Differential pathlength factor in continuous wave functional near-infrared spectroscopy: reducing hemoglobin's cross talk in high-density recordings

The effects of real vs simulated high altitude on associative memory for emotional stimuli

INTRODUCTION

This study aimed to investigate the effects of normobaric hypoxia (NH) and hypobaric hypoxia (HH) on associative memory performance for emotionally valenced stimuli.

METHODS

Two experiments were conducted. In Study 1, n=18 undergraduates performed an associative memory task under three NH conditions (FiO2= 20.9%, 15.1%, 13.6%) using a tent with a hypoxic generator. In Study 2, n=20 participants were assessed in a field study at various altitudes on the Himalayan mountains, including the Pyramid Laboratory (5,000 meters above sea level), using functional Near-Infrared Spectroscopy (fNIRS) and behavioral assessments.

RESULTS

Study 1 revealed no significant differences in recognition accuracy across NH conditions. However, Study 2 showed a complex relationship between altitude and memory for emotionally valenced stimuli. At lower altitudes, participants more accurately recognized emotional stimuli compared to neutral ones, a trend that reversed at higher altitudes. Brain oxygenation varied with altitude, indicating adaptive cognitive processing, as revealed by fNIRS measurements.

CONCLUSIONS

These findings suggest that hypoxia affects associative memory and emotional processing in an altitude-dependent manner, highlighting adaptive cognitive mechanisms. Understanding the effects of hypobaric hypoxia on cognition and memory can help develop strategies to mitigate its impact in high-altitude and hypoxic environments.

Physical training improves inhibitory control in children aged 7-12 years: An fNIRS study

Physical exercise plays a crucial role in the development of cognition and brain functions in children. Inhibitory control is an advanced cognition that affects children's life and learning. In the current study, the relationship between physical training and inhibitory control was explored. In total, 80 children were randomly but equally assigned to the experimental and control groups. The experimental group underwent physical training (volleyball) for 60 min, thrice a week for 12 weeks. In contrast, the control group did not undergo any training and continued with their daily routines. The flanker task and functional near-infrared spectroscopy (fNIRS) were employed to investigate the effects of 12-week physical training on inhibitory control and changes in the oxy-Hb concentration in the prefrontal cortex (PFC) during the task. The behavioral results revealed that the experimental group performed better on the flanker task (e.g., shorter response time [F(1,74) = 18.420, p < 0.001, ηp2 = 0.199] and higher accuracy [F(1,74) = 15.00, p < 0.001, ηp2 = 0.169] than the control group. The oxy-Hb concentration in the right dorsolateral PFC (R-DLPFC) was higher and the activation level of this region was higher during the flanker task [F(1,74) = 6.216, p < 0.05, ηp2 = 0.077]. Moreover, the McNemar test revealed improved cognitive performance in response time or accuracy and R-DLPFC activation induced by physical exercise coincided significantly (χ2 = 5.49, p < 0.05; χ2 = 6.081, p < 0.05). These findings suggest that the R-DLPFC is likely the neural substrate for improved cognitive performance elicited by 12-week physical training.

A Novel Approach to Evaluating Crosstalk for Near-Infrared Spectrometers

Multi-channel and multi-parameter near-infrared spectroscopy (NIRS) has gradually become a new research direction and hot spot due to its ability to provide real-time, continuous, comprehensive indicators of multiple parameters. However, multi-channel and multi-parameter detection may lead to crosstalk between signals. There is still a lack of benchmarks for the evaluation of the reliability, sensitivity, stability and response consistency of the NIRS instruments. In this study, a set of test methods (a human blood model test, ink drop test, multi-channel crosstalk test and multi-parameter crosstalk test) for analyzing crosstalk and verifying the reliability of NIRS was conducted to test experimental verification on a multi-channel (8-channel), multi-parameter (4-parameter) NIRS instrument independently developed by our team. Results show that these tests can be used to analyze the signal crosstalk and verify the reliability, sensitivity, stability and response consistency of the NIRS instrument. This study contributes to the establishment of benchmarks for the NIRS instrument crosstalk and reliability testing. These novel tests have the potential to become the benchmark for NIRS instrument reliability testing.

Upregulation of a Small-World Brain Network Improves Inhibitory Control: An fNIRS Neurofeedback Training Study

The aim of this study was to investigate the inner link between the small-world brain network and inhibitory control. Functional near-infrared spectroscopy (fNIRS) was used to construct a neurofeedback (NF) training system and regulate the frontal small-world brain network. The small-world network downregulation group (DOWN, n = 17) and the small-world network upregulation group (UP, n = 17) received five days of fNIRS-NF training and performed the color-word Stroop task before and after training. The behavioral and functional brain network topology results of both groups were analyzed by a repeated-measures analysis of variance (ANOVA), which showed that the upregulation training helped to improve inhibitory control. The upregulated small-world brain network exhibits an increase in the brain network regularization, links widely dispersed brain resources, and reduces the lateralization of brain functional networks between hemispheres. This suggests an inherent correlation between small-world functional brain networks and inhibitory control; moreover, dynamic optimization under cost efficiency trade-offs provides a neural basis for inhibitory control. Inhibitory control is not a simple function of a single brain region or connectivity but rather an emergent property of a broader network.

Alteration in brain functional connectivity in patients with post-stroke cognitive impairment during memory task: A fNIRS study

OBJECTIVE

This study attempted to evaluate the functional connectivity (FC) in relevant cortex areas during three memory tasks using the functional near-infrared spectroscopy (fNIRS) method to expound the neural mechanisms in individuals with post-stroke cognitive impairment (PSCI).

METHODS

Short-term memory and visuospatial abilities were assessed using the clock drawing test, digit span test, and Corsi Block-tapping tests with simultaneous fNIRS. The oxygenated hemoglobin concentration signals were recorded from the bilateral motor sense cortex (LMS/RMS) and prefrontal lobe (LPFT/PFT/RPFT) of 19 subjects with cognitive impairment (PSCI group), 27 stroke subjects (STR group) and 26 healthy subjects (HC group).

RESULTS

MMSE scores were positively correlated with the clock drawing test and digit span test scores but not with Corsi Block-tapping scores. During each test, functional connectivity between the bilateral MS (LMS/RMS) was highest within each group, but the functional connectivity between motor sense cortex and frontal lobe was lowest. PSCI group showed decreased FC between bilateral motor sense cortex (P < 0.05) and between motor sense cortex and frontal lobe (P > 0.05) during clock drawing test and Corsi Block-tapping test while decreased FC between each region of interest during digit span test with no significant difference. Functional connectivity levels were closely related to MMSE scores.

CONCLUSIONS

Decreased functional connectivity level may be a marker of impaired cognitive function in post-stroke cognitive impairment. The fNIRS-based functional connectivity provides a non-invasive method to recognize cognitive impairment post-stroke. Functional connectivity changes may help to further understand the neural mechanisms of cognitive impairment post stroke.

Near-Infrared Spectroscopy for the In Vivo Monitoring of Biodegradable Implants in Rats

Magnesium (Mg) alloys possess unique properties that make them ideal for use as biodegradable implants in clinical applications. However, reports on the in vivo assessment of these alloys are insufficient. Thus, monitoring the degradation of Mg and its alloys in vivo is challenging due to the dynamic process of implant degradation and tissue regeneration. Most current works focus on structural remodeling, but functional assessment is crucial in providing information about physiological changes in tissues, which can be used as an early indicator of healing. Here, we report continuous wave near-infrared spectroscopy (CW NIRS), a non-invasive technique that is potentially helpful in assessing the implant-tissue dynamic interface in a rodent model. The purpose of this study was to investigate the effects on hemoglobin changes and tissue oxygen saturation (StO₂) after the implantation of Mg-alloy (WE43) and titanium (Ti) implants in rats' femurs using a multiwavelength optical probe. Additionally, the effect of changes in the skin on these parameters was evaluated. Lastly, combining NIRS with photoacoustic (PA) imaging provides a more reliable assessment of tissue parameters, which is further correlated with principal component analysis.

Overestimation of Oxygen Saturation Measured by Pulse Oximetry in Hypoxemia. Part 1: Effect of Optical Pathlengths-Ratio Increase

On average, arterial oxygen saturation measured by pulse oximetry (SpO₂) is higher in hypoxemia than the true oxygen saturation measured invasively (SaO₂), thereby increasing the risk of occult hypoxemia. In the current article, measurements of SpO₂ on 17 cyanotic newborns were performed by means of a Nellcor pulse oximeter (POx), based on light with two wavelengths in the red and infrared regions (660 and 900 nm), and by means of a novel POx, based on two wavelengths in the infrared region (761 and 820 nm). The SpO₂ readings from the two POxs showed higher values than the invasive SaO₂ readings, and the disparity increased with decreasing SaO₂. SpO₂ measured using the two infrared wavelengths showed better correlation with SaO₂ than SpO₂ measured using the red and infrared wavelengths. After appropriate calibration, the standard deviation of the individual SpO₂-SaO₂ differences for the two-infrared POx was smaller (3.6%) than that for the red and infrared POx (6.5%, p < 0.05). The overestimation of SpO₂ readings in hypoxemia was explained by the increase in hypoxemia of the optical pathlengths-ratio between the two wavelengths. The two-infrared POx can reduce the overestimation of SpO₂ measurement in hypoxemia and the consequent risk of occult hypoxemia, owing to its smaller increase in pathlengths-ratio in hypoxemia.

Identification of Functional Cortical Plasticity in Children with Cerebral Palsy Associated to Robotic-Assisted Gait Training: An fNIRS Study

Cerebral palsy (CP) is a non-progressive neurologic condition that causes gait limitations, spasticity, and impaired balance and coordination. Robotic-assisted gait training (RAGT) has become a common rehabilitation tool employed to improve the gait pattern of people with neurological impairments. However, few studies have demonstrated the effectiveness of RAGT in children with CP and its neurological effects through portable neuroimaging techniques, such as functional near-infrared spectroscopy (fNIRS). The aim of the study is to evaluate the neurophysiological processes elicited by RAGT in children with CP through fNIRS, which was acquired during three sessions in one month. The repeated measure ANOVA was applied to the β-values delivered by the General Linear Model (GLM) analysis used for fNIRS data analysis, showing significant differences in the activation of both prefrontal cortex (F (1.652, 6.606) = 7.638; p = 0.022), and sensorimotor cortex (F (1.294, 5.175) = 11.92; p = 0.014) during the different RAGT sessions. In addition, a cross-validated Machine Learning (ML) framework was implemented to estimate the gross motor function measure (GMFM-88) from the GLM β-values, obtaining an estimation with a correlation coefficient r = 0.78. This approach can be used to tailor clinical treatment to each child, improving the effectiveness of rehabilitation for children with CP.

Deep-learning informed Kalman filtering for priori-free and real-time hemodynamics extraction in functional near-infrared spectroscopy

Separation of the physiological interferences and the neural hemodynamics has been a vitally important task in the realistic implementation of functional near-infrared spectroscopy (fNIRS). Although many efforts have been devoted, the established solutions to this issue additionally rely on priori information on the interferences and activation responses, such as time-frequency characteristics and spatial patterns, etc., also hindering the realization of real-time. To tackle the adversity, we herein propose a novel priori-free scheme for real-time physiological interference suppression. This method combines the robustness of deep-leaning-based interference characterization and adaptivity of Kalman filtering: a long short-term memory (LSTM) network is trained with the time-courses of the absorption perturbation baseline for interferences profiling, and successively, a Kalman filtering process is applied with reference to the noise prediction for real-time activation extraction. The proposed method is validated using both simulated dynamic data and in-vivo experiments, showing the comprehensively improved performance and promisingly appended superiority achieved in the purely data-driven way.

Future Applications of Real-World Neuroimaging to Clinical Psychology

Clinical neuroimaging has largely been limited to examining the neurophysiological outcomes of treatments for psychiatric conditions rather than the neurocognitive mechanisms by which these outcomes are brought about as a function of clinical strategies, and the cognitive neuroscientific research aiming to investigate these mechanisms in nonclinical and clinical populations has been ecologically challenged by the extent to which tasks represent and generalize to intervention strategies. However, recent technological and methodological advancements to neuroimaging techniques such as functional near-infrared spectroscopy and functional near-infrared spectroscopy-based hyperscanning provide novel opportunities to investigate the mechanisms of change in more naturalistic and interactive settings, representing a unique prospect for improving our understanding of the intra- and interbrain systems supporting the recogitation of dysfunctional cognitive operations.

The Validation of a Portable Functional NIRS System for Assessing Mental Workload

Portable functional near-infrared spectroscopy (fNIRS) systems have the potential to image the brain in naturalistic settings. Experimental studies are essential to validate such fNIRS systems. Working memory (WM) is a short-term active memory that is associated with the temporary storage and manipulation of information. The prefrontal cortex (PFC) brain area is involved in the processing of WM. We assessed the PFC brain during n-back WM tasks in a group of 25 college students using our laboratory-developed portable fNIRS system, WearLight. We designed an experimental protocol with 32 n-back WM task blocks with four different pseudo-randomized task difficulty levels. The hemodynamic response of the brain was computed from the experimental data and the evaluated brain responses due to these tasks. We observed the incremental mean hemodynamic activation induced by the increasing WM load. The left-PFC area was more activated in the WM task compared to the right-PFC. The task performance was seen to be related to the hemodynamic responses. The experimental results proved the functioning of the WearLight system in cognitive load imaging. Since the portable fNIRS system was wearable and operated wirelessly, it was possible to measure the cognitive load in the naturalistic environment, which could also lead to the development of a user-friendly brain–computer interface system.

Evidence of Neurovascular Un-Coupling in Mild Alzheimer's Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data

Alzheimer’s disease (AD) is associated with modifications in cerebral blood perfusion and autoregulation. Hence, neurovascular coupling (NC) alteration could become a biomarker of the disease. NC might be assessed in clinical settings through multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Multimodal EEG-fNIRS was recorded at rest in an ambulatory setting to assess NC and to evaluate the sensitivity and specificity of the methodology to AD. Global NC was evaluated with a general linear model (GLM) framework by regressing whole-head EEG power envelopes in three frequency bands (theta, alpha and beta) with average fNIRS oxy- and deoxy-hemoglobin concentration changes in the frontal and prefrontal cortices. NC was lower in AD compared to healthy controls (HC) with significant differences in the linkage of theta and alpha bands with oxy- and deoxy-hemoglobin, respectively (p = 0.028 and p = 0.020). Importantly, standalone EEG and fNIRS metrics did not highlight differences between AD and HC. Furthermore, a multivariate data-driven analysis of NC between the three frequency bands and the two hemoglobin species delivered a cross-validated classification performance of AD and HC with an Area Under the Curve, AUC = 0.905 (p = 2.17 × 10⁻⁵). The findings demonstrate that EEG-fNIRS may indeed represent a powerful ecological tool for clinical evaluation of NC and early identification of AD.

Prediction of state anxiety by machine learning applied to photoplethysmography data

Background

As the human behavior is influenced by both cognition and emotion, affective computing plays a central role in human-machine interaction. Algorithms for emotions recognition are usually based on behavioral analysis or on physiological measurements (e.g., heart rate, blood pressure). Among these physiological signals, pulse wave propagation in the circulatory tree can be assessed through photoplethysmography (PPG), a non-invasive optical technique. Since pulse wave characteristics are influenced by the cardiovascular status, which is affected by the autonomic nervous activity and hence by the psychophysiological state, PPG might encode information about emotional conditions. The capability of a multivariate data-driven approach to estimate state anxiety (SA) of healthy participants from PPG features acquired on the brachial and radial artery was investigated.

Methods

The machine learning method was based on General Linear Model and supervised learning. PPG was measured employing a custom-made system and SA of the participants was assessed through the State-Trait Anxiety Inventory (STAI-Y) test.

Results

A leave-one-out cross-validation framework showed a good correlation between STAI-Y score and the SA predicted by the machine learning algorithm (r = 0.81; p = 1.87∙10⁻⁹). The preliminary results suggested that PPG can be a promising tool for emotions recognition, convenient for human-machine interaction applications.

Mismatch between Tissue Partial Oxygen Pressure and Near-Infrared Spectroscopy Neuromonitoring of Tissue Respiration in Acute Brain Trauma: The Rationale for Implementing a Multimodal Monitoring Strategy

The brain tissue partial oxygen pressure (PbtO₂) and near-infrared spectroscopy (NIRS) neuromonitoring are frequently compared in the management of acute moderate and severe traumatic brain injury patients; however, the relationship between their respective output parameters flows from the complex pathogenesis of tissue respiration after brain trauma. NIRS neuromonitoring overcomes certain limitations related to the heterogeneity of the pathology across the brain that cannot be adequately addressed by local-sample invasive neuromonitoring (e.g., PbtO₂ neuromonitoring, microdialysis), and it allows clinicians to assess parameters that cannot otherwise be scanned. The anatomical co-registration of an NIRS signal with axial imaging (e.g., computerized tomography scan) enhances the optical signal, which can be changed by the anatomy of the lesions and the significance of the radiological assessment. These arguments led us to conclude that rather than aiming to substitute PbtO₂ with tissue saturation, multiple types of NIRS should be included via multimodal systemic- and neuro-monitoring, whose values then are incorporated into biosignatures linked to patient status and prognosis. Discussion on the abnormalities in tissue respiration due to brain trauma and how they affect the PbtO₂ and NIRS neuromonitoring is given.

Effect of adipose tissue thickness and tissue optical properties on the differential pathlength factor estimation for NIRS studies on human skeletal muscle

We propose a quantitative and systematic investigation of the differential pathlength factor (DPF) behavior for skeletal muscles and its dependence on different factors, such as the subcutaneous adipose tissue thickness (ATT), the variations of the tissue absorption (µ_a ) and reduced scattering (µ'_s ) coefficients, and the source-detector distance. A time domain (TD) NIRS simulation study is performed in a two-layer geometry mimicking a human skeletal muscle with an overlying adipose tissue layer. The DPF decreases when µ_a increases, while it increases when µ'_s increases. Moreover, a positive correlation between DPF and ATT is found. These results are supported by an in-vivo TD NIRS study on vastus lateralis and biceps brachii muscles of eleven subjects at rest, showing a high inter-subject and inter-muscle variability.

Working Memory Decline in Alzheimer's Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS

Alzheimer's disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey-Osterrieth complex figure and Raven's progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.

Dynamic contrast-enhanced near-infrared spectroscopy using indocyanine green on moderate and severe traumatic brain injury: a prospective observational study

BACKGROUND

The care given to moderate and severe traumatic brain injury (TBI) patients may be hampered by the inability to tailor their treatments according to their neurological status. Contrast-enhanced near-infrared spectroscopy (NIRS) with indocyanine green (ICG) could be a suitable neuromonitoring tool.

METHODS

Monitoring the effective attenuation coefficients (EAC), we compared the ICG kinetics between five TBI and five extracranial trauma patients, following a venous-injection of 5 mL of 1 mg/mL ICG, using two commercially available NIRS devices.

RESULTS

A significantly slower passage of the dye through the brain of the TBI group was observed in two parameters related to the first ICG inflow into the brain (P=0.04; P=0.01). This is likely related to the reduction of cerebral perfusion following TBI. Significant changes in ICG optical properties minutes after injection (P=0.04) were registered. The acquisition of valid optical data in a clinical environment was challenging.

CONCLUSIONS

Future research should analyze abnormalities in the ICG kinetic following brain trauma, test how these values can enhance care in TBI, and adapt the current optical devices to clinical settings. Also, studies on the pattern in changes of ICG optical properties after venous injection can improve the accuracy of the values detected.

Recent Developments in Instrumentation of Functional Near-Infrared Spectroscopy Systems

In the last three decades, the development and steady improvement of various optical technologies at the near-infrared region of the electromagnetic spectrum has inspired a large number of scientists around the world to design and develop functional near-infrared spectroscopy (fNIRS) systems for various medical applications. This has been driven further by the availability of new sources and detectors that support very compact and wearable system designs. In this article, we review fNIRS systems from the instrumentation point of view, discussing the associated challenges and state-of-the-art approaches. In the beginning, the fundamentals of fNIRS systems as well as light-tissue interaction at NIR are briefly introduced. After that, we present the basics of NIR systems instrumentation. Next, the recent development of continuous-wave, frequency-domain, and time-domain fNIRS systems are discussed. Finally, we provide a summary of these three modalities and an outlook into the future of fNIRS technology.

Tomographic Task-Related Functional Near-Infrared Spectroscopy in Acute Sport-Related Concussion: An Observational Case Study

Making decisions regarding return-to-play after sport-related concussion (SRC) based on resolution of symptoms alone can expose contact-sport athletes to further injury before their recovery is complete. Task-related functional near-infrared spectroscopy (fNIRS) could be used to scan for abnormalities in the brain activation patterns of SRC athletes and help clinicians to manage their return-to-play. This study aims to show a proof of concept of mapping brain activation, using tomographic task-related fNIRS, as part of the clinical assessment of acute SRC patients. A high-density frequency-domain optical device was used to scan 2 SRC patients, within 72 h from injury, during the execution of 3 neurocognitive tests used in clinical practice. The optical data were resolved into a tomographic reconstruction of the brain functional activation pattern, using diffuse optical tomography. Moreover, brain activity was inferred using single-subject statistical analyses. The advantages and limitations of the introduction of this optical technique into the clinical assessment of acute SRC patients are discussed.

Towards a Portable Platform Integrated With Multispectral Noncontact Probes for Delineating Normal and Breast Cancer Tissue Based on Near-Infrared Spectroscopy

Currently, the confirmation of diagnosis of breast cancer is made by microscopic examination of an ultra-thin slice of a needle biopsy specimen. This slice is conventionally formalin-fixed and stained with hematoxylin-eosin and visually examined under a light microscope. This process is labor-intensive and requires highly skilled doctors (pathologists). In this paper, we report a novel tool based on near-infrared spectroscopy (Spectral-IRDx) which is a portable, non-contact, and cost-effective system and could provide a rapid and accurate diagnosis of cancer. The Spectral-IRDx tool performs absorption spectroscopy at near-infrared (NIR) wavelengths of 850, 935, and 1060 nm. We measure normalized detected voltage (V_dn) with the tool in 10 deparaffinized breast biopsy tissue samples, 5 of which were cancer (C) and 5 were normal (N) tissues. The difference in V_dn at 935 nm and 1060 nm between cancer and normal tissues is statistically significant with p-values of 0.0038 and 0.0022 respectively. Absorption contrast factor (N/C) of 1.303, 1.551, and 1.45 are observed for 850, 935, and 1060 nm respectively. The volume fraction contrast (N/C) of lipids and collagens are reported as 1.28 and 1.10 respectively. Higher absorption contrast factor (N/C) and volume fraction contrast (N/C) signifies higher concentration of lipids in normal tissues as compared to cancerous tissues, a basis for delineation. These preliminary results support the envisioned concept for noninvasive and noncarcinogenic NIR-based breast cancer diagnostic platform, which will be tested using a larger number of samples.

Fiberless, Multi-Channel fNIRS-EEG System Based on Silicon Photomultipliers: Towards Sensitive and Ecological Mapping of Brain Activity and Neurovascular Coupling

Portable neuroimaging technologies can be employed for long-term monitoring of neurophysiological and neuropathological states. Functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are highly suited for such a purpose. Their multimodal integration allows the evaluation of hemodynamic and electrical brain activity together with neurovascular coupling. An innovative fNIRS-EEG system is here presented. The system integrated a novel continuous-wave fNIRS component and a modified commercial EEG device. fNIRS probing relied on fiberless technology based on light emitting diodes and silicon photomultipliers (SiPMs). SiPMs are sensitive semiconductor detectors, whose large detection area maximizes photon harvesting from the scalp and overcomes limitations of fiberless technology. To optimize the signal-to-noise ratio and avoid fNIRS-EEG interference, a digital lock-in was implemented for fNIRS signal acquisition. A benchtop characterization of the fNIRS component showed its high performances with a noise equivalent power below 1 pW. Moreover, the fNIRS-EEG device was tested in vivo during tasks stimulating visual, motor and pre-frontal cortices. Finally, the capabilities to perform ecological recordings were assessed in clinical settings on one Alzheimer's Disease patient during long-lasting cognitive tests. The system can pave the way to portable technologies for accurate evaluation of multimodal brain activity, allowing their extensive employment in ecological environments and clinical practice.

Multi-Site Photoplethysmographic and Electrocardiographic System for Arterial Stiffness and Cardiovascular Status Assessment

The development and validation of a system for multi-site photoplethysmography (PPG) and electrocardiography (ECG) is presented. The system could acquire signals from 8 PPG probes and 10 ECG leads. Each PPG probe was constituted of a light-emitting diode (LED) source at a wavelength of 940 nm and a silicon photomultiplier (SiPM) detector, located in a back-reflection recording configuration. In order to ensure proper optode-to-skin coupling, the probe was equipped with insufflating cuffs. The high number of PPG probes allowed us to simultaneously acquire signals from multiple body locations. The ECG provided a reference for single-pulse PPG evaluation and averaging, allowing the extraction of indices of cardiovascular status with a high signal-to-noise ratio. Firstly, the system was characterized on optical phantoms. Furthermore, in vivo validation was performed by estimating the brachial-ankle pulse wave velocity (baPWV), a metric associated with cardiovascular status. The validation was performed on healthy volunteers to assess the baPWV intra- and extra-operator repeatability and its association with age. Finally, the baPWV, evaluated via the developed instrumentation, was compared to that estimated with a commercial system used in clinical practice (Enverdis Vascular Explorer). The validation demonstrated the system's reliability and its effectiveness in assessing the cardiovascular status in arterial ageing.