Pulsatile microvascular cerebral blood flow waveforms change with intracranial compliance and age.

Significance: Diffuse correlation spectroscopy (DCS) is an optical method to measure relative changes in cerebral blood flow (rCBF) in the microvasculature. Each heartbeat generates a pulsatile signal with distinct morphological features that we hypothesized to be related to intracranial compliance (ICC). Aim: We aim to study how three features of the pulsatile rCBF waveforms: the augmentation index (AIx), the pulsatility index, and the area under the curve, change with respect to ICC. We describe ICC as a combination of vascular compliance and extravascular compliance. Approach: Since patients with Chiari malformations (CM) (n=30) have been shown to have altered extravascular compliance, we compare the morphology of rCBF waveforms in CM patients with age-matched healthy control (n=30). Results: AIx measured in the supine position was significantly less in patients with CM compared to healthy controls (p<0.05). Since physiologic aging also leads to changes in vessel stiffness and intravascular compliance, we evaluate how the rCBF waveform changes with respect to age and find that the AIx feature was strongly correlated with age (Rhealthy subjects=-0.63, Rpreoperative CM patient=-0.70, and Rpostoperative CM patients=-0.62, p<0.01). Conclusions: These results suggest that the AIx measured in the cerebral microvasculature using DCS may be correlated to changes in ICC.

Scaling of Algorithmic Bias in Pulse Oximetry with Signal-to-Noise Ratio.

Recent work has noted a skin-color bias in existing pulse oximetry systems in their estimation of arterial oxygen saturation. Frequently, the algorithm used by these systems estimate a "ratio-of-ratios", called the "R-value", on their way to estimating the oxygen saturation. In this work, we focus on an "SNR-related" bias that is due to noise in measurements. We derive expressions for the SNR-related bias in R-value estimation, and observe how it scales with the signal-to-noise ratio (SNR). We show that the bias can arise at two steps of R-value estimation: in estimating the max and min of a pulsatile signal, and, additionally in taking ratios to estimate the R-value. We assess the bias resulting from the combination of the two steps, but also separate out contributions of each step. By doing so, we deduce that the bias induced in max and min estimation is likely to dominate. Because the SNR tends to get worse with higher melanin concentration, our result provides a sense of scaling of this bias with melanin concentration.

Self-calibrated pulse oximetry algorithm based on photon pathlength change and the application in human freedivers.

Significance: Pulse oximetry estimates the arterial oxygen saturation of hemoglobin (SaO2) based on relative changes in light intensity at the cardiac frequency. Commercial pulse oximeters require empirical calibration on healthy volunteers, resulting in limited accuracy at low oxygen levels. An accurate, self-calibrated method for estimating SaO2 is needed to improve patient monitoring and diagnosis. Aim: Given the challenges of calibration at low SaO2 levels, we pursued the creation of a self-calibrated algorithm that can effectively estimate SaO2 across its full range. Our primary objective was to design and validate our calibration-free method using data collected from human subjects. Approach: We developed an algorithm based on diffuse optical spectroscopy measurements of cardiac pulses and the modified Beer-Lambert law (mBLL). Recognizing that the photon mean pathlength (⟨L⟩) varies with SaO2 related absorption changes, our algorithm aligns/fits the normalized ⟨L⟩ (across wavelengths) obtained from optical measurements with its analytical representation. We tested the algorithm with human freedivers performing breath-hold dives. A continuous-wave near-infrared spectroscopy probe was attached to their foreheads, and an arterial cannula was inserted in the radial artery to collect arterial blood samples at different stages of the dive. These samples provided ground-truth SaO2 via a blood gas analyzer, enabling us to evaluate the accuracy of SaO2 estimation derived from the NIRS measurement using our self-calibrated algorithm. Results: The self-calibrated algorithm significantly outperformed the conventional method (mBLL with a constant ⟨L⟩ ratio) for SaO2 estimation through the diving period. Analyzing 23 ground-truth SaO2 data points ranging from 41% to 100%, the average absolute difference between the estimated SaO2 and the ground truth SaO2 is 4.23%±5.16% for our algorithm, significantly lower than the 11.25%±13.74% observed with the conventional approach. Conclusions: By factoring in the variations in the spectral shape of ⟨L⟩ relative to SaO2, our self-calibrated algorithm enables accurate SaO2 estimation, even in subjects with low SaO2 levels.

A model of neurovascular coupling and its application to cortical spreading depolarization.

Cortical spreading depolarization (CSD) is a neuropathological condition involving propagating waves of neuronal silence, and is related to multiple diseases, such as migraine aura, traumatic brain injury (TBI), stroke, and cardiac arrest, as well as poor outcome of patients. While CSDs of different severity share similar roots on the ion exchange level, they can lead to different vascular responses (namely spreading hyperemia and spreading ischemia). In this paper, we propose a mathematical model relating neuronal activities to predict vascular changes as measured with near-infrared spectroscopy (NIRS) and fMRI recordings, and apply it to the extreme case of CSD, where sustained near-complete neuronal depolarization is seen. We utilize three serially connected models (namely, ion exchange, neurovascular coupling, and hemodynamic model) which are described by differential equations. Propagating waves of ion concentrations, as well as the associated vasodynamics and hemodynamics, are simulated by solving these equations. Our proposed model predicts vasodynamics and hemodynamics that agree both qualitatively and quantitatively with experimental literature. Mathematical modeling and simulation offer a powerful tool to help understand the underlying mechanisms of CSD and help interpret the data. In addition, it helps develop novel monitoring techniques prior to data collection. Our simulated results strongly suggest that fMRI is unable to reliably distinguish between spreading hyperemia and spreading ischemia, while NIRS signals are substantially distinct in the two cases.

Evaluating feasibility of functional near-infrared spectroscopy in dolphins.

Significance: Using functional near-infrared spectroscopy (fNIRS) in bottlenose dolphins (Tursiops truncatus) could help to understand how echolocating animals perceive their environment and how they focus on specific auditory objects, such as fish, in noisy marine settings. Aim: To test the feasibility of near-infrared spectroscopy (NIRS) in medium-sized marine mammals, such as dolphins, we modeled the light propagation with computational tools to determine the wavelengths, optode locations, and separation distances that maximize sensitivity to brain tissue. Approach: Using frequency-domain NIRS, we measured the absorption and reduced scattering coefficient of dolphin sculp. We assigned muscle, bone, and brain optical properties from the literature and modeled light propagation in a spatially accurate and biologically relevant model of a dolphin head, using finite-element modeling. We assessed tissue sensitivities for a range of wavelengths (600 to 1700 nm), source-detector distances (50 to 120 mm), and animal sizes (juvenile model 25% smaller than adult). Results: We found that the wavelengths most suitable for imaging the brain fell into two ranges: 700 to 900 nm and 1100 to 1150 nm. The optimal location for brain sensing positioned the center point between source and detector 30 to 50 mm caudal of the blowhole and at an angle 45 deg to 90 deg lateral off the midsagittal plane. Brain tissue sensitivity comparable to human measurements appears achievable only for smaller animals, such as juvenile bottlenose dolphins or smaller species of cetaceans, such as porpoises, or with source-detector separations ≫100 mm in adult dolphins. Conclusions: Brain measurements in juvenile or subadult dolphins, or smaller dolphin species, may be possible using specialized fNIRS devices that support optode separations of >100 mm. We speculate that many measurement repetitions will be required to overcome hemodynamic signals originating predominantly from the muscle layer above the skull. NIRS measurements of muscle tissue are feasible today with source-detector separations of 50 mm, or even less.

Diffuse optical tomography spatial prior for EEG source localization in human visual cortex.

Electroencephalography (EEG) and diffuse optical tomography (DOT) are imaging methods which are widely used for neuroimaging. While the temporal resolution of EEG is high, the spatial resolution is typically limited. DOT, on the other hand, has high spatial resolution, but the temporal resolution is inherently limited by the slow hemodynamics it measures. In our previous work, we showed using computer simulations that when using the results of DOT reconstruction as the spatial prior for EEG source reconstruction, high spatio-temporal resolution could be achieved. In this work, we experimentally validate the algorithm by alternatingly flashing two visual stimuli at a speed that is faster than the temporal resolution of DOT. We show that the joint reconstruction using both EEG and DOT clearly resolves the two stimuli temporally, and the spatial confinement is drastically improved in comparison to reconstruction using EEG alone.

Cerebrovascular Impedance as a Function of Cerebral Perfusion Pressure.

Goal: Cerebrovascular impedance is modulated by a vasoactive autoregulative mechanism in response to changes in cerebral perfusion pressure. Characterization of impedance and the limits of autoregulation are important biomarkers of cerebral health. We developed a method to quantify impedance based on the spectral content of cerebral blood flow and volume at the cardiac frequency, measured with diffuse optical methods. Methods: In three non-human primates, we modulated cerebral perfusion pressure beyond the limits of autoregulation. Cerebral blood flow and volume were measured with diffuse correlation spectroscopy and near-infrared spectroscopy, respectively. Results: We show that impedance can be used to identify the lower and upper limits of autoregulation. Conclusions: This impedance method may be an alternative method to measure autoregulation and a way of assessing cerebral health non-invasively at the clinical bedside.

Clinical translation of noninvasive intracranial pressure sensing with diffuse correlation spectroscopy.

OBJECTIVE: Intracranial pressure (ICP) is an important therapeutic target in many critical neuropathologies. The current tools for ICP measurements are invasive; hence, these are only selectively applied in critical cases where the benefits surpass the risks. To address the need for low-risk ICP monitoring, the authors developed a noninvasive alternative. METHODS: The authors recently demonstrated noninvasive quantification of ICP in an animal model by using morphological analysis of microvascular cerebral blood flow (CBF) measured with diffuse correlation spectroscopy (DCS). The current prospective observational study expanded on this preclinical study by translating the method to pediatric patients. Here, the CBF features, along with mean arterial pressure (MAP) and heart rate (HR) data, were used to build a random decision forest, machine learning model for estimation of ICP; the results of this model were compared with those of invasive monitoring. RESULTS: Fifteen patients (mean age ± SD [range] 9.8 ± 5.1 [0.3-17.5] years; median age [interquartile range] 11 [7.4] years; 10 males and 5 females) who underwent invasive neuromonitoring for any purpose were enrolled. Estimated ICP (ICPest) very closely matched invasive ICP (ICPinv), with a root mean square error (RMSE) of 1.01 mm Hg and 95% limit of agreement of ≤ 1.99 mm Hg for ICPinv 0.01-41.25 mm Hg. When the ICP range (ICPinv 0.01-29.05 mm Hg) was narrowed on the basis of the sample population, both RMSE and limit of agreement improved to 0.81 mm Hg and ≤ 1.6 mm Hg, respectively. In addition, 0.3% of the test samples for ICPinv ≤ 20 mm Hg and 5.4% of the test samples for ICPinv > 20 mm Hg had a limit of agreement > 5 mm Hg, which may be considered the acceptable limit of agreement for clinical validity of ICP sensing. For the narrower case, 0.1% of test samples for ICPinv ≤ 20 mm Hg and 1.1% of the test samples for ICPinv > 20 mm Hg had a limit of agreement > 5 mm Hg. Although the CBF features were crucial, the best prediction accuracy was achieved when these features were combined with MAP and HR data. Lastly, preliminary leave-one-out analysis showed model accuracy with an RMSE of 6 mm Hg and limit of agreement of ≤ 7 mm Hg. CONCLUSIONS: The authors have shown that DCS may enable ICP monitoring with additional clinical validation. The lower risk of such monitoring would allow ICP to be estimated for a wide spectrum of indications, thereby both reducing the use of invasive monitors and increasing the types of patients who may benefit from ICP-directed therapies.

Cerebrovascular impedance estimation with near-infrared and diffuse correlation spectroscopy.

Significance: Cerebrovascular impedance (CVI) is related to cerebral autoregulation (CA), which is the mechanism of the brain to maintain near-constant cerebral blood flow (CBF) despite changes in cerebral perfusion pressure (CPP). Changes in blood vessel impedance enable the stabilization of blood flow. Due to the interplay between CVI and CA, assessment of CVI may enable quantification of CA and may serve as a biomarker for cerebral health. Aim: We developed a method to quantify CVI based on a combination of diffuse correlation spectroscopy (DCS) and continuous wave (CW) near-infrared spectroscopy (NIRS). Data on healthy human volunteers were used to validate the method. Approach: A combined high-speed DCS-NIRS system was developed, allowing for simultaneous, noninvasive blood flow, and volume measurements in the same tissue compartment. Blood volume was used as a surrogate measurement for blood pressure and CVI was calculated as the spectral ratio of blood volume and blood flow changes. This technique was validated on six healthy human volunteers undergoing postural changes to elicit CVI changes. Results: Averaged across the six subjects, a decrease in CVI was found for a head of bed (HOB) tilting of - 40 deg . These impedance changes were reversed when returning to the horizontal (0 deg) HOB baseline. Conclusions: We developed a combined DCS-NIRS system, which measures CBF and volume changes, which we demonstrate can be used to measure CVI. Using CVI as a metric of CA may be beneficial for assessing cerebral health, especially in patients where CPP is altered.

In situvolumetric imaging and analysis of FRESH 3D bioprinted constructs using optical coherence tomography.

As 3D bioprinting has grown as a fabrication technology, so too has the need for improved analytical methods to characterize engineered constructs. This is especially challenging for engineered tissues composed of hydrogels and cells, as these materials readily deform when trying to assess print fidelity and other properties non-destructively. Establishing that the 3D architecture of the bioprinted construct matches its intended anatomic design is critical given the importance of structure-function relationships in most tissue types. Here we report development of a multimaterial bioprinting platform with integrated optical coherence tomography forin situvolumetric imaging, error detection, and 3D reconstruction. We also report improvements to the freeform reversible embedding of suspended hydrogels bioprinting process through new collagen bioink compositions, gelatin microparticle support bath optical clearing, and optimized machine pathing. This enables quantitative 3D volumetric imaging with micron resolution over centimeter length scales, the ability to detect a range of print defect types within a 3D volume, and real-time imaging of the printing process at each print layer. These advances provide a comprehensive methodology for print quality assessment, paving the way toward the production and process control required for achieving regulatory approval and ultimately clinical translation of engineered tissues.

Using near-infrared spectroscopy and a random forest regressor to estimate intracranial pressure.

Significance: Intracranial pressure (ICP) measurements are important for patient treatment but are invasive and prone to complications. Noninvasive ICP monitoring methods exist, but they suffer from poor accuracy, lack of generalizability, or high cost. Aim: We previously showed that cerebral blood flow (CBF) cardiac waveforms measured with diffuse correlation spectroscopy can be used for noninvasive ICP monitoring. Here we extend the approach to cardiac waveforms measured with near-infrared spectroscopy (NIRS). Approach: Changes in hemoglobin concentrations were measured in eight nonhuman primates, in addition to invasive ICP, arterial blood pressure, and CBF changes. Features of average cardiac waveforms in hemoglobin and CBF signals were used to train a random forest (RF) regressor. Results: The RF regressor achieves a cross-validated ICP estimation of 0.937 r 2 , 2.703 - mm Hg 2 mean squared error (MSE), and 95% confidence interval (CI) of [ - 3.064 3.160 ] mmHg on oxyhemoglobin concentration changes; 0.946 r 2 , 2.301 - mmHg 2 MSE, and 95% CI of [ - 2.841 2.866 ] mmHg on total hemoglobin concentration changes; and 0.963 r 2 , 1.688 mmHg 2 MSE, and 95% CI of [ - 2.450 2.397 ] mmHg on CBF changes. Conclusions: This study provides a proof of concept for the use of NIRS in noninvasive ICP estimation.

Optical imaging and spectroscopy for the study of the human brain: status report.

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy.

Diffuse correlation spectroscopy (DCS) has been widely explored for its ability to measure cerebral blood flow (CBF), however, mostly under the assumption that the human head is homogenous. In addition to CBF, knowledge of extracerebral layers, such as skull thickness, can be informative and crucial for patient with brain complications such as traumatic brain injuries. To bridge the gap, this study explored the feasibility of simultaneously extracting skull thickness and flow in the cortex layer using DCS. We validated a two-layer analytical model that assumed the skull as top layer with a finite thickness and the brain cortex as bottom layer with semi-infinite geometry. The model fitted for thickness of the top layer and flow of the bottom layer, while assumed other parameters as constant. The accuracy of the two-layer model was tested against the conventional single-layer model using measurements from custom made two-layer phantoms mimicking skull and brain. We found that the fitted top layer thickness at each source detector (SD) distance is correlated with the expected thickness. For the fitted bottom layer flow, the two-layer model fits relatively consistent flow across all top layer thicknesses. In comparison, the conventional one-layer model increasingly underestimates the bottom layer flow as top layer thickness increases. The overall accuracy of estimating first layer thickness and flow depends on the SD distance in relationship to first layer thickness. Lastly, we quantified the influence of uncertainties in the optical properties of each layer. We found that uncertainties in the optical properties only mildly influence the fitted thickness and flow. In this work we demonstrate the feasibility of simultaneously extracting of layer thickness and flow using a two-layer DCS model. Findings from this work may introduce a robust and cost-effective approach towards simultaneous bedside assessment of skull thickness and cerebral blood flow.

Non-Invasive Spectroscopy for Measuring Cerebral Tissue Oxygenation and Metabolism as a Function of Cerebral Perfusion Pressure.

Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) measure cerebral hemodynamics, which in turn can be used to assess the cerebral metabolic rate of oxygen (CMRO2) and cerebral autoregulation (CA). However, current mathematical models for CMRO2 estimation make assumptions that break down for cerebral perfusion pressure (CPP)-induced changes in CA. Here, we performed preclinical experiments with controlled changes in CPP while simultaneously measuring NIRS and DCS at rest. We observed changes in arterial oxygen saturation (~10%) and arterial blood volume (~50%) with CPP, two variables often assumed to be constant in CMRO2 estimations. Hence, we propose a general mathematical model that accounts for these variations when estimating CMRO2 and validate its use for CA monitoring on our experimental data. We observed significant changes in the various oxygenation parameters, including the coupling ratio (CMRO2/blood flow) between regions of autoregulation and dysregulation. Our work provides an appropriate model and preliminary experimental evidence for the use of NIRS- and DCS-based tissue oxygenation and metabolism metrics for non-invasive diagnosis of CA health in CPP-altering neuropathologies.

Erratum: Estimating intracranial pressure using pulsatile cerebral blood flow measured with diffuse correlation spectroscopy: erratum.

[This corrects the article on p. 1462 in vol. 11, PMID: 32206422.].

Review of optical methods for fetal monitoring in utero.

The current technology for monitoring fetal wellbeing during child birth is cardiotocography. However, CTG has high false positive rates that lead to unnecessary emergency Cesarean deliveries and false negatives that result in birth injuries. To curtail these issues, fetal pulse oximetery has been a topic of interest for many decades. Fetal pulse oximetry would yield the oxygen saturation of the fetus in utero and provide a more robust marker for clinicians to make decisions about performing emergency Cesarean deliveries. Here, we present a review of biomedical optical developments related to transabdominal fetal pulse oximetery in the biophotonics field and the challenges that must be overcome to make transabdominal pulse oximetry a clinical reality.

Changes in neurovascular coupling with cerebral perfusion pressure indicate a link to cerebral autoregulation.

Cerebral autoregulation ensures a stable average blood supply to brain tissue across steady state cerebral perfusion pressure (CPP) levels. Neurovascular coupling, in turn, relies on sufficient blood flow to meet neuronal demands during activation. These mechanisms break down in pathologies where extreme levels of CPP can cause dysregulation in cerebral blood flow. Here, we experimentally tested the influence of changes in CPP on neurovascular coupling in a hydrocephalus-type non-human primate model (n = 3). We recorded local neural and vascular evoked responses to a checkerboard visual stimulus, non-invasively, using electroencephalography and near-infrared spectroscopy respectively. The evoked signals showed changes in various waveform features in the visual evoked potentials and the hemodynamic responses, with CPP. We further used these signals to fit for a hemodynamic response function (HRF) to describe neurovascular coupling. We estimated n = 26 distinct HRFs at a subset of CPP values ranging from 40-120 mmHg across all subjects. The HRFs, when compared to a subject dependent healthy baseline (CPP 70-90 mmHg) HRF, showed significant changes in shape with increasing CPP (ρCPP = -0.55, p-valueCPP = 0.0049). Our study provides preliminary experimental evidence on the relationship between neurovascular coupling and CPP changes, especially when beyond the limits of static autoregulation.

Review of studies on dynamic cerebral autoregulation in the acute phase of stroke and the relationship with clinical outcome.

Acute stroke is associated with high morbidity and mortality. In the last decades, new therapies have been investigated with the aim of improving clinical outcomes in the acute phase post stroke onset. However, despite such advances, a large number of patients do not demonstrate improvement, furthermore, some unfortunately deteriorate. Thus, there is a need for additional treatments targeted to the individual patient. A potential therapeutic target is interventions to optimize cerebral perfusion guided by cerebral hemodynamic parameters such as dynamic cerebral autoregulation (dCA). This narrative led to the development of the INFOMATAS (Identifying New targets FOr Management And Therapy in Acute Stroke) project, designed to foster interventions directed towards understanding and improving hemodynamic aspects of the cerebral circulation in acute cerebrovascular disease states. This comprehensive review aims to summarize relevant studies on assessing dCA in patients suffering acute ischemic stroke, intracerebral haemorrhage, and subarachnoid haemorrhage. The review will provide to the reader the most consistent findings, the inconsistent findings which still need to be explored further and discuss the main limitations of these studies. This will allow for the creation of a research agenda for the use of bedside dCA information for prognostication and targeted perfusion interventions.

Shining new light on sensory brain activation and physiological measurement in seals using wearable optical technology.

Sensory ecology and physiology of free-ranging animals is challenging to study but underpins our understanding of decision-making in the wild. Existing non-invasive human biomedical technology offers tools that could be harnessed to address these challenges. Functional near-infrared spectroscopy (fNIRS), a wearable, non-invasive biomedical imaging technique measures oxy- and deoxyhaemoglobin concentration changes that can be used to detect localized neural activation in the brain. We tested the efficacy of fNIRS to detect cortical activation in grey seals (Halichoerus grypus) and identify regions of the cortex associated with different senses (vision, hearing and touch). The activation of specific cerebral areas in seals was detected by fNIRS in responses to light (vision), sound (hearing) and whisker stimulation (touch). Physiological parameters, including heart and breathing rate, were also extracted from the fNIRS signal, which allowed neural and physiological responses to be monitored simultaneously. This is, to our knowledge, the first time fNIRS has been used to detect cortical activation in a non-domesticated or laboratory animal. Because fNIRS is non-invasive and wearable, this study demonstrates its potential as a tool to quantitatively investigate sensory perception and brain function while simultaneously recording heart rate, tissue and arterial oxygen saturation of haemoglobin, perfusion changes and breathing rate in free-ranging animals. This article is part of the theme issue 'Measuring physiology in free-living animals (Part I)'.

When the human brain goes diving: using near-infrared spectroscopy to measure cerebral and systemic cardiovascular responses to deep, breath-hold diving in elite freedivers.

Continuous measurements of haemodynamic and oxygenation changes in free living animals remain elusive. However, developments in biomedical technologies may help to fill this knowledge gap. One such technology is continuous-wave near-infrared spectroscopy (CW-NIRS)-a wearable and non-invasive optical technology. Here, we develop a marinized CW-NIRS system and deploy it on elite competition freedivers to test its capacity to function during deep freediving to 107 m depth. We use the oxyhaemoglobin and deoxyhaemoglobin concentration changes measured with CW-NIRS to monitor cerebral haemodynamic changes and oxygenation, arterial saturation and heart rate. Furthermore, using concentration changes in oxyhaemoglobin engendered by cardiac pulsation, we demonstrate the ability to conduct additional feature exploration of cardiac-dependent haemodynamic changes. Freedivers showed cerebral haemodynamic changes characteristic of apnoeic diving, while some divers also showed considerable elevations in venous blood volumes close to the end of diving. Some freedivers also showed pronounced arterial deoxygenation, the most extreme of which resulted in an arterial saturation of 25%. Freedivers also displayed heart rate changes that were comparable to diving mammals both in magnitude and patterns of change. Finally, changes in cardiac waveform associated with heart rates less than 40 bpm were associated with changes indicative of a reduction in vascular compliance. The success here of CW-NIRS to non-invasively measure a suite of physiological phenomenon in a deep-diving mammal highlights its efficacy as a future physiological monitoring tool for human freedivers as well as free living animals. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.