performance compared to state-of-the-art deep learning models. It provides high accuracy (97%–100 %) for all HSIs, overcoming various difficulties and blood collection times.

Evaluation of foveal avascular zone changes in patients with type 1 diabetes using optical coherence topography angiography

Aim To evaluate vascular changes in the foveal avascular zone in pediatric patients with type 1 diabetes by using optical coherence tomography angiography (OCTA). Patients and methods This cross-sectional study was performed in Benha University Hospital at Department of Ophthalmology. The patients were obtained from the Pediatric Endocrinology Clinic in Benha University Hospital. The study was conducted on 48 patients (96 eyes) divided into two groups: group A, 24 diabetic children with type 1 diabetes, group B, 24 healthy children of the same age and sex who met the inclusion criteria. The patients were collected from April 2022 to April 2023. The patients were photographed using the Optovue AngioVue OCTA System. Results Our results show that according to the foveal avascular zone it was slightly wider in type 1 diabetic cases with no clinically evident diabetes retinopathy (DR) than control. There were insignificant differences between the two groups as regards foveal density, but as regards foveal thickness, it was significantly lower in diabetic cases than in the control group. Conclusion We discovered that OCTA could consistently identify microvascular changes in the Deep and Superficial Capillary Plexus prior to the clinical indications’ onset of DR. In order to assess the OCTA potential for the screening of DR in children with T1DM, it is necessary to conduct numerous prospective studies.

Accidental Corneal Intrastromal Intraocular Lens Implantation During Cataract Surgery: A Case Report

Purpose To report an unusual but important complication of routine cataract surgery, accidental intrastromal intraocular lens (IOL) implantation. Methods During cataract surgery in a 66-year-old man, the IOL was delivered into the intrastromal space of the cornea accidentally. The lens was removed immediately and carefully by enlarging the corneal tunnel. Results Anterior segment optical coherence topography (AS-OCT) was used for postoperative follow-up of the patient, which showed a viscoelastic substance in the stroma of the cornea that was washed out. Ther patient's final visual acuity was 20/20. Conclusions A uniplanar corneal incision with wound-assisted IOL insertion can lead to intrastromal IOL injection. If a cataract surgeon encounters such a complication, AS-OCT could be a useful imaging technique for follow-up. [ Journal of Refractive Surgery Case Reports . 2024;4(4):e36–e39.]

Intelligent Monitoring of Post-Processing Characteristics in 3D-Printed Food Products: A Focus on Fermentation Process of Starch-gluten Mixture Using NIR and Multivariate Analysis

The production of three-dimensional (3D)-printed food products requires not only optimal 3D-printing adaptability but also appropriate post-processing characteristics. This study aimed to use near infrared (NIR) spectroscopy to predict the rheological properties of 3D-printed dough, enabling intelligent monitoring of the dough’s fermentation process. Utilizing support vector machine (SVM) classification model, the fermentation stages can be classified as under-fermentation, complete fermentation, and over-fermentation. Employing preprocessing methods with Synergy Interval Partial Least Square-Competitive Adaptive Reweighted Sampling (SIPLS-CARS) algorithm, 27, 39, 23, and 27 key wavelengths were filtered from the raw NIR spectral data, corresponding to the prediction of storage modulus (G'), loss modulus (G''), complex viscosity (η*), and loss factor (tan δ), respectively. Quantitatively, SVM (Support Vector Machine) regression outperformed Partial Least Squares (PLS) with Rc2 values (0.95, 0.94, 0.94) and Rp2 values (0.93, 0.93, 0.94) for G', G'', and η*. NIR spectra-based predictive models demonstrated superior performance compared to rheo-fermentation properties models. In summary, these findings show the potential of NIR spectroscopy as a rapid tool for predicting the fermentation progress of 3D-printed doughs.

Comparing different motion correction approaches for resting-state functional connectivity analysis with functional near-infrared spectroscopy data.

Motion artifacts are a notorious challenge in the functional near-infrared spectroscopy (fNIRS) field. However, little is known about how to deal with them in resting-state data. We assessed the impact of motion artifact correction approaches on assessing functional connectivity, using semi-simulated datasets with different percentages and types of motion artifact contamination. Thirty-five healthy adults underwent a 15-min resting-state acquisition. Semi-simulated datasets were generated by adding spike-like and/or baseline-shift motion artifacts to the real dataset. Fifteen pipelines, employing various correction approaches, were applied to each dataset, and the group correlation matrix was computed. Three metrics were used to test the performance of each approach. When motion artifact contamination was low, various correction approaches were effective. However, with increased contamination, only a few pipelines were reliable. For datasets mostly free of baseline-shift artifacts, discarding contaminated frames after pre-processing was optimal. Conversely, when both spike and baseline-shift artifacts were present, discarding contaminated frames before pre-processing yielded the best results. This study emphasizes the need for customized motion correction approaches as the effectiveness varies with the specific type and amount of motion artifacts present.

Atypical prefrontal neural activity during an emotional interference control task in adolescents with autism spectrum disorder: A functional near-infrared spectroscopy study

Atypical prefrontal neural activity during an emotional interference control task in adolescents with autism spectrum disorder: A functional near-infrared spectroscopy study

Characteristic Changes of Prefrontal and Motor Areas in Patients with Type 2 Diabetes and Major Depressive Disorder During a Motor Task of Tai Chi Chuan: A Functional Near-Infrared Spectroscopy Study.

This cross-sectional study aims to identify the characteristic changes of prefrontal and motor areas during a tai chi chuan task in patients with Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) using wearable functional near-infrared spectroscopy (fNIRS). Three parallel groups (T2DM with DD group, T2DM group, and healthy group) were recruited from December 10, 2022, to May 31, 2023. Participants in three groups conducted a motor task of tai chi chuan designed by Eprime 3.0, and fNIRS was used to monitor the brain activation, functional connectivity (FC), and lateralization of prefrontal and motor areas. Correlation analyses were performed to examine the relationship between depressive symptoms and the function of prefrontal and motor areas. Ninety elder adults (aged ≥ 60), including 30 patients with T2DM and MDD, 30 patients with T2DM, and 30 healthy subjects, were enrolled. In contrast with the patients with T2DM and healthy subjects, the patients with T2DM and MDD had decreased activation and abnormal lateralization in prefrontal and motor areas and decreased FC among supplementary motor area, motor area, and dorsolateral prefrontal cortex (DLPFC). Furthermore, the oxyhemoglobin (HbO2) concentration value of DLPFC in patients with T2DM and MDD was negatively associated with scores of Hamilton Depression Scale-24 (HAMD-24). Patients with T2DM and MDD had characteristic functional changes in prefrontal and motor areas. DLPFC may be a potential target of diagnosis and intervention for patients with T2DM and MDD.

CT-Net: an interpretable CNN-Transformer fusion network for fNIRS classification.

Functional near-infrared spectroscopy (fNIRS), an optical neuroimaging technique, has been widely used in the field of brain activity recognition and brain-computer interface. Existing works have proposed deep learning-based algorithms for the fNIRS classification problem. In this paper, a novel approach based on convolutional neural network and Transformer, named CT-Net, is established to guide the deep modeling for the classification of mental arithmetic (MA) tasks. We explore the effect of data representations, and design a temporal-level combination of two raw chromophore signals to improve the data utilization and enrich the feature learning of the model. We evaluate our model on two open-access datasets and achieve the classification accuracy of 98.05% and 77.61%, respectively. Moreover, we explain our model by the gradient-weighted class activation mapping, which presents a high consistent between the contributing value of features learned by the model and the mapping of brain activity in the MA task. The results suggest the feasibility and interpretability of CT-Net for decoding MA tasks.

Electrophysiological and hemodynamic mechanisms underlying load modulations in visuospatial working memory: A functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) study.

The n-back task has been widely used to study working memory. Previous studies investigating the electrophysiological (electroencephalogram [EEG]) and hemodynamic correlates (functional near-infrared spectroscopy [fNIRS]) of the n-back task have been generally based on verbal stimuli and only investigated EEG frequency bands. We simultaneously acquired the EEG and fNIRS in 35 participants (16 males; age = 26.4 ± 4.3 years; educational attainment = 18 ± 2 years) during a visuospatial n-back task. The task encompassed a control condition and a low (requiring to recall one previous stimulus) and a high (requiring to recall two previous stimuli) working memory load experimental conditions. Accuracy decreased and reaction times slowed in the high compared to both low load and control conditions. Regarding EEG, P3a showed higher amplitude in the experimental conditions compared to the control one, and P3b exhibited higher amplitude in the low compared to the high load condition. Regarding fNIRS, the high load condition showed higher deoxygenated hemoglobin compared to the control one. Moreover, the central frontopolar cortex showed higher activation compared with the left frontal cortex. Our study showed that working memory load during a visuospatial n-back task influenced behavioral and electrophysiological indices. Even if the load effect was only observed for deoxygenated hemoglobin on hemodynamic data, this was in line with previous studies and coherent with its electrophysiological correlates. Thus, our study confirms that EEG and fNIRS can be successfully used in multimodal acquisitions, but also highlights that future studies are needed to develop a novel version of the task. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Analgesic effect of dance movement therapy: An fNIRS study

ObjectiveThis study aims to explores the physiological and psychological mechanisms of exercise-induced hypoalgesia (EIH) by combining the behavioral results with neuroimaging data on changes oxy-hemoglobin (HbO) in prefrontal cortex (PFC). MethodsA total of 97 healthy participants were recruited and randomly divided into three groups: a single dance movement therapy (DMT) group, a double DMT group, and control group. Evaluation indicators included the pressure pain threshold (PPT) test, the color-word stroop task (CWST) for wearing functional near-infrared spectroscopy (fNIRS), and the self-assessment manikin (SAM). The testing time is before intervention, after intervention, and one hour of sit rest after intervention. Results1) Repeated measures ANOVA revealed that, there is a time * group effect on the PPT values of the three groups of participants at three time points. After 30 min of acute dance intervention, an increase in the PPT values of 10 test points occurred in the entire body of the participants in the experimental group with a significant difference than the control group. 2) In terms of fNIRS signals, bilateral DLPFC and left VLPFC channels were significantly activated in the experimental group. 3) DMT significantly awakened participants and brought about pleasant emotions, but cognitive improvement was insignificant. 4) Mediation effect analysis found that the change in HbO concentration in DLPFC may be a mediator in predicting the degree of improvement in pressure pain threshold through dance intervention (total effect β = 0.7140). ConclusionIn healthy adults, DMT can produce a diffuse EIH effect on improving pressure pain threshold, emotional experience but only showing an improvement trend in cognitive performance. Dance intervention significantly activates the left ventrolateral and bilateral dorsolateral prefrontal cortex. This study explores the central nervous system mechanism of EIH from a physiological and psychological perspective.

The effect of different visual feedback interfaces of music training games on speech rehabilitation in hearing-impaired children: An fNIRS study

Singing plays a critical role in enhancing musicality, sound discrimination, and attention, and proves advantageous for speech rehabilitation in children with hearing impairments. Computer-based training games are well-suited to the learning behaviors of children, with substantial evidence suggesting that music training augments speech training capabilities in this demographic. Despite this, there is a lack of detailed exploration into the design of interactive online music training interfaces tailored for these needs. This study investigates brain activation changes using two visual feedback singing games, analyzed through functional near-infrared spectroscopy: a serious game (SG) and an entertainment game (EG) with visually enhanced feedback. It also assesses the efficacy of home-based music training software for speech rehabilitation.Methods involved recording oxygenated hemoglobin concentration (Delta [HbO]) signals from the prefrontal cortex, motor cortex, occipital lobe, and temporal lobe in 21 children (average age: 9.3 ± 1.9 years) during two singing interface experiments. Subjects also completed the Intrinsic Motivation Inventory (IMI) questionnaire post-experiment.Main results showed that brain regions, particularly the temporal lobe, exhibited stronger and more pronounced activation signals with the SG interface compared to the EG, suggesting that SG is more effective for speech system rehabilitation. The Intrinsic Motivation Scale results revealed higher acceptability for SG than for EG. This study provides insights into designing online speech rehabilitation products for children with hearing impairment, advocating for better interactive training methods from a neuroscience perspective.

Exergames: Effects On Executive Function In Sedentary University Students Measured With Functional Near-infrared Spectroscopy

Exergames: Effects On Executive Function In Sedentary University Students Measured With Functional Near-infrared Spectroscopy

Assessing Leg Blood Flow In Multiple Locations Using Multiple Near-infrared Spectroscopy Devices

Assessing Leg Blood Flow In Multiple Locations Using Multiple Near-infrared Spectroscopy Devices

Sport training of axial rotation affects spatial ability: evidence from behavior and fNIRS

The present study investigated the spatial ability of adolescent athletes with different sport expertise of axial rotation, providing the cognitive characteristics from both behavior and functional near-infrared spectroscopy (fNIRS) tests. 16 basketball and soccer players, 15 freestyle athletes and 15 runners were selected for spatial ability testing with a three-factor mixed experimental design of 3 (sport type: open high-spatial sport, closed high-spatial sport, closed low-spatial sport) × 2 (rotation angle: 45°, 90°) × 3 (rotation axis: horizontal, vertical, longitudinal). Repeated-measures ANOVA was performed to evaluate the behavioral and fNIRS data of the mental rotation test. The behavioral data showed that the closed high-spatial (CH) group showed better performance than the open high-spatial (OH) and closed low-spatial (CL) group for large angle for every rotation axes. The fNIRS results showed the CH group had greater brain activation than the OH and CL group in the left dorsolateral superior frontal gyrus, precentral gyrus, postcentral gyrus, superior parietal gyrus, left angular gyrus, left precuneus and middle occipital gyrus. The findings provide additional empirical support for relating body rotation experience to spatial cognition performance.

TCT-16 Intracoronary Near-Infrared Spectroscopy to Predict No-Reflow Phenomenon During Percutaneous Coronary Intervention in Acute Coronary Syndrome

TCT-16 Intracoronary Near-Infrared Spectroscopy to Predict No-Reflow Phenomenon During Percutaneous Coronary Intervention in Acute Coronary Syndrome

Feasibility of Near-Infrared Spectroscopy and Peripheral Arterial Disease Risk in CKD

Feasibility of Near-Infrared Spectroscopy and Peripheral Arterial Disease Risk in CKD

Novel multimodal sensing and machine learning strategies to classify cognitive workload in laparoscopic surgery

BackgroundSurgeons can experience elevated cognitive workload (CWL) during surgery due to various factors including operative technicalities and the environmental demands of the operating theatre. This can result in poorer outcomes and have a detrimental effect on surgeon well-being. The objective measurement of CWL provides a potential solution to facilitate classification of workload levels, however results are variable when physiological measures are used in isolation. The aim of this study is to develop and propose a multimodal machine learning (ML) approach to classify CWL levels using a bespoke sensor platform and to develop a ML approach to impute missing pupil diameter measures due to the effect of blinking or noise. Materials and MethodsTen surgical trainees performed a simulated laparoscopic cholecystectomy under cognitive conditions of increasing difficulty, namely a modified auditory N-back task with increasing difficulty and a verbal clinical scenario. Physiological measures were recorded using a novel platform (MAESTRO). Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) were used as direct measures of CWL. Indirect measures included electromyography (EMG), electrocardiography (ECG) and pupil diameter (PD). A reference point for validation was provided by subjective assessment of perceived CWL using the SURG-TLX. A multimodal machine learning approach that systematically implements a CNN-BiLSTM, a binary version of the metaheuristic Manta Ray Foraging Optimisation (BMRFO) and a version of Fuzzy C-Means (FCM) called Optimal Completion Strategy (OCS) was used to classify the associated perceived CWL state. ResultsCompared to other state-of-art classification techniques, cross-validation results for the classification of CWL levels suggest that the CNN-BLSTM and BMRFO approach provides an average accuracy of 97% based on the confusion matrix. Additionally, OCS demonstrated a superior average performance of 9.15% in terms of Root-Mean-Square-Error (RMSE) when compared to other PD imputation methods. ConclusionPerceived CWL levels were correctly classified using a multimodal ML approach. This approach provides a potential route to accurately classify CWL levels, which may have application in future surgical training and assessment programs as well as the development of cognitive support systems in the operating room.

Near-infrared luminescence in Ca3ZnMGe3O12:Cr3+ (M = Zr, Hf, Sn, Ti) garnet family for light-emitting diode applications

Near-infrared (NIR) phosphors as crucial components of NIR light sources have multifunctional and smart spectroscopy applications, prompting an increasing research interest in developing efficient and stable NIR materials. Focusing on this issue, the present study explored the luminescent properties of Cr3+-doped Ca3ZnMGe3O12 (M = Zr, Hf, Sn and Ti) garnet family. These materials exhibit an emission peak falls within the range of 785–805 nm with a full width at half maximum (FWHM) varying from 114 to 123 nm. Among them, the Ca3ZnZrGe3O12:Cr3+ phosphor shows the highest photoluminescence quantum yield (PLQY = 60.3 %) and an excellent thermal stability (I423K/I298K = 77.51 %). Moreover, the performance of a prototype Ca3ZnZrGe3O12:Cr3+-containing NIR pc-LED device was estimated, which achieves an NIR output of 23.46 mW and a photonic efficiency of 14.09 % under 100 mA driving current. Non-destructive examination can be realized using this light source, demonstrating the good potential of the material in NIR spectroscopy applications.