Integrating fNIRS and machine learning: shedding light on Parkinson's disease detection.

The purpose of this research is to introduce an approach to assist the diagnosis of Parkinson's disease (PD) by classifying functional near-infrared spectroscopy (fNIRS) studies as PD positive or negative. fNIRS is a non-invasive optical signal modality that conveys the brain's hemodynamic response, specifically changes in blood oxygenation in the cerebral cortex; and its potential as a tool to assist PD detection deserves to be explored since it is non-invasive and cost-effective as opposed to other neuroimaging modalities. Besides the integration of fNIRS and machine learning, a contribution of this work is that various approaches were implemented and tested to find the implementation that achieves the highest performance. All the implementations used a logistic regression model for classification. A set of 792 temporal and spectral features were extracted from each participant's fNIRS study. In the two best performing implementations, an ensemble of feature-ranking techniques was used to select a reduced feature subset, which was subsequently reduced with a genetic algorithm. Achieving optimal detection performance, our approach reached 100 % accuracy, precision, and recall, with an F1 score and area under the curve (AUC) of 1, using 14 features. This significantly advances PD diagnosis, highlighting the potential of integrating fNIRS and machine learning for non-invasive PD detection.

An end-to-end approach for single-cell infrared absorption spectroscopy of bacterial inclusion bodies: from AFM-IR measurement to data interpretation of large sample sets.

BACKGROUND: Inclusion bodies (IBs) are well-known subcellular structures in bacteria where protein aggregates are collected. Various methods have probed their structure, but single-cell spectroscopy remains challenging. Atomic Force Microscopy-based Infrared Spectroscopy (AFM-IR) is a novel technology with high potential for the characterisation of biomaterials such as IBs. RESULTS: We present a detailed investigation using AFM-IR, revealing the substructure of IBs and their variation at the single-cell level, including a rigorous optimisation of data collection parameters and addressing issues such as laser power, pulse frequency, and sample drift. An analysis pipeline was developed tailored to AFM-IR image data, allowing high-throughput, label-free imaging of more than 3500 IBs in 12,000 bacterial cells. We examined IBs generated in Escherichia coli under different stress conditions. Dimensionality reduction analysis of the resulting spectra suggested distinct clustering of stress conditions, aligning with the nature and severity of the applied stresses. Correlation analyses revealed intricate relationships between the physical and morphological properties of IBs. CONCLUSIONS: Our study highlights the power and limitations of AFM-IR, revealing structural heterogeneity within and between IBs. We show that it is possible to perform quantitative analyses of AFM-IR maps over a large collection of different samples and determine how to control for various technical artefacts.

Bioenergy feedstock production in Chlamydomonas reinhardtii (microalgae) cultivated under mixotrophic growth with cellulose hydrolysate from agricultural waste.

In the present study, cellulose purified from finger millet agricultural waste is subjected to enzymatic hydrolysis, and the hydrolysate (predominantly glucose) is used as a carbon source supplement in the media for the mixotrophic growth of Chlamydomonas reinhardtii. Interestingly, a switch between excess starch production and excess lipid (triacylglycerols, TAG) production occurs by a small change in hydrolysate concentration in the media. Starch production increased 4.5-fold with respect to the photoautotrophic control, with a glucose concentration of 3 mg/mL in the media after hydrolysate addition. This culture had TAG production enhancement by 1.5-fold. However, mixotrophic cultivation with 4 mg/mL glucose concentration in the media with hydrolysate addition resulted in TAG productivity enhancement by 4.2-fold compared to control and starch amount increase of 1.3-fold. The organic carbon source (glucose) and the inorganic carbon source (citrate ions) in the hydrolysate together played a role in this delicate switching between starch and lipid pathways. Proteins, starch, and TAG molecules are analyzed in the microalgal cells grown under different conditions with FTIR spectroscopy, a rapid, high-throughput method of biomolecular estimation. High-resolution single-cell AFM studies of the cell wall structure reveal enhanced corrugations in surface morphology during mixotrophic growth with cellulose hydrolysate, illustrating an adaptive mechanism with improved mechanical stress management. Lipid droplet morphology at the single-cell level points to two distinct mechanisms of lipid accumulation: one in which the lipids are segregated as droplets, and the other in which lipid molecules are uniformly dispersed in the cytosol as unresolved, ultra-small droplets. The present study therefore analyzes both the bulk and the single-cell level changes when cellulose hydrolysate is used as a carbon source for Chlamydomonas reinhardtii mixotrophic cultivation, which serves a four-fold purpose: value from waste, fixation of atmospheric CO2, production of lipids for biodiesel, and starch for bioethanol.

Characterization and ecological risk assessment of microplastics accumulated in sea water, sand, sediment, shell water and selected tissues of hermit crab of Sundarban Biosphere Reserve.

Sundarban, a Ramsar site of India, has been encountering an ecological threat due to the presence of microplastic (MP) wastes generated from different anthropogenic sources. Clibanarius longitarsus, an intertidal hermit crab of Sundarban Biosphere Reserve, resides within the abandoned shell of a gastropod mollusc, Telescopium telescopium. We characterized and estimated the MP in the gills and gut of hermit crab, as well as in the water present in its occupied gastropod shell. The average microplastic abundance in sea water, sand and sediment were 0.175 ± 0.145 MP L-1, 42 ± 15.03 MP kg-1 and 67.63 ± 24.13 MP kg-1 respectively. The average microplastic load in hermit crab was 1.94 ± 0.59 MP crab-1, with 33.89 % and 66.11 % in gills and gut respectively. Gastropod shell water exhibited accumulation of 1.69 ± 1.43 MP L-1. Transparent and fibrous microplastics were documented as the dominant polymers of water, sand and sediment. Shell water exhibited the prevalence of green microplastics followed by transparent ones. Microscopic examination revealed microplastics with 100-300 µm size categories were dominant across all abiotic compartments. ATR-FTIR and Raman spectroscopy confirmed polyethylene and polypropylene as the prevalent polymers among the five identified polymers of biotic and abiotic components. The target group index indicated green and black as the preferable microplastics of crab. The ecological risk analysis indicated a considerable level of environmental pollution risk in Sundarban and its inhabiting organisms. This important information base may facilitate in developing a strategy of mitigation to limit the MP induced ecological risk at Sundarban Biosphere Reserve.

Tissue desaturation is not a major determinant of aging-related impairment in skeletal muscle reactive hyperemia: A retrospective analysis.

Near-infrared spectroscopy (NIRS) combined with vascular occlusion test (NIRS-VOT) is a reactive hyperemia technique for in vivo evaluation of skeletal muscle microvascular reactivity. Previous studies using NIRS-VOT have been shown to be able to detect impairments in microvascular function in high-risk cardiovascular disease (CVD) populations such as older individuals. It has been demonstrated that older individuals have slower reactive hyperemia compared to young individuals. Importantly, older individuals also show less desaturation during ischemia compared to young. Based on these findings, it has been suggested that the slower reactive hyperemia observed in older individuals is explained by the lower desaturation during blood flow occlusion (reduced ischemic stimulus). This retrospective analysis compared reactive hyperemia in 36 young and 47 older tissue desaturation-matched individuals that underwent 5-min blood flow occlusion. Overall, we showed that older individuals have impaired reactive hyperemia compared to young when matching for the degree of desaturation and blood flow occlusion time. These findings provide evidence that lower tissue desaturation during ischemia is not a major determinant of impaired reactive hyperemia in older individuals.

Analysis of infrared radiation emitted by moxibustion devices made of different materials using Fourier transform infrared spectroscopy.

Moxibustion has a long history of use as a traditional Chinese medicine therapy. Infrared radiation is an important and effective factor in moxibustion. Instead of the time-consuming and laborious process of holding moxa sticks in the hand, moxibustion devices are commonly used as moxibustion methods and tools in modern times. With the publication of the international standard of moxibustion devices (ISO18666:2021, Traditional Chinese Medicine - General requirements of moxibustion devices) published, moxibustion devices of various materials are now sold in the pharmacies and online stores. However, the influence of moxibustion devices on the therapeutic effect of moxibustion has not been studied. Therefore, this research was aimed to evaluate the infrared radiation of moxibustion devices, in order to select the moxibustion device that delivered infrared radiation closest to that of moxa stick combustion. The combination of combustion stability and infrared radiation intensity showed that cardboard tubes and silicone were better materials for moxibustion devices. In the mid-far infrared wave band, the moxibustion devices made from cardboard tubes and silica gels can better maintain the thermal effect generated by moxibustion and enable it to be more easily absorbed by the human body. The infrared radiation intensity of the cardboard moxibustion devices increased rapidly and steadily and could be maintained for the longest time. In conclusion, cardboard tubes are the better material for moxibustion devices with respect to infrared radiation.

Prediction of WHO grade and methylation class of aggressive meningiomas: Extraction of diagnostic information from infrared spectroscopic data.

Background: Infrared (IR) spectroscopy allows intraoperative, optical brain tumor diagnosis. Here, we explored it as a translational technology for the identification of aggressive meningioma types according to both, the WHO CNS grading system and the methylation classes (MC). Methods: Frozen sections of 47 meningioma were examined by IR spectroscopic imaging and different classification approaches were compared to discern samples according to WHO grade or MC. Results: IR spectroscopic differences were more pronounced between WHO grade 2 and 3 than between MC intermediate and MC malignant, although similar spectral ranges were affected. Aggressive types of meningioma exhibited reduced bands of carbohydrates (at 1024 cm-1) and nucleic acids (at 1080 cm-1), along with increased bands of phospholipids (at 1240 and 1450 cm-1). While linear discriminant analysis was able to discern spectra of WHO grade 2 and 3 meningiomas (AUC 0.89), it failed for MC (AUC 0.66). However, neural network classifiers were effective for classification according to both WHO grade (AUC 0.91) and MC (AUC 0.83), resulting in the correct classification of 20/23 meningiomas of the test set. Conclusions: IR spectroscopy proved capable of extracting information about the malignancy of meningiomas, not only according to the WHO grade, but also for a diagnostic system based on molecular tumor characteristics. In future clinical use, physicians could assess the goodness of the classification by considering classification probabilities and cross-measurement validation. This might enhance the overall accuracy and clinical utility, reinforcing the potential of IR spectroscopy in advancing precision medicine for meningioma characterization.

Differential effects of hypnotherapy and cognitive behavioral therapy on the default mode network of depressed patients.

Hypnosis has been applied in healing procedures since the earliest of recorded history and today it is implemented in a wholesome concept Hypnotherapy (HT1). On a neurophysiological level, hypnosis has been associated with parts of the Default Mode Network (DMN2), but its effects on this network when induced in a treatment setting of a widespread disorder, namely depression, have never been investigated. Depression is associated with abnormal functional connectivity (FC3) of the DMN. Cognitive Behavioral Therapy (CBT4) has proven itself to be an effective treatment for depression; effects of CBT on DMN-related regions are heterogeneous. In the past years, HT was found to be a promising alternative or helpful adjunction. Yet, its underlying mechanisms remain to be unclear. In this original study 75 depressed patients receiving either CBT or HT were included and measured during resting-state before and after therapy with functional near-infrared-spectroscopy (fNIRS5). On symptom level, results show a significant reduction in both groups. On a neurophysiological level, first exploratory analyses hint toward treatment effects in two components of the DMN. However, these effects do not withstand correction for multiple testing. Still, our study is a first stepstone in the investigation of neural mechanisms of HT and offers first ideas about possible implications.

Application of adaptive chaotic dung beetle optimization algorithm to near-infrared spectral model transfer.

A new transfer approach was proposed to share calibration models of the hexamethylenetetramine-acetic acid solution for studying hexamethylenetetramine concentration values across different near-infrared (NIR) spectrometers. This approach combines Savitzky-Golay first derivative (S_G_1) and orthogonal signal correction (OSC) preprocessing, along with feature variable optimization using an adaptive chaotic dung beetle optimization (ACDBO) algorithm. The ACDBO algorithm employs tent chaotic mapping and a nonlinear decreasing strategy, enhancing the balance between global and local search capabilities and increasing population diversity to address limitations observed in traditional dung beetle optimization (DBO). Validated using the CEC-2017 benchmark functions, the ACDBO algorithm demonstrated superior convergence speed, accuracy, and stability. In the context of a partial least squares (PLS) regression model for transferring hexamethylenetetramine-acetic acid solutions using NIR spectroscopy, the ACDBO algorithm excelled over alternative methods such as uninformative variable elimination, competitive adaptive reweighted sampling, cuckoo search, grey wolf optimizer, differential evolution, and DBO in efficiency, accuracy of feature variable selection, and enhancement of model predictive performance. The algorithm attained outstanding metrics, including a determination coefficient for the calibration set (Rc2) of 0.99999, a root mean square error for the calibration set (RMSEC) of 0.00195%, a determination coefficient for the validation set (Rv2) of 0.99643, a root mean squared error for the validation set (RMSEV) of 0.03818%, residual predictive deviation (RPD) of 16.72574. Compared to existing OSC, slope and bias correction (S/B), direct standardization (DS), and piecewise direct standardization (PDS) model transfer methods, the novel strategy enhances the accuracy and robustness of model predictions. It eliminates irrelevant background information about the hexamethylenetetramine concentration, thereby minimizing the spectral discrepancies across different instruments. As a result, this approach yields a determination coefficient for the prediction set (Rp2) of 0.96228, a root mean squared error for the prediction set (RMSEP) of 0.12462%, and a relative error rate (RER) of 17.62331, respectively. These figures closely follow those obtained using DS and PDS, which recorded Rp2, RMSEP, and RER values of 0.97505, 0.10135%, 21.67030, and 0.98311, 0.08339%, 26.33552, respectively. Unlike conventional methods such as OSC, S/B, DS, and PDS, this novel approach does not require the analysis of identical samples across different instruments. This characteristic significantly broadens its applicability for model transfer, which is particularly beneficial for transferring specific measurement samples.

Optical Studies of Doped Two-Dimensional Lead Halide Perovskites: Evidence for Rashba-Split Branches in the Conduction Band.

Two-dimensional (2D) hybrid organic/inorganic perovskites are an emerging materials class for optoelectronic and spintronic applications due to strong excitonic absorption and emission, large spin-orbit coupling, and Rashba spin-splitting effects. For many of the envisioned applications, tuning the majority charge carrier (electron or hole) concentration is desirable, but electronic doping of metal-halide perovskites has proven to be challenging. Here, we demonstrate electron injection into the lower-energy branch of the Rashba-split conduction band of 2D phenethylammonium lead iodide by means of n-type molecular doping at room temperature. The molecular dopant, benzyl viologen (BV), is shown to compensate adventitious p-type impurities and can lead to a tunable Fermi level above the conduction band minimum and increased conductivity in intrinsic samples. The doping-induced carrier concentration is monitored by the observation of free-carrier absorption and intraband optical transitions in the infrared spectral range. These optical measurements allow for an estimation of the Rashba splitting energy ER ≈38 ± 4 meV. Photoinduced quantum beating measurements demonstrate that the excess electron density reduces the electron spin g-factor by ca. 6%. This work demonstrates controllable carrier concentrations in hybrid organic/inorganic perovskites and yields potential for room temperature spin control through the Rashba effect.

Convolutional neural networks can detect orthostatic hypotension in Parkinson's disease using resting-state functional near-infrared spectroscopy data.

Neurological disorders such as Parkinson's disease (PD) often adversely affect the vascular system, leading to alterations in blood flow patterns. Functional near-infrared spectroscopy (fNIRS) is used to monitor hemodynamic changes via signal measurement. This study investigated the potential of using resting-state fNIRS data through a convolutional neural network (CNN) to evaluate PD with orthostatic hypotension. The CNN demonstrated significant efficacy in analyzing fNIRS data, and it outperformed the other machine learning methods. The results indicate that judicious input data selection can enhance accuracy by over 85%, while including the correlation matrix as an input further improves the accuracy to more than 90%. This study underscores the promising role of CNN-based fNIRS data analysis in the diagnosis and management of the PD. This approach enhances diagnostic accuracy, particularly in resting-state conditions, and can reduce the discomfort and risks associated with current diagnostic methods, such as the head-up tilt test.

Investigation of the Mechanical Properties of Thermoplastic Materials Influenced by Different Chemicals.

Objective: The quality of orthodontic forces in aligners is mainly influenced by their mechanical properties. At present, there is insufficient information on how environmental factors affect the mechanical function of aligners, and studies have shown that patients do not pay enough attention to removing aligners while eating and drinking. Therefore, in this study, we investigated the effect of different chemicals on the mechanical properties of thermoplastic materials. Methods: In this study, 175 thermoplastic samples from Easy-Vac gasket (3A Medes, Korea) were prepared, and their chemical composition, tensile strength, and hardness before and after exposure to solutions of orange juice, Cola, chlorhexidine mouthwash, and distilled water were measured. One-Way analysis of variance (ANOVA), Tamhane's test, and Tukey's test were used for statistical analysis. Results: The tensile strength of the sheets increased with continuous exposure to orange juice and chlorhexidine mouthwash, and their hardness decreased with continuous exposure to carbonated beverages. There was no change in the chemical composition of the samples after exposure to different chemicals. Conclusion: Although these changes are statistically significant, they do not have a significant effect on the result of aligner performance. Therefore, the only concern is the cariogenicity of orange juice and Cola during treatment with aligners and the administration of chlorhexidine mouthwash.

Concurrent behavioral modeling and multimodal neuroimaging reveals how feedback affects the performance of decision making in internet gaming disorder.

Internet gaming disorder (IGD) prompts inquiry into how feedback from prior gaming rounds influences subsequent risk-taking behavior and potential neural mechanisms. Forty-two participants, including 15 with IGD and 27 health controls (HCs), underwent a sequential risk-taking task. Hierarchy Bayesian modeling was adopted to measure risky propensity, behavioral consistence, and affection by emotion ratings from last trial. Concurrent electroencephalogram and functional near-infrared spectroscopy (EEG-fNIRS) recordings were performed to demonstrate when, where and how the previous-round feedback affects the decision making to the next round. We discovered that the IGD illustrated heightened risk-taking propensity as compared to the HCs, indicating by the computational modeling (p = 0.028). EEG results also showed significant time window differences in univariate and multivariate pattern analysis between the IGD and HCs after the loss of the game. Further, reduced brain activation in the prefrontal cortex during the task was detected in IGD as compared to that of the control group. The findings underscore the importance of understanding the aberrant decision-making processes in IGD and suggest potential implications for future interventions and treatments aimed at addressing this behavioral addiction.

Use of cortical hemodynamic responses in digital therapeutics for upper limb rehabilitation in patients with stroke.

BACKGROUND: Stroke causes long-term disabilities, highlighting the need for innovative rehabilitation strategies for reducing residual impairments. This study explored the potential of functional near-infrared spectroscopy (fNIRS) for monitoring cortical activation during rehabilitation using digital therapeutics. METHODS: This cross-sectional study included 18 patients with chronic stroke, of whom 13 were men. The mean age of the patients was 67.0 ± 7.1 years. Motor function was evaluated through various tests, including the Fugl-Meyer assessment for upper extremity (FMA-UE), grip and pinch strength test, and box and block test. All the patients completed the digital rehabilitation program (MotoCog®, Cybermedic Co., Ltd., Republic of Korea) while being monitored using fNIRS (NIRScout®, NIRx Inc., Germany). Statistical parametric mapping (SPM) was employed to analyze the cortical activation patterns from the fNIRS data. Furthermore, the K-nearest neighbor (K-NN) algorithm was used to analyze task performance and fNIRS data to classify the severity of motor impairment. RESULTS: The participants showed diverse task performances in the digital rehabilitation program, demonstrating distinct patterns of cortical activation that correlated with different motor function levels. Significant activation was observed in the ipsilesional primary motor area (M1), primary somatosensory area (S1), and contralateral prefrontal cortex. The activation patterns varied according to the FMA-UE scores. Positive correlations were observed between the FMA-UE scores and SPM t-values in the ipsilesional M1, whereas negative correlations were observed in the ipsilesional S1, frontal lobe, and parietal lobe. The incorporation of cortical hemodynamic responses with task scores in a digital rehabilitation program substantially improves the accuracy of the K-NN algorithm in classifying upper limb functional levels in patients with stroke. The accuracy for tasks, such as the gas stove-operation task, increased from 44.4% using only task scores to 83.3% when these scores were combined with oxy-Hb t-values from the ipsilesional M1. CONCLUSIONS: The results advocated the development of tailored digital rehabilitation strategies by combining the behavioral and cerebral hemodynamic data of patients with stroke. This approach aligns with the evolving paradigm of personalized rehabilitation in stroke recovery, highlighting the need for further extensive research to optimize rehabilitation outcomes.

Association between neural prosody discrimination and language abilities in toddlers: a functional near-infrared spectroscopy study.

BACKGROUND: Language delay affects near- and long-term social communication and learning in toddlers, and, an increasing number of experts pay attention to it. The development of prosody discrimination is one of the earliest stages of language development in which key skills for later stages are mastered. Therefore, analyzing the relationship between brain discrimination of speech prosody and language abilities may provide an objective basis for the diagnosis and intervention of language delay. METHODS: In this study, all cases(n = 241) were enrolled from a tertiary women's hospital, from 2021 to 2022. We used functional near-infrared spectroscopy (fNIRS) to assess children's neural prosody discrimination abilities, and a Chinese communicative development inventory (CCDI) were used to evaluate their language abilities. RESULTS: Ninety-eight full-term and 108 preterm toddlers were included in the final analysis in phase I and II studies, respectively. The total CCDI screening abnormality rate was 9.2% for full-term and 34.3% for preterm toddlers. Full-term toddlers showed prosody discrimination ability in all channels except channel 5, while preterm toddlers showed prosody discrimination ability in channel 6 only. Multifactorial logistic regression analyses showed that prosody discrimination of the right angular gyrus (channel 3) had a statistically significant effect on language delay (odd ratio = 0.301, P < 0.05) in full-term toddlers. Random forest (RF) regression model presented that prosody discrimination reflected by channels and brain regions based on fNIRS data was an important parameter for predicting language delay in preterm toddlers, among which the prosody discrimination reflected by the right angular gyrus (channel 4) was the most important parameter. The area under the model Receiver operating characteristic (ROC) curve was 0.687. CONCLUSIONS: Neural prosody discrimination ability is positively associated with language development, assessment of brain prosody discrimination abilities through fNIRS could be used as an objective indicator for early identification of children with language delay in the future clinical application.

Anisotropic Optical Response of Ti-Doped VO2 Single Crystals.

This study delves into the effects of titanium (Ti) doping on the optical properties of vanadium dioxide (VO2), a material well known for its metal-to-insulator transition (MIT) near room temperature. By incorporating Ti into VO2's crystal lattice, we aim to uncover the resultant changes in its physical properties, crucial for enhancing its application in smart devices. Utilizing polarized infrared micro-spectroscopy, we examined TixV1-xO2 single crystals with varying Ti concentrations (x = 0.059, x = 0.082, and x = 0.187) across different crystal phases (the conductive rutile phase and insulating monoclinic phases M1 and M2) from the far-infrared to the visible spectral range. Our findings reveal that Ti doping significantly influences the phononic spectra, introducing absorption peaks not attributed to pure VO2 or TiO2. This is especially notable with polarization along the crystal growth axis, mainly in the x = 0.187 sample. Furthermore, we demonstrate that the electronic contribution to optical conductivity in the metallic phase exhibits strong anisotropy, higher along the c axis than the a-b plane. This anisotropy, coupled with the progressive broadening of the zone center infrared active phonon modes with increasing doping, highlights the complex interplay between structural and electronic dynamics in doped VO2. Our results underscore the potential of Ti doping in fine-tuning VO2's electronic and thermochromic properties, paving the way for its enhanced application in optoelectronic devices and technologies.

Low Effectiveness of Mid-Infrared Spectroscopy Prediction Models of Mediterranean Italian Buffalo Bulk Milk Coagulation Traits.

This study evaluated the potential use of mid-infrared spectroscopy to predict milk coagulation traits in bulk milk from Mediterranean Italian buffaloes. A total of 1736 bulk milk samples from 55 farms in central Italy were collected during the official milk quality testing system. The prediction models were developed based on modified partial least-squares regression with 75% of the samples and validated with the remaining samples. All bulk milk samples coagulated between 7.37 and 29.45 min. Average values for milk coagulation traits in the calibration set were 17.71 min, 3.29 min, and 38.83 mm for rennet coagulation time, curd firming time, and curd firmness, respectively. The validation set included samples with similar mean and standard deviation for each trait. The prediction models showed the greatest coefficient of determination of external validation (0.57) and the ratio of prediction to deviation (1.52) for curd firmness. Similar fitting statistics of the prediction models were obtained for rennet coagulation time and curd firming time. In conclusion, the prediction models for all three coagulation traits were below the threshold to consider the prediction models adequate even for rough screening of the samples.

Intervention-Induced Changes in Balance and Task-Dependent Neural Activity in Adults with Acquired Brain Injury: A Pilot Randomized Control Trial.

Advances in neuroimaging technology, like functional near-infrared spectroscopy (fNIRS), support the evaluation of task-dependent brain activity during functional tasks, like balance, in healthy and clinical populations. To date, there have been no studies examining how interventions, like yoga, impact task-dependent brain activity in adults with chronic acquired brain injury (ABI). This pilot study compared eight weeks of group yoga (active) to group exercise (control) on balance and task-dependent neural activity outcomes. Twenty-three participants were randomized to yoga (n = 13) or exercise groups (n = 10). Neuroimaging and balance performance data were collected simultaneously using a force plate and mobile fNIRS device before and after interventions. Linear mixed-effects models were used to evaluate the effect of time, time x group interactions, and simple (i.e., within-group) effects. Regardless of group, all participants had significant balance improvements after the interventions. Additionally, regardless of group, there were significant changes in task-dependent neural activity, as well as distinct changes in neural activity within each group. In summary, using advances in sensor technology, we were able to demonstrate preliminary evidence of intervention-induced changes in balance and neural activity in adults with ABI. These preliminary results may provide an important foundation for future neurorehabilitation studies that leverage neuroimaging methods, like fNIRS.

NIR-Based Electronic Platform for Glucose Monitoring for the Prevention and Control of Diabetes Mellitus.

The glucose level in the blood is measured through invasive methods, causing discomfort in the patient, loss of sensitivity in the area where the sample is obtained, and healing problems. This article deals with the design, implementation, and evaluation of a device with an ESP-WROOM-32D microcontroller with the application of near-infrared photospectroscopy technology that uses a diode array that transmits between 830 nm and 940 nm to measure glucose levels in the blood. In addition, the system provides a webpage for the monitoring and control of diabetes mellitus for each patient; the webpage is hosted on a local Linux server with a MySQL database. The tests are conducted on 120 people with an age range of 35 to 85 years; each person undergoes two sample collections with the traditional method and two with the non-invasive method. The developed device complies with the ranges established by the American Diabetes Association: presenting a measurement error margin of close to 3% in relation to traditional blood glucose measurement devices. The purpose of the study is to design and evaluate a device that uses non-invasive technology to measure blood glucose levels. This involves constructing a non-invasive glucometer prototype that is then evaluated in a group of participants with diabetes.

Multivariate disturbance filtering in auditory fNIRS signals using maximum likelihood gradient estimation method: Feasibility study using sound quality indices.

Functional near-infrared spectroscopy (fNIRS) technology has been widely used to analyze biomechanics and diagnose brain activity. Despite being a promising tool for assessing the brain cortex status, this system is susceptible to disturbances and noise from electrical instrumentation and basal metabolism. In this study, an alternative filtering method, maximum likelihood generalized extended stochastic gradient (ML-GESG) estimation, is proposed to overcome the limitations of these disturbance factors. The proposed algorithm was designed to reduce multiple disturbances originating from heartbeats, breathing, shivering, and instrumental noises as multivariate parameters. To evaluate the effectiveness of the algorithm in filtering involuntary signals, a comparative analysis was conducted with a conventional filtering method, using hemodynamic responses to auditory stimuli and psycho-acoustic factors as quality indices. Using auditory sound stimuli consisting of 12 voice sources (six males and six females), the fNIRS test was configured with 18 channels and conducted on 10 volunteers. The psycho-acoustic factors of loudness and sharpness were used to evaluate physiological responses to the stimuli. Applying the proposed filtering method, the oxygenated hemoglobin concentration correlated better with the psychoacoustic analysis of each auditory stimulus than that of the conventional filtering method.