Abstract

In addition to supplying oxygen molecule O2 for metabolic functions during the adaptation to exercise, blood also plays a critical role in heat dissipation for core temperature stabilization. This study investigates the status of hemodynamic oxygenation in the forearm’s skin tissue of three participants during a complete ergometer exercise from the resting to exercising, and to recovering conditions using a three-wavelength frequency-domain diffuse reflectance spectroscopy (FD DRS) alongside the monitoring of heartbeat rate and skin temperature. The FD DRS system was synchronized with radiofrequency (RF)-modulated input photon sources and the respective output to extract time-course absorption and scattering coefficients of the skin tissue, which, through the fitting of lambert’s law of absorbance, can be used to determine the concentration of oxygenated/deoxygenated hemoglobin molecules, and consequentially, the oxygen saturation of skin tissue and total hemoglobin (THb) concentration. Expressly, a sudden jump in heartbeat rate at the beginning of the exercise, a temporal lag of the rising edge of skin temperature behind that of the THb concentration in the procession of step-wise incremental working intensity, and the uprising of THb in the exhaustion zone in responses to the physiological adaptation to exercise were identified. Finally, conclusive remarks were drawn that the FD DRS system is useful in extracting the hemodynamic properties of forearm skin which is often being neglected in previous exercise physiology studies by DRS-related techniques. The detailed variation of hemodynamic and optical scattering parameters of forearm skin elucidated in the studies can be applied for the analysis of athletes’ physiological status, and may be a potential reference for the design of future wearable devices.

© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

Tissue oxygenation plays a critical role in facilitating oxidative phosphorylation in mitochondrial cytochrome that produces ATPs for synthesizing protein and enabling cellular function in mammalian organ [1]. To carry out tissue oxygenation, the flow of blood cells encapsulated with oxygen (O2)-binding hemoglobin proteins pick up O2 upon alveolar diffusion and release it at local organo-tissue via reduction-oxidation reactions. Particularly in the adaptation to many physiological circumstances such as knee-extensor exercising under hypoxia/hyperoxia [2], wound healing [3], extreme cold and heat [4], surgery [5] as well as many organo-functions [6], a dynamic balance between the O2 supply (QO2) and consumption (VO2) in biological tissues was absolutely necessary to accommodate the metabolic needs and functional activities. Given the cycling exercise as an example, a number of factors including the work intensity, level of training and activating degree of muscle groups can impact the oxygenation status during an exercise [7,8], and the condition of oxygenation varies throughout the entire period of the exercise. These prior studies were mostly conducted on muscle tissues. Skin tissue, on the other front, is human’s outermost layer serving not only as a protection barrier against external impacts, but also as a thermal regulator that competes with working tissues, the leg muscle in the case of cycling exercise, for blood flows from the cardiac output [9]. Such heat-dissipating function of thermo-regulatory drive during the process of exercise is greatly dependent on the physical fitness and age of individuals upon blood re-distribution from splanchnic and renal circulations [10]. Comparing to the sedate condition, physical exercise can make profound increase in the concentration of oxy-hemoglobin and deoxy-hemoglobin of forearm skin tissue by about 1.5 fold [11], and elevate the body core temperature (Tc), which sets the threshold for an increase in heat-dissipating skin blood flow, by at least 0.2 °C [12]. Thus, evidently, the skin tissue measurement for quantification of hemodynamic properties in situ including oxy-hemoglobin, deoxy-hemoglobin, and total hemoglobin (THb) is of pivotal importance for monitoring the physiological condition of cyclists in correlation with the cutaneous heat-dissipation function.

Photon within the range of near-infrared (NIR) wavelength from 650 nm to 900 nm provide an optimal spectral window for functional imaging on the basis of its low optical scattering and water absorption, and high penetration into biological tissues [13]. This spectral window is also highly absorptive to several important molecular entities like intravascular hemoglobin, intramusclular hemoglobin (Mb), skin melanin and mitochondrial cytochrome c oxidase [14]. From the absorption spectra, in conjunction to a photon diffusion model that depicts photon migration pathways in biological tissues and mathematically separates scattering effects from absorption the concentrations of oxy-hemoglobin and deoxy-hemoglobin can be determined [15] and provide a noninvasive measurement method for oxygenation in exercising tissue. Using continuous-wave (CW) based diffuse reflectance spectroscopy (DRS), several studies found a rebound of the relative oxy-hemoglobin concentration from a transient dip in muscle tissue at the onset of exercise and a subsequent recover slightly above the pre-exercise baseline [16,17,18]. Although CW DRS can make quick measurement of oxygen saturation from the measured reflectance using setups composed of simple light sources and detectors, however, it does not allow a separation of absorption from scattering under one-source one-detector configuration, thus requiring making assumptions of tissue scattering property to be constant, wavelength invariant, or linearly wavelength-dependent to estimate the concentration of tissues’ total hemoglobin [1921]. With CW DRS, Yodh et. al. revealed strong hemodynamic responses including blood flow and muscle oxygenation SmO2 during exercise by employing a fixed baseline reduced scattering ${\mu _s}^{\prime}$ of 5 cm−1 at 785 nm [20]. Ferreira et. al. further confirmed that the muscle tissues’ scattering property changed during exercise, and a presumed constant scattering can lead to a distortion in the recovered hemodynamic parameters [22].

Frequency-domain diffuse reflectance spectroscopy (FD DRS) systems utilize radiofrequency (RF)-modulated input photon sources and determine the amplitude demodulation and phase delay introduced by tissues. The information collected at either single or multiple source detector distances (SDDs) can be used to extract absorption and scattering coefficients of biological tissues, which, through the fitting of lambert’s law of absorbance, can be used to determine the concentration of oxy-/deoxy- hemoglobin. For example, Periard et. al. studied the muscle tissue’s hemodynamics during steady-state, moderate intensity cycling using a multi-SDD FD DRS, which acquired data at 1.94 s per data point, found absolute changes in a flattened concentration of deoxy-hemoglobin and uprising trends for oxy-hemoglobin, total hemoglobin and oxygen saturation (SmO2) toward exhaustion [4]. Using the same type of instrument with sampling rate of 50 Hz, the required oxygenation in muscle tissues for the cycling exercise was found impaired in diabetes II patients due to the spatial heterogeneity of oxygen uptakes [23].

Up-to-date, most of the exercise-relevant studies aimed to interrogate the skeletal muscle tissues, but used models that assumed homogeneous tissue structure by neglecting the influence of adipose and skin layers [24,25]. Franceschini et. al.’s systematic interrogation on the simulating effects of a cover-up layer on the reduced scattering coefficient, ${\mu _s}^{\prime}$, of an underneath thick block utilizing FD DRS, for example, revealed at least 20% of deviation when the ratio of thickness of the top layer over the block is greater 0.05 [25], suggesting an imposing influence of skin layer on the optical measurement of subcutaneous tissues. An another CW DRS investigation not only extracted the NIR ${\mu _a}$ and ${\mu _s}^{\prime}$ spectra pre-corrected with skin pigment and fat, but also assumed a linear wavelength-dependence of the ${\mu _s}^{\prime}$ to determine SmO2, implying the importance of other tissue layers above the muscle tissue [19]. To make things more awkward, the findings of a few reports indicated that the skin blood flow can likewise contribute significantly to the DRS measurement [26,27], which, may mislead the result interpretation, and however, was largely neglected in a majority of measurement on skeletal muscle oxygenation. In addition, one’s capability of modulating the skin blood flow to satisfy the thermo-regulatory demands reflects the level of exercise training [28]. Thus, these aforementioned findings suggest that the importance of skin tissue’s hemoglobin concentration in the correlation with athelete’s performance is often overlooked, leaving the role of skin tissue’s hemodynamic properties in exercise at bay as a controversial issue for further discovery. Therefore, a complete understanding of the dynamic change in skin tissue’s hemodynamics and thermal regulatory function during the entire span of long-duration cycling exercise from the onset, to incremental steady intensities, and from exhaustion to recovery is of great importance.

FD DRS, being capable of single source and detector pair to restrain the measurement of interest on the volume of the skin tissue, could better elucidate the skin tissue’s hemodynamics, evaluate usefulness and value of skin measurement, and segregate the implication from other subcutaneous tissues. Hence, the principle goals of this present study are two-fold. Principally, using our FD DRS system, we direct our aim to better understand the variation of absorption and scattering properties of skin of individuals undergoing an hour of cycling ergometer exercise. Secondly, in addition to heart rate and skin temperature, the role of the cutaneous tissue’ hemodynamics in objectively assessing the cyclists’ physiological conditions during the course of the exercise, is to be elucidated. Since our measurements were performed on the forearm, our results shown here may provide a potential reference for the design of future wearable devices that are capable of monitoring the local tissue oxygenation and thermo-regulatory conditions of users.

2. Experimental methods

2.1 Frequency-domain diffuse optics theory

Typical FD DRS systems work in conjunction with photon transport models to determine the absorption coefficient (${\mu _a}$) and reduced scattering coefficient (${\mu _s}^{\prime}$) of biological tissues. Temporally dependent diffusion theory, for example, is a frequently adopted photon transport model that describes light propagation in an infinite turbid medium and can be written as [29]

$$\left[ {\frac{1}{c}\frac{\partial }{{\partial t}} + {\mu_a} - \nabla [{D(r )\nabla } ]} \right]\mathrm{\Phi }({r,t} )= S({r,t},$$
where D=1/3(${\mu _a} +{\mu _s}^{\prime}$ and φ are the diffusion constant and photon fluence rate, respectively. S is the source term of input optical power and c is the speed of light in the medium. As a harmonic light source is used, the source term in the equation can be expressed in the form of P•exp(iωt), and the fluence rate is solved explicitly as:
$$\mathrm{\Phi }\left( {\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\rightharpoonup$}} \over r} ,t} \right) = \frac{{P \bullet \textrm{exp}({ - {k_{real}}r} )}}{{4\pi Dr}}\textrm{exp}[{ - i({{k_{imag}}r - \omega t} )} ],$$
where ${k_{real}}$ and ${k_{real}}$ are
$${k_{real}} = \sqrt {\frac{3}{2}{\mu _a}{\mu _s}^{\prime}} {\left\{ {{{\left[ {1 + {{\left( {\frac{\omega }{{c{\mu_a}}}} \right)}^2}} \right]}^{{\raise0.7ex\hbox{$1$} \!\mathord{\left/ {\vphantom {1 2}} \right.}\!\lower0.7ex\hbox{$2$}}}} + 1} \right\}^{{\raise0.7ex\hbox{$1$} \!\mathord{\left/ {\vphantom {1 2}} \right.}\!\lower0.7ex\hbox{$2$}}}}$$
$${k_{imag}} = \sqrt {\frac{3}{2}{\mu _a}{\mu _s}^{\prime}} {\left\{ {{{\left[ {1 + {{\left( {\frac{\omega }{{c{\mu_a}}}} \right)}^2}} \right]}^{{\raise0.7ex\hbox{$1$} \!\mathord{\left/ {\vphantom {1 2}} \right.}\!\lower0.7ex\hbox{$2$}}}} - 1} \right\}^{{\raise0.7ex\hbox{$1$} \!\mathord{\left/ {\vphantom {1 2}} \right.}\!\lower0.7ex\hbox{$2$}}}}.$$

By applying an extrapolated boundary condition and the Fick’s law, the frequency-domain diffuse reflectance R in a semi-infinite medium can be determined as [29]

$$R = \mathop \smallint \nolimits_{2\pi }^{} d\Omega [{1 - {R_F}({cos\theta } )} ]\cdot \frac{1}{{4\pi }}\left[ {{\mathrm{\Phi }_{Z = 0}} + 3D{{\left. {\frac{{\partial \mathrm{\Phi }}}{{\partial z}}} \right|}_{z = 0}}cos\theta } \right]cos\theta ,$$
where RF is the Fresnel reflection coefficient. The ${\mu _a}$ and ${\mu _s}^{\prime}$ can be calculated by fitting the measured frequency-domain diffuse reflectance to Eq. (2.5) through a nonlinear least square optimization algorithm, such as the MATLAB (Mathworks, MA) lsqcurvefit function employed in this study. The derived absorption coefficients can be further used to quantify the dynamic changes in the absolute values of oxy-hemoglobin or deoxy-hemoglobin concentration of skin tissue using Beer-Lambert law and the known absorption extinction spectra of hemoglobin [30]. Based on these absolute quantities, the fraction of oxy-hemoglobin referred as StO2 and the sum of oxy-hemoglobin and deoxy-hemoglobin termed the total hemoglobin concentration can be readily determined.

2.2 FD DRS system

Figure 1 illustrates a complete setup of the FD DRS system that is consisted of electronic, optic and optoelectronic units for modulation of photon sources, sample illumination, retrieval of signal from an examining object. At the central hub of the system are three laser diodes that deliver fathoming light sources for sample interrogation. These laser diodes emitting photon with center wavelengths of 660 nm (HL6545MG, Thorlabs, Inc., United States), 780 nm (QLD-780-150S, QPhotonics, Inc., United States) and 830 nm (QLD-830-150S, QPhotonics, Inc., United States) were biased with a proper D.C. current source for A.C. modulation, mounted on a temperature-controlled platform, and synchronously fed with amplified, equally divided, bandpass-filtered RF sinusoid sources at the designated frequencies from a network analyzer (N5230C, Agilent Technologies, United States). The emitted photon from the laser diodes were first collimated with aspherical lenses, coupled by ball lenses onto the respective multimode optical fibers and delivered to an optical probe, which is configured in such ways that the distal ends of the illuminating optical fibers are linearly arranged and equivalently spaced 8 mm from a receiving multi-mode optical fiber, for sample interrogation. The spacing of 8 mm was designed for examining the skin tissue approximately 2∼3 mm deep into the cutaneous surface, thus potentially excluding the layer of muscular structure [30]. Afterward, the returning optical retro-reflectance signal was collected by a multimode optical fiber and registered using an avalanche photodiode (APD) (Module C5658, Hamamatsu photonics K.K., Japan) that sends out RF signals to be received by the network analyzer helping decipher the modulation of amplitude and phase of the incident RF signals via the photon migration in the examining samples. System calibration extracting the deviation of absorption and scattering coefficients of a known phantom composite sample was done and shown in our previous papers [31,32].

 figure: Fig. 1.

Fig. 1. Component-level schematic diagram of three-wavelength FD DRS system. This system is comprised of the modules of radio frequency (RF) electronics, laser diodes and controls, optical probe for sample interrogation and optoelectronic receiver. Blue and red line paths indicate electronic and optical routes. LM, IOF, DOF and BPF stand for laser module, input optical fiber, detection optical fiber and RF bandpass filter, respectively.

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2.3 Cycling ergometer exercise protocol

Three participants from our laboratory were enlisted to conduct this study on one-hour cycling ergometer exercise, which was approved by and conducted under the guidelines of the human research ethics committee of National Cheng Kung University. Participant A, B, and C were aged 29, 26, and 24 years old, weighted 80 Kg, 76 Kg, and 76 Kg, and had body mass indices (BMI) of 31.2, 22.9, and 22.9, respectively, and participant B was an amateur of sport activities. As shown in the schematic of Fig. 2(a), each individual was mounted with a temperature sensor (PS-3200, Pasco, Inc., United States), the custom-made FDPM probe, and a chest-strapped heart rate sensor (Polar H10, Polar Electro, Finland) in the corresponding location to monitor the skin temperature, THb concentration and oxygen saturation (StO2%) of the skin tissue, and heartbeat rate, respectively. The protocol of the cycling exercise goes as the following and is presented by zones of colors in Fig. 2(b). Prior to the beginning of the exercise, the measurement of all parameters were taken under the static condition for 300 s (grey zone).

 figure: Fig. 2.

Fig. 2. Schematic diagrams of (a) somatic location of the measuring devices, the FDPM probe, heart rate belt and temperature sensor on the participants and (b) a temporal protocol of all stages of the cycling exercise in color zones are presented. TIL stands for training intensity level; in the brackets are the time dedicated to each zone, x means individual-dependent duration; the red arrow points from the start of the exercise to the recovery.

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The speed was subsequently maintained between 60–65 round per min. (RPM) at TIL:1 for a warm-up of 360 s (first white zone), and incrementally intensified in the TIL every 4 min. (second white zone). Afterward, the speed was kept at the highest TIL:7 and stopped till the exhaustion occurs (pink zone), the duration of which is individual-dependent, and the recovery process after the occurrence of exhaustion was also monitored until a total of 3200 s was recorded (in green zone).

3. Results and discussion

3.1 Optical properties of forearm skin tissue

Throughout the entire session of the one-hour ergometer exercise, the RF modulation frequency-dependent absorption spectra of three distinctive photon wavelength, 660 nm, 780 nm and 830 nm were measured as a function of time and utilized to extract the absorption coefficient, ${\mu _a}$, and reduced scattering coefficient, ${\mu _s}^{\prime}$, of skin tissues of the participants. Figure 3 illustrates the time-course profiles of the coefficients of the participant A. As can be seen in Fig. 3(a), the ${\mu _a}$ of skin tissue increases as the photon wavelength decreases, and the traces of all wavelengths peak within the exhaustion zone (2040 s). In details, traces of ${\mu _a}$ at 660 nm, 780 nm and 830 nm, start to take off at 750 s, continues to hike drastically over the next 1290 s, which was conferred in the vicinity of exhaustion zone implying a rapid influx of red blood cells in the local skin tissue [33]. Afterward, ${\mu _a}$ drops monotonically as the O2 was largely depleted in the local tissue corresponding to the end of the exhaustion zone, and later gets stabilizes at a level as the metabolic demand for the O2 was gradually ceased and re-stabilized. Similar to ${\mu _a}$, the ${\mu _s}^{\prime}$ decreases as the wavelength increases, which confirms the typical results for people with light skin in the previous studies [34,35]. Temporally, the ${\mu _s}^{\prime}$ of all wavelength increases slightly until the trace of 660 nm drops abruptly and the traces of 780 nm and 860 nm peaks at the end of exhaustion zone (at 2040 s). Also note the corresponding peak and dip at 2000 s. Within the recovery period, the trace of 660 nm re-elevates slightly and remain at a stabilized level while others flatten at a stabilized level.

 figure: Fig. 3.

Fig. 3. Absorption and scattering coefficients of participant A. Time-course profiles of μa and μs at the laser wavelength of 660 nm, 780 nm and 830 nm are respectively presented by black, red and blue lines.

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By implementing the same exercise protocol, the time-course profiles of ${\mu _a}$ and ${\mu _s}^{\prime}$ for participant B were registered and are presented in Fig. 4. Contrary to participant A and previous studies [34,35], the participant B’s ${\mu _a}$ decreases as the photon wavelength decreases. Of all wavelength, the temporal trace of ${\mu _a}$ starts to kick off at 790 s and peaks at the end of exhaustion zone (2000 s). Afterward, all traces reduced gradually till the end of recording session. On the other hand, the ${\mu _s}^{\prime}$ behaves in an opposite fashion when compared to ${\mu _a}$ and reduces as the wavelength increases. Also, participant B has neither a clear peak of ${\mu _a}$ nor a dipping valley of ${\mu _s}^{\prime}$ found in participant A, the disparities of which may be explained by the sheer difference of the two participants in the physical caliber, BMI and dissipating ability of Tc.

 figure: Fig. 4.

Fig. 4. Absorption and scattering coefficients of participant B. Time-course profiles of ${\mu _a}$ and ${\mu _s}^{\prime}$ at the laser wavelength of 660 nm, 780 nm and 830 nm are respectively presented by black, red and blue lines.

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Likewise, a third examining individual, the participant C, was undergone the same cycling ergometer protocol. Shown in Fig. 5 are the extracted temporally dependent optical properties, ${\mu _a}$ and ${\mu _s}^{\prime}$ at the three wavelength. The dependence of ${\mu _a}$ on wavelength generally follows those of participant A and B, especially within the range posterior to 1000 s when the ${\mu _a}$ start to rise, peak distinctively at around 2000 s and decrease subsequently till the end of the exercise. Oppositely, the ${\mu _s}^{\prime}$ coefficient at 780 nm is higher than at 830 nm throughout the entire cycling session, which is not congruent with those of participant B and C.

 figure: Fig. 5.

Fig. 5. Absorption and scattering coefficients of participant C. Time-course profiles of ${\mu _a}$ and ${\mu _s}^{\prime}$ at the laser wavelength of 660 nm, 780 nm and 830 nm are respectively presented by black, red and blue lines.

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Also notice the apparent peaks observed for all wavelength at 2000 s which coincides with the time-point toward the end of exhaustion zone and no corresponding abruptions can be found from the respective StO2 and THb. Hence, together with the seemingly correlated spike and dip at 2000 s in the 660 nm plot, we concluded that such peaks and dips are most likely due to an abrupt event caused by the shaky attachment of the optical probe off the forearm skin surface as the cyclist experienced the strenuous effort toward the end of the exhaustion since the same effect is not observed in other wavelength plots, therefore, we believe such abruption is not of any physiological correlation.

As a summary for this section, in contrast to the previous studies, in which pre-defined baselines of ${\mu _s}^{\prime}$ were used for determining hemodynamic analysis during exercise, our results indicated that all cycling participants have substantial disparity in the ${\mu _s}^{\prime}$ of skin tissue, casting great impact on the accuracy of molecular quantification and authenticity of the outcome interpretation of exercise. Hence, we believe that our results shown in this study may provide useful information for researchers in the relevant community to evaluate the necessity of quantifying absolute absorption and reduced scattering properties in their future studies.

3.2 Parameters of tissue oxygenation

Subsequently, the determination of ${\mu _a}$ and ${\mu _s}^{\prime}$ allows quantification of the concentration of chromophores including oxy-hemoglobin, deoxy-hemoglobin, and lipid fat by numerically fitting the coefficients in the Beer-Lambert power law with the known absorption extinction spectra of the chromophores. Molecularly, the quantified concentration of oxy-hemoglobin and deoxy-hemoglobin convey the status of tissue oxygenation when the testing individuals were at rest or in the different stages of the cycling activity. To better elucidate the dynamic adaptation of forearm skin tissue’s oxygenation status to the changes of physiological condition, the relevant oxygenation parameters, StO2%, THb concentration, a sum of oxy-hemoglobin and deoxy-hemoglobin, along with the heart rate and skin temperature were monitored for an hour.

3.2.1 Participant A

Participant A was considered in the state of obesity for his BMI (31.2) greater than 30 [36], and indeed, has a sedentary lifestyle while attending the graduate school. Figure 6 depicts the temporal profiles of the tissue oxygenation parameters of participant A. Immediately, within the first 25 s of the exercise, an abrupt jump in the heart rate from 79 to 107 beats can be identified while the StO2 remain at 71%, a transitory change in skin temperature from a slight drop at 660 s to re-stabilization around 31.8 °C attributed to a concomitant increase of vasoconstrictor [37,38], was observed. Additionally, the THb concentration rises for a mere of 1.8% over the next 450 s posterior to the start of the exercise; physiologically, the drop in skin temperature at 660 s corresponds a chill felt by participant A. Right after the finishing of the warm-up session (first 360 s) and once entering a period of regular increments in the TIL every 4 min., all parameters underwent drastic increases. The rise in StO2, which was confirmed by the previous studies on muscle tissues during exercise [27], reflects an increasing demand for O2 metabolism and greater energy consumption, causing a parallel hike in the THb concentration [13]. As the skeletal muscle tissue in the body, particularly of the legs, engage in O2 metabolism that generates heat and induces consequential thermoregulatory mechanisms promoting drastic increases in the skin blood flow and temperature [28,38]. Also note a unique feature of a lag of about 450 s between the rising edges of the skin temperature and StO2 implying an infusion of oxygen-binding red blood cells for O2 metabolism that augments the Tc, and thus, necessitates a delayed dissipation of heat through a cutaneous endothelium-dependent vasodilation that increases heart rate and the associated skin blood flow to compensate for the continuing build-up of the Tc and to keep up the metabolic functions of O2 upon energy extraction [10,38]. Once the participant A reached the exhaustion zone (pink zone) defined as 90% of the maximal theoretical heart rate, all parameters continued to increase at a slower pace except the StO2 which drops monotonically from 77% to 68.8% at the end of exhaustion zone, Such reduction in StO2 as well as the increase in the THb concentration, which was found in the muscle tissue [8], suggest a depletion of oxy-hemoglobin and an imbalance between supply and demand of O2 as the cyclist experienced the maximal level of training intensity in the zone of physiological exhaustion, and the supply of O2 cannot keep up the metabolic needs despite the continuing increase in the heart rate and skin temperature, which can be explained by a constrained skin blood flow once the Tc reaches its maximum [39,40]. Concurrently, the heart rate, total hemoglobin concentration and skin temperature attended their respective maximal values, 193 number/min, 139.8 uM and 35.5 °C at the end of exhaustion. Once the exercise arrested, StO2 rebounded beyond 75% during the recovery session suggesting that the oxy-hemoglobin was re-supplanted in the skin tissue during the recovery of tissue oxygenation while the heart rate and total hemoglobin concentration drop deciduously at 2024 s and continue the dwindling trend throughout the entire recovery record.

 figure: Fig. 6.

Fig. 6. Time-course profiles of the StO2, skin temperature, heart rate and THb concentration of participant A. The temporal duration and TIL of all color zones are depicted in Fig. 2(b).

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3.2.2 Participant B

Participant B was aged 3 years younger, weighted 4 Kg less than participant A and had a BMI of 22.9, which is much lower than participant A and considered normal for a college student [36]. The same exercise protocol was implemented and recorded temporally with the assessment parameters which are presented in Fig. 7. Similar to participant A, an immediate jump in heart rate from 94 to 103 within the first 25 s is identified, and the skin temperature drops from 32.8 °C to 32.57 °C, reflecting a chill in the leg felt by participant B as well as the evocation of vasoconstrictors [41], and the oxy-hemoglobin and total hemoglobin concentration take off slightly within the duration of warm-up. Once the cyclist entered the zone of incremental intensity, the sharp rising edge of total hemoglobin concentration and a gently rising edge of StO2 at 900 s can be found, which later plateau at 131.8 μM and 88% at 1706 s for the entire period of exhaustion zone. Also note that the uprising edge of the skin temperature is 170 s behind the THb concentration’s abrupt jump at 900 s, and this temporal lag is 2.6-fold smaller than that of participant A, implying a quicker heat dissipation through an increase in skin blood flow for participant B than for participant A [42]. Once the cyclist reached the exhaustion zone, the THb concentration remained at 131.8 μ M, the skin temperature and heartbeat continued to rise till the exercise was arrested scoring their respective maxima at 34.48 °C and 186 number/min. Participant B’s exceeding ability of heat dissipation and 11% higher in maximal StO2 than those of participant A can well correspond his lower BMI, implying a higher aerobic and cardiorespiratory fitness [43]. For both participants, the skin temperature is only highly correlated with the heartbeat rate, a quintessential driver of skin blood flow rate [28]. This correlation is also confirmed indirectly by the previous studies where the time-course profiles of the skin temperature of sports players, cycling ergometer or supine leg exercise, were strongly in parallel with blood flow rate [44,37]. Interestingly, in contrast to participant A, no significant drop (<0.2%) in StO2 throughout the entire exercise session was found, and this measurement is believed to be an authentic StO2 for the superficial layers of skin tissue above adipose tissue since the SDD of the FDPM probe was not designed to examine muscle region [30] and no iconic drop in the StO2 of muscle tissue was observed [26,45]. While the hand-gripping position and manner of participant B stay mostly consistent and stable throughout the entire cycling session, we suspect that such discrepancy in StO2 is most likely attributed to participant A’s tenuously hard hand-gripping action that inadvertently disturbs the measurement of the FDPM probe as the final exhaustion was experienced. Therefore, the skin’s structure may be in a constantly well-oxygenated state, and remain relatively impertinent to the exercise-induced metabolic needs of tissue oxygenation than its associated muscle layer. During the period of recuperation, the StO2 drops only slightly to 87.9%, then rebounded and continued with an uprising trend while the heartbeat, skin temperature and THb concentration dropped continuously as the demand of metabolic needs for O2 ceased. Another interesting point is the highest skin temperature of 32.6 °C attained at 2000 s, which 2 °C lower than that of participant A.

 figure: Fig. 7.

Fig. 7. Time-course profiles of the StO2, skin temperature, heart rate and THb concentration of participant B. The temporal duration and TIL of all color zones are depicted in Fig. 2(b).

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3.2.3 Participant C

Participant C was 5 years younger than participant A, weighted and BMI-indexed the same as participant B and undergone the similar exercise protocol, the relevant examining parameters are presented in Fig. 8. A similar jump in the heart rate at the onset of the exercise was recorded, and it increases all the way until the end of exhaustion zone was reached. Likewise, the trend of participant C’s total hemoglobin behaves similarly as the other participants, increasing from 105.2 μM to 140.6 μM as the exercise proceeds from onset toward exhaustion. Unlike the other participants, of which the StO2 level rises as the working intensity increases from the lowest to highest, the participant C’s StO2 level does not increase significantly and undulates around 130% from the beginning to the end of the exercise. Moreover, the lagging of the rising edge of skin temperature behind that of total Hb was not observed in the participant C, and instead, the skin temperature only increases mildly from 33.2 to 33.9 °C, drop at around 1050s, which also can be found in Participant B and C. The skin temperature stays low at about 33.4 °C posterior to 1350 s till the rest of the exercise, contradicting the uprising trends for the participant B and C as well as the participant’s self-evaluation on skin temperature sensation that records highest degree of warm. We double-checked with the temperature sensor, and found no glitches in data readout system. Thus, we believe that this may be caused by the sweats and faster heat dissipation. Furthermore, the increase in total hemoglobin concentration by 21 μM, 36.5 μM and 35.4 μM from TL2 to TL6 for participant A, B and C corresponds well with the respective BMI, where participant A’s obesity and lower physical caliber confirm with his lower magnitude change in the total hemoglobin than participant B and C. As a major conclusion of this study, the skin tissue’s hemoglobin concentration serves as a better indicator for physiological condition of cyclists than the skin temperature, and is not influenced by the skin’s temperature variation.

 figure: Fig. 8.

Fig. 8. Time-course profiles of the StO2, skin temperature, heart rate and THb concentration of participant C. The temporal duration and TIL of all color zones are depicted in Fig. 2(b).

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4. Conclusion

In summary, this study examined the hemodynamic status of skin tissue in three human participants undergoing an hour of cycling ergometer exercise. Expressly, the time-dependent absorption of the participants’ forearm skin tissue at three laser wavelength 660 nm, 780 nm and 830 nm alongside the real-time in situ skin temperature and heartbeat rate were registered. Thereafter, the temporal profiles of variation in optical properties of skin tissue, the absorption and scattering coefficients, and the corresponding hemodynamic parameters including StO2 and total hemoglobin concentration were determined and analyzed. These informative data not only convey the instant status of oxygenation in the skin tissue, but also provide an insight into the hemodynamic adaptation of physiological conditions of the participants undergoing different stages of the exercise protocol. Overall, several interesting features from the time-dependent profiles can be generalized. For instance, a jump in heart rate at the beginning of the exercise in all participants as well as a lag in time of the skin temperature’s uprising edge behind that of total hemoglobin concentration was found in all participants. Also, a consistent supply of StO2 in the cutaneous tissue throughout the entire session of the exercise was found, and the current design of FDPM probe could produce some unnoticeable disturbance in the data readout. The heartbeat rate and total hemoglobin of all participants continued to rise all the way until the exercise was arrested, both the maximal heartbeat rate and heat dissipation efficiency have reached their maxima, and the thermos-regulatory drive cannot help keep up the delivery of any additional O2 from cardiac output. Lastly, this study proved the concept of monitoring the physiological conditions of individuals participated in cycling ergometer exercise by measuring optical and hemodynamic properties of forearm’s skin tissue. We found that total hemoglobin is a better indicator for the physiological condition of exercising athletes than the skin temperature. Together with in situ measurement of the total hemoglobin and heartbeat rate not only was the correlation between cardiac out and efficiency of heat dissipation better understood, but also their dynamic adaptation to the metabolic needs of oxy-hemoglobin in the local skin tissue was well elucidated.

Funding

Ministry of Science and Technology, Taiwan (107-2221-E009-102-MY3, 110-2221-E-A49-102).

Disclosures

The authors declare no conflict of interest.

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

References

1. K.-M. Scheufler, “Tissue oxygenation and capacity to deliver O2 do the two go together?” Transfus Apher. Sci. 31(1), 45–54 (2004). [CrossRef]  

2. J. Gozalez-Alonso, S. P. Mortensen, E. A. Dawson, N. H. Secher, and R. Damsgaard, “Erythrocytes and the regulation of human skeletal muscle blood flow and oxygen delivery: role of erythrocyte count and oxygenation state of haemoglobin,” J. Physiol. 572(1), 295–305 (2006). [CrossRef]  

3. P. G. Rodriguez, F. N. Felix, D. T. Woodley, and E. K. Shim, “The role of oxygen in wound healing: a review of the literature,” Dermatol. Surg. 34(9), 1159–1169 (2008). [CrossRef]  

4. J. D. Periard, M. W. Thompson, C. Caillaud, and V. Quaresima, “Influence of heat stress and exercise intensity on vastus lateralis muscle and prefrontal cortex oxygenation,” Eur. J. Appl. Physiol. 113(1), 211–222 (2013). [CrossRef]  

5. P.A. Beest, J. J. Vos, M. Poterman, A. F. Kalmar, and T. W. L. Scheeren, “Tissue oxygenation as a target for goal-directed therapy in high-risk surgery: a pilot study,” BMC Anesthesiology 14(1), 122 (2014). [CrossRef]  

6. J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” Br. J. Anaesth. Suppl. 103, Suppl. 1, I3-I13 (2009).

7. F. Esposito, V. Reese, R. Shabetai, P. D. Wagner, and R. S. Richardson, “Isolated quadriceps training increases maximal exercise capacity in chronic heart failure,” J. Am. Coll. Cardiol. 58(13), 1353–1362 (2011). [CrossRef]  

8. B. Grassi, V. Quaresima, C. Marconi, M. Ferrari, and P. Cerretelli, “Blood lactate accumulation and muscle deoxygenation during incremental exercise,” J. Appl. Physiol. 87(1), 348–355 (1999). [CrossRef]  

9. W. L. Kenny and J. M. Johnson, “Control of skin blood flow during exercise,” Med. Sci. Sports Exerc. 96(9), 822–828 (2011).

10. C. W. Ho, J. L. Beard, P. A. Farrell, C. T. Minson, and W. L. Kenney, “Age, fitness, and regional blood flow during exercise in the heat,” J. Appl. Physiol. 82(4), 1126–1135 (1997). [CrossRef]  

11. R. A. Blasi, M. Ferrari, A. Natali, G. Conti, A. Mega, and A. Gasparetto, “Noninvasive measurement of forearm blood flow and oxygen consumption by near-infrared spectroscopy,” J. Appl. Physiol. 76(3), 1388–1393 (1994). [CrossRef]  

12. C. M. Thomas, J. M. Pierzga, and W. L. Kenney, “Aerobic training and cutaneous vasodilation in young and older men,” J. Appl. Physiol. 86(5), 1676–1686 (1999). [CrossRef]  

13. T. Hamaoka, K. K. McCully, V. Quaresima, K. Yamamoto, and B. Chance, “Near-infrared spectroscopy/imaging for monitoring muscle oxygenation and oxidative metabolism in healthy and diseased humans,” J. Biomed. Opt. 12(6), 062105 (2007). [CrossRef]  

14. F. F. Jobsis, “Noninvasive infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science 198(4323), 1264–1267 (1977). [CrossRef]  

15. T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010). [CrossRef]  

16. M. J. MacDonald, M. A. Tarnopolsky, H. J. Green, and R. L. Hughson, “Comparison of femoral blood gases and muscle near-infrared spectroscopy at exercise onset in humans,” J. Appl. Physiol. 86(2), 687–693 (1999). [CrossRef]  

17. D. S. DeLorey, J. M. Kowalchuk, and D. H. Paterson, “Relationship between pulmonary O2 uptake kinetics and muscle deoxygenation during moderate-intensity exercise,” Js. Appl. Physiol. 95(1), 113–120 (2003). [CrossRef]  

18. B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003). [CrossRef]  

19. Y. Yang, O. Soyemi, P. J. Scott, M. R. Landry, S. M. Lee, L. Stroud, and B. R. Soller, “Quantitative measurement of muscle oxygen saturation without influence from skin and fat using continuous-wave near infrared spectroscopy,” Opt. Express 15(21), 13715–13730 (2007). [CrossRef]  

20. G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10(2), 024027 (2005). [CrossRef]  

21. V. Quaresima, M. Ferrari, M. A. Franceschini, M. L. Hoimes, and S. Fantini, “Spatial distribution of vastus lateralis blood flow and oxyhemoglobin saturation measured at the end of isometric quadriceps contraction by multichannel near-infrared spectroscopy,” J. Biomed. Opt. 9(2), 413–420 (2004). [CrossRef]  

22. L. F. Ferreira, D. M. Hueber, and T. J. Barstow, “Effects of assuming constant optical scattering on measurements of muscle oxygenation by near-infrared spectroscopy during exercise,” J. Appl. Physiol. 102(1), 358–367 (2007). [CrossRef]  

23. P. M. McClatchey, T. A. Bauer, J. G. Regensteiner, I. E. Schauer, A. G. Huebschmann, and J. E. B. Reusch, “Dissociation of local and global skeletal muscle oxygen transport metrics in type 2 diabetes,” J. Diabetes Complications 31(8), 1311–1317 (2017). [CrossRef]  

24. M. C. van Beekvelt, M. S. Borghuis, B. G. van Engelen, R. A. Wevers, and W. N. Colier, “Adipose tissue thickness affects in vivo quantitative near-IR spectroscopy in human skeletal muscle,” Clin. Sci. 101(1), 21 (2001). [CrossRef]  

25. M. A. Franceschini, S. Fantini, L. A. Paunescu, J. S. Maier, and E. Gratton, “Influence of a superficial layer in the quantitative spectroscopic study of strongly scattering media,” Appl. Opt. 37(31), 7447–7458 (1998). [CrossRef]  

26. S. L. Davis, P. J. Fadel, J. Cui, G. D. Thomas, and C. G. Crandall, “Skin blood flow influences near-infrared spectroscopy-derived measurements of tissue oxygenation during heat stress,” J. Appl. Physiol. 100(1), 221–224 (2006). [CrossRef]  

27. M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Phil. Trans. Soc. 369(1955), 4577–4590 (2011). [CrossRef]  

28. G. H. Simmons, B. J. Wong, L. A. Holowatz, and W. L. Kenney, “Changes in the control of skin blood flow with exercise training: where do cutaneous vascular adaptations fit in?” Exp. Physiol. 96(9), 822–828 (2011). [CrossRef]  

29. R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. 11(10), 2727–2741 (1994). [CrossRef]  

30. T. Del Rio, L. Valor, I. de la Torre, and E. Naredo, “Impact of the thickness of the subcutaneous tissue at the site of injection as measured by ultrasound on the therapeutic response to subcutaneous anti-tumour necrosis factor drugs,” Reumatol. Clin. 12(5), 300–301 (2016). [CrossRef]  

31. Y. W. Chen, C. C. Chen, P. J. Huang, and S. H. Tseng, “Artificial neural networks for retrieving absorption and reduced scattering spectra from frequency-domain diffuse reflectance spectroscopy at short source-detector separation,” Biomed. Opt. Exp. 7(4), 1496–1510 (2016). [CrossRef]  

32. M. W. Lee, C. H. Hung, J. L. Liao, N. Y. Cheng, M. F. Hou, and S. H. Tseng, “A linear gradient line source facilitates the use of diffusion models with high order approximation for efficient, accurate turbid sample optical properties recovery,” Biomed. Opt. Express 5(10), 3628–3639 (2014). [CrossRef]  

33. A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, “Optical properties of circulating human blood in the wavelength range 400-2500 nm,” J. Biomed. Opt. 4(1), 36–46 (1999). [CrossRef]  

34. Y. Shimojo, T. Nishimura, H. Hazama, T. Ozawa, and K. Awazu, “Measurement of absorption and reduced scattering coefficients in Asian human epidermis, dermis, and subcutaneous fat tissues in the 400- to 1100-nm wavelength range for optical penetration depth and energy deposition analysis,” J. Biomed. Opt. 25(04), 1 (2020). [CrossRef]  

35. S. H. Tseng, A. Grant, and A. J. Durkin, “In vivo determination of skin near-infrared optical properties using diffuse optical spectroscopy,” J. Biomed. Opt. 13(1), 014016 (2008). [CrossRef]  

36. M. Grasdalsmoen, H. R. Eriksen, K. J. Lonning, and B. Sivertsen, “Physical exercise and body-mass index in young adults: a national survey of Norwegian university students,” BMC Public Health 19(1), 1354 (2019). [CrossRef]  

37. J. M. Johnson and M. K. Park, “Effect of heat stress on cutaneous vascular responses to the initiation of exercise,” J. Appl. Physiol. Respir. Environ. Exerc. Physiol. 53(3), 744–749 (1982). [CrossRef]  

38. M. A. Black, D. J. Green, and N. T. Cable, “Exercise prevents age-related decline in nitric-oxide-mediated vasodilator function in cutaneous microvessels,” J. Physiol. 586(14), 3511–3524 (2008). [CrossRef]  

39. M. F. Roberts, C. B. Wenger, J. A. Stolwijk, and E. R. Nadel, “Skin blood flow and sweating changes following exercise training and heat acclimation,” J. Appl. Physiol. 43(1), 133–137 (1977). [CrossRef]  

40. J. Gonzalez-Alonso, C. Teller, S. L. Andersen, F. B. Jensen, T. Hyldig, and B. Nielsen, “Influence of body temperature on the development of fatigue during prolonged exercise in the heat,” J. Appl. Physiol. 86(3), 1032–1039 (1999). [CrossRef]  

41. D. L. Kellogg Jr, J. M. Johnson, and W. A. Kosiba, “Competition between cutaneous active vasoconstriction and active vasodilation during exercise in humans,” Am. J. Physiol. 261(6), C1184–C1195 (1991). [CrossRef]  

42. J. M. Johnson and D. W. Proppe, “Cardiovascular adjustments to heat stress,” The handbook of physiology, section 4: Environmental Physiology, Vol. 1, American Physiological Society; Bethesda, MD. Ch. 11, P 215 (1996).

43. V. Carayanni, E. Vlachopadopoulou, D. Koutsouki, G. C. Bogdanis, T. Psaltopoulou, Y. Manios, F. Karachaliou, A. Hatzakis, and S. Michalacos, “Effects of body mass index (BMI), demographic and socioeconomic factors on organized physical activity (OPA) participation in children aged 6-15 years: a cross-sectional study comparing primary and secondary school children in Greece,” 20(1), 491 (2020).

44. J. Smolander, P. Kolari, O. Korhonen, and R. Ilmarinen, “Skin blood flow during incremental exercise in a thermoneutral and a hot dry environment,” Eur. J. Appl. Physiol. 56(3), 273–280 (1987). [CrossRef]  

45. S. Koga, D. C. Poole, N. Kondo, A. Oue, E. Ohmae, and T. J. Barstow, “Effects of increased skin blood flow on muscle oxygantion/deoxygenation: comparison of time-resolved and continuous-wave near-infrared spectroscopy singals,” Eur. J. Appl. Physiol. 115(2), 335–343 (2015). [CrossRef]  

References

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  1. K.-M. Scheufler, “Tissue oxygenation and capacity to deliver O2 do the two go together?” Transfus Apher. Sci. 31(1), 45–54 (2004).
    [Crossref]
  2. J. Gozalez-Alonso, S. P. Mortensen, E. A. Dawson, N. H. Secher, and R. Damsgaard, “Erythrocytes and the regulation of human skeletal muscle blood flow and oxygen delivery: role of erythrocyte count and oxygenation state of haemoglobin,” J. Physiol. 572(1), 295–305 (2006).
    [Crossref]
  3. P. G. Rodriguez, F. N. Felix, D. T. Woodley, and E. K. Shim, “The role of oxygen in wound healing: a review of the literature,” Dermatol. Surg. 34(9), 1159–1169 (2008).
    [Crossref]
  4. J. D. Periard, M. W. Thompson, C. Caillaud, and V. Quaresima, “Influence of heat stress and exercise intensity on vastus lateralis muscle and prefrontal cortex oxygenation,” Eur. J. Appl. Physiol. 113(1), 211–222 (2013).
    [Crossref]
  5. P.A. Beest, J. J. Vos, M. Poterman, A. F. Kalmar, and T. W. L. Scheeren, “Tissue oxygenation as a target for goal-directed therapy in high-risk surgery: a pilot study,” BMC Anesthesiology 14(1), 122 (2014).
    [Crossref]
  6. J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” Br. J. Anaesth. Suppl. 103, Suppl. 1, I3-I13 (2009).
  7. F. Esposito, V. Reese, R. Shabetai, P. D. Wagner, and R. S. Richardson, “Isolated quadriceps training increases maximal exercise capacity in chronic heart failure,” J. Am. Coll. Cardiol. 58(13), 1353–1362 (2011).
    [Crossref]
  8. B. Grassi, V. Quaresima, C. Marconi, M. Ferrari, and P. Cerretelli, “Blood lactate accumulation and muscle deoxygenation during incremental exercise,” J. Appl. Physiol. 87(1), 348–355 (1999).
    [Crossref]
  9. W. L. Kenny and J. M. Johnson, “Control of skin blood flow during exercise,” Med. Sci. Sports Exerc. 96(9), 822–828 (2011).
  10. C. W. Ho, J. L. Beard, P. A. Farrell, C. T. Minson, and W. L. Kenney, “Age, fitness, and regional blood flow during exercise in the heat,” J. Appl. Physiol. 82(4), 1126–1135 (1997).
    [Crossref]
  11. R. A. Blasi, M. Ferrari, A. Natali, G. Conti, A. Mega, and A. Gasparetto, “Noninvasive measurement of forearm blood flow and oxygen consumption by near-infrared spectroscopy,” J. Appl. Physiol. 76(3), 1388–1393 (1994).
    [Crossref]
  12. C. M. Thomas, J. M. Pierzga, and W. L. Kenney, “Aerobic training and cutaneous vasodilation in young and older men,” J. Appl. Physiol. 86(5), 1676–1686 (1999).
    [Crossref]
  13. T. Hamaoka, K. K. McCully, V. Quaresima, K. Yamamoto, and B. Chance, “Near-infrared spectroscopy/imaging for monitoring muscle oxygenation and oxidative metabolism in healthy and diseased humans,” J. Biomed. Opt. 12(6), 062105 (2007).
    [Crossref]
  14. F. F. Jobsis, “Noninvasive infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science 198(4323), 1264–1267 (1977).
    [Crossref]
  15. T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
    [Crossref]
  16. M. J. MacDonald, M. A. Tarnopolsky, H. J. Green, and R. L. Hughson, “Comparison of femoral blood gases and muscle near-infrared spectroscopy at exercise onset in humans,” J. Appl. Physiol. 86(2), 687–693 (1999).
    [Crossref]
  17. D. S. DeLorey, J. M. Kowalchuk, and D. H. Paterson, “Relationship between pulmonary O2 uptake kinetics and muscle deoxygenation during moderate-intensity exercise,” Js. Appl. Physiol. 95(1), 113–120 (2003).
    [Crossref]
  18. B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003).
    [Crossref]
  19. Y. Yang, O. Soyemi, P. J. Scott, M. R. Landry, S. M. Lee, L. Stroud, and B. R. Soller, “Quantitative measurement of muscle oxygen saturation without influence from skin and fat using continuous-wave near infrared spectroscopy,” Opt. Express 15(21), 13715–13730 (2007).
    [Crossref]
  20. G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10(2), 024027 (2005).
    [Crossref]
  21. V. Quaresima, M. Ferrari, M. A. Franceschini, M. L. Hoimes, and S. Fantini, “Spatial distribution of vastus lateralis blood flow and oxyhemoglobin saturation measured at the end of isometric quadriceps contraction by multichannel near-infrared spectroscopy,” J. Biomed. Opt. 9(2), 413–420 (2004).
    [Crossref]
  22. L. F. Ferreira, D. M. Hueber, and T. J. Barstow, “Effects of assuming constant optical scattering on measurements of muscle oxygenation by near-infrared spectroscopy during exercise,” J. Appl. Physiol. 102(1), 358–367 (2007).
    [Crossref]
  23. P. M. McClatchey, T. A. Bauer, J. G. Regensteiner, I. E. Schauer, A. G. Huebschmann, and J. E. B. Reusch, “Dissociation of local and global skeletal muscle oxygen transport metrics in type 2 diabetes,” J. Diabetes Complications 31(8), 1311–1317 (2017).
    [Crossref]
  24. M. C. van Beekvelt, M. S. Borghuis, B. G. van Engelen, R. A. Wevers, and W. N. Colier, “Adipose tissue thickness affects in vivo quantitative near-IR spectroscopy in human skeletal muscle,” Clin. Sci. 101(1), 21 (2001).
    [Crossref]
  25. M. A. Franceschini, S. Fantini, L. A. Paunescu, J. S. Maier, and E. Gratton, “Influence of a superficial layer in the quantitative spectroscopic study of strongly scattering media,” Appl. Opt. 37(31), 7447–7458 (1998).
    [Crossref]
  26. S. L. Davis, P. J. Fadel, J. Cui, G. D. Thomas, and C. G. Crandall, “Skin blood flow influences near-infrared spectroscopy-derived measurements of tissue oxygenation during heat stress,” J. Appl. Physiol. 100(1), 221–224 (2006).
    [Crossref]
  27. M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Phil. Trans. Soc. 369(1955), 4577–4590 (2011).
    [Crossref]
  28. G. H. Simmons, B. J. Wong, L. A. Holowatz, and W. L. Kenney, “Changes in the control of skin blood flow with exercise training: where do cutaneous vascular adaptations fit in?” Exp. Physiol. 96(9), 822–828 (2011).
    [Crossref]
  29. R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. 11(10), 2727–2741 (1994).
    [Crossref]
  30. T. Del Rio, L. Valor, I. de la Torre, and E. Naredo, “Impact of the thickness of the subcutaneous tissue at the site of injection as measured by ultrasound on the therapeutic response to subcutaneous anti-tumour necrosis factor drugs,” Reumatol. Clin. 12(5), 300–301 (2016).
    [Crossref]
  31. Y. W. Chen, C. C. Chen, P. J. Huang, and S. H. Tseng, “Artificial neural networks for retrieving absorption and reduced scattering spectra from frequency-domain diffuse reflectance spectroscopy at short source-detector separation,” Biomed. Opt. Exp. 7(4), 1496–1510 (2016).
    [Crossref]
  32. M. W. Lee, C. H. Hung, J. L. Liao, N. Y. Cheng, M. F. Hou, and S. H. Tseng, “A linear gradient line source facilitates the use of diffusion models with high order approximation for efficient, accurate turbid sample optical properties recovery,” Biomed. Opt. Express 5(10), 3628–3639 (2014).
    [Crossref]
  33. A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, “Optical properties of circulating human blood in the wavelength range 400-2500 nm,” J. Biomed. Opt. 4(1), 36–46 (1999).
    [Crossref]
  34. Y. Shimojo, T. Nishimura, H. Hazama, T. Ozawa, and K. Awazu, “Measurement of absorption and reduced scattering coefficients in Asian human epidermis, dermis, and subcutaneous fat tissues in the 400- to 1100-nm wavelength range for optical penetration depth and energy deposition analysis,” J. Biomed. Opt. 25(04), 1 (2020).
    [Crossref]
  35. S. H. Tseng, A. Grant, and A. J. Durkin, “In vivo determination of skin near-infrared optical properties using diffuse optical spectroscopy,” J. Biomed. Opt. 13(1), 014016 (2008).
    [Crossref]
  36. M. Grasdalsmoen, H. R. Eriksen, K. J. Lonning, and B. Sivertsen, “Physical exercise and body-mass index in young adults: a national survey of Norwegian university students,” BMC Public Health 19(1), 1354 (2019).
    [Crossref]
  37. J. M. Johnson and M. K. Park, “Effect of heat stress on cutaneous vascular responses to the initiation of exercise,” J. Appl. Physiol. Respir. Environ. Exerc. Physiol. 53(3), 744–749 (1982).
    [Crossref]
  38. M. A. Black, D. J. Green, and N. T. Cable, “Exercise prevents age-related decline in nitric-oxide-mediated vasodilator function in cutaneous microvessels,” J. Physiol. 586(14), 3511–3524 (2008).
    [Crossref]
  39. M. F. Roberts, C. B. Wenger, J. A. Stolwijk, and E. R. Nadel, “Skin blood flow and sweating changes following exercise training and heat acclimation,” J. Appl. Physiol. 43(1), 133–137 (1977).
    [Crossref]
  40. J. Gonzalez-Alonso, C. Teller, S. L. Andersen, F. B. Jensen, T. Hyldig, and B. Nielsen, “Influence of body temperature on the development of fatigue during prolonged exercise in the heat,” J. Appl. Physiol. 86(3), 1032–1039 (1999).
    [Crossref]
  41. D. L. Kellogg Jr, J. M. Johnson, and W. A. Kosiba, “Competition between cutaneous active vasoconstriction and active vasodilation during exercise in humans,” Am. J. Physiol. 261(6), C1184–C1195 (1991).
    [Crossref]
  42. J. M. Johnson and D. W. Proppe, “Cardiovascular adjustments to heat stress,” The handbook of physiology, section 4: Environmental Physiology, Vol. 1, American Physiological Society; Bethesda, MD. Ch. 11, P 215 (1996).
  43. V. Carayanni, E. Vlachopadopoulou, D. Koutsouki, G. C. Bogdanis, T. Psaltopoulou, Y. Manios, F. Karachaliou, A. Hatzakis, and S. Michalacos, “Effects of body mass index (BMI), demographic and socioeconomic factors on organized physical activity (OPA) participation in children aged 6-15 years: a cross-sectional study comparing primary and secondary school children in Greece,” 20(1), 491 (2020).
  44. J. Smolander, P. Kolari, O. Korhonen, and R. Ilmarinen, “Skin blood flow during incremental exercise in a thermoneutral and a hot dry environment,” Eur. J. Appl. Physiol. 56(3), 273–280 (1987).
    [Crossref]
  45. S. Koga, D. C. Poole, N. Kondo, A. Oue, E. Ohmae, and T. J. Barstow, “Effects of increased skin blood flow on muscle oxygantion/deoxygenation: comparison of time-resolved and continuous-wave near-infrared spectroscopy singals,” Eur. J. Appl. Physiol. 115(2), 335–343 (2015).
    [Crossref]

2020 (1)

Y. Shimojo, T. Nishimura, H. Hazama, T. Ozawa, and K. Awazu, “Measurement of absorption and reduced scattering coefficients in Asian human epidermis, dermis, and subcutaneous fat tissues in the 400- to 1100-nm wavelength range for optical penetration depth and energy deposition analysis,” J. Biomed. Opt. 25(04), 1 (2020).
[Crossref]

2019 (1)

M. Grasdalsmoen, H. R. Eriksen, K. J. Lonning, and B. Sivertsen, “Physical exercise and body-mass index in young adults: a national survey of Norwegian university students,” BMC Public Health 19(1), 1354 (2019).
[Crossref]

2017 (1)

P. M. McClatchey, T. A. Bauer, J. G. Regensteiner, I. E. Schauer, A. G. Huebschmann, and J. E. B. Reusch, “Dissociation of local and global skeletal muscle oxygen transport metrics in type 2 diabetes,” J. Diabetes Complications 31(8), 1311–1317 (2017).
[Crossref]

2016 (2)

T. Del Rio, L. Valor, I. de la Torre, and E. Naredo, “Impact of the thickness of the subcutaneous tissue at the site of injection as measured by ultrasound on the therapeutic response to subcutaneous anti-tumour necrosis factor drugs,” Reumatol. Clin. 12(5), 300–301 (2016).
[Crossref]

Y. W. Chen, C. C. Chen, P. J. Huang, and S. H. Tseng, “Artificial neural networks for retrieving absorption and reduced scattering spectra from frequency-domain diffuse reflectance spectroscopy at short source-detector separation,” Biomed. Opt. Exp. 7(4), 1496–1510 (2016).
[Crossref]

2015 (1)

S. Koga, D. C. Poole, N. Kondo, A. Oue, E. Ohmae, and T. J. Barstow, “Effects of increased skin blood flow on muscle oxygantion/deoxygenation: comparison of time-resolved and continuous-wave near-infrared spectroscopy singals,” Eur. J. Appl. Physiol. 115(2), 335–343 (2015).
[Crossref]

2014 (2)

M. W. Lee, C. H. Hung, J. L. Liao, N. Y. Cheng, M. F. Hou, and S. H. Tseng, “A linear gradient line source facilitates the use of diffusion models with high order approximation for efficient, accurate turbid sample optical properties recovery,” Biomed. Opt. Express 5(10), 3628–3639 (2014).
[Crossref]

P.A. Beest, J. J. Vos, M. Poterman, A. F. Kalmar, and T. W. L. Scheeren, “Tissue oxygenation as a target for goal-directed therapy in high-risk surgery: a pilot study,” BMC Anesthesiology 14(1), 122 (2014).
[Crossref]

2013 (1)

J. D. Periard, M. W. Thompson, C. Caillaud, and V. Quaresima, “Influence of heat stress and exercise intensity on vastus lateralis muscle and prefrontal cortex oxygenation,” Eur. J. Appl. Physiol. 113(1), 211–222 (2013).
[Crossref]

2011 (4)

F. Esposito, V. Reese, R. Shabetai, P. D. Wagner, and R. S. Richardson, “Isolated quadriceps training increases maximal exercise capacity in chronic heart failure,” J. Am. Coll. Cardiol. 58(13), 1353–1362 (2011).
[Crossref]

W. L. Kenny and J. M. Johnson, “Control of skin blood flow during exercise,” Med. Sci. Sports Exerc. 96(9), 822–828 (2011).

M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Phil. Trans. Soc. 369(1955), 4577–4590 (2011).
[Crossref]

G. H. Simmons, B. J. Wong, L. A. Holowatz, and W. L. Kenney, “Changes in the control of skin blood flow with exercise training: where do cutaneous vascular adaptations fit in?” Exp. Physiol. 96(9), 822–828 (2011).
[Crossref]

2010 (1)

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref]

2008 (3)

P. G. Rodriguez, F. N. Felix, D. T. Woodley, and E. K. Shim, “The role of oxygen in wound healing: a review of the literature,” Dermatol. Surg. 34(9), 1159–1169 (2008).
[Crossref]

S. H. Tseng, A. Grant, and A. J. Durkin, “In vivo determination of skin near-infrared optical properties using diffuse optical spectroscopy,” J. Biomed. Opt. 13(1), 014016 (2008).
[Crossref]

M. A. Black, D. J. Green, and N. T. Cable, “Exercise prevents age-related decline in nitric-oxide-mediated vasodilator function in cutaneous microvessels,” J. Physiol. 586(14), 3511–3524 (2008).
[Crossref]

2007 (3)

L. F. Ferreira, D. M. Hueber, and T. J. Barstow, “Effects of assuming constant optical scattering on measurements of muscle oxygenation by near-infrared spectroscopy during exercise,” J. Appl. Physiol. 102(1), 358–367 (2007).
[Crossref]

T. Hamaoka, K. K. McCully, V. Quaresima, K. Yamamoto, and B. Chance, “Near-infrared spectroscopy/imaging for monitoring muscle oxygenation and oxidative metabolism in healthy and diseased humans,” J. Biomed. Opt. 12(6), 062105 (2007).
[Crossref]

Y. Yang, O. Soyemi, P. J. Scott, M. R. Landry, S. M. Lee, L. Stroud, and B. R. Soller, “Quantitative measurement of muscle oxygen saturation without influence from skin and fat using continuous-wave near infrared spectroscopy,” Opt. Express 15(21), 13715–13730 (2007).
[Crossref]

2006 (2)

J. Gozalez-Alonso, S. P. Mortensen, E. A. Dawson, N. H. Secher, and R. Damsgaard, “Erythrocytes and the regulation of human skeletal muscle blood flow and oxygen delivery: role of erythrocyte count and oxygenation state of haemoglobin,” J. Physiol. 572(1), 295–305 (2006).
[Crossref]

S. L. Davis, P. J. Fadel, J. Cui, G. D. Thomas, and C. G. Crandall, “Skin blood flow influences near-infrared spectroscopy-derived measurements of tissue oxygenation during heat stress,” J. Appl. Physiol. 100(1), 221–224 (2006).
[Crossref]

2005 (1)

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10(2), 024027 (2005).
[Crossref]

2004 (2)

V. Quaresima, M. Ferrari, M. A. Franceschini, M. L. Hoimes, and S. Fantini, “Spatial distribution of vastus lateralis blood flow and oxyhemoglobin saturation measured at the end of isometric quadriceps contraction by multichannel near-infrared spectroscopy,” J. Biomed. Opt. 9(2), 413–420 (2004).
[Crossref]

K.-M. Scheufler, “Tissue oxygenation and capacity to deliver O2 do the two go together?” Transfus Apher. Sci. 31(1), 45–54 (2004).
[Crossref]

2003 (2)

D. S. DeLorey, J. M. Kowalchuk, and D. H. Paterson, “Relationship between pulmonary O2 uptake kinetics and muscle deoxygenation during moderate-intensity exercise,” Js. Appl. Physiol. 95(1), 113–120 (2003).
[Crossref]

B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003).
[Crossref]

2001 (1)

M. C. van Beekvelt, M. S. Borghuis, B. G. van Engelen, R. A. Wevers, and W. N. Colier, “Adipose tissue thickness affects in vivo quantitative near-IR spectroscopy in human skeletal muscle,” Clin. Sci. 101(1), 21 (2001).
[Crossref]

1999 (5)

C. M. Thomas, J. M. Pierzga, and W. L. Kenney, “Aerobic training and cutaneous vasodilation in young and older men,” J. Appl. Physiol. 86(5), 1676–1686 (1999).
[Crossref]

A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, “Optical properties of circulating human blood in the wavelength range 400-2500 nm,” J. Biomed. Opt. 4(1), 36–46 (1999).
[Crossref]

M. J. MacDonald, M. A. Tarnopolsky, H. J. Green, and R. L. Hughson, “Comparison of femoral blood gases and muscle near-infrared spectroscopy at exercise onset in humans,” J. Appl. Physiol. 86(2), 687–693 (1999).
[Crossref]

B. Grassi, V. Quaresima, C. Marconi, M. Ferrari, and P. Cerretelli, “Blood lactate accumulation and muscle deoxygenation during incremental exercise,” J. Appl. Physiol. 87(1), 348–355 (1999).
[Crossref]

J. Gonzalez-Alonso, C. Teller, S. L. Andersen, F. B. Jensen, T. Hyldig, and B. Nielsen, “Influence of body temperature on the development of fatigue during prolonged exercise in the heat,” J. Appl. Physiol. 86(3), 1032–1039 (1999).
[Crossref]

1998 (1)

1997 (1)

C. W. Ho, J. L. Beard, P. A. Farrell, C. T. Minson, and W. L. Kenney, “Age, fitness, and regional blood flow during exercise in the heat,” J. Appl. Physiol. 82(4), 1126–1135 (1997).
[Crossref]

1994 (2)

R. A. Blasi, M. Ferrari, A. Natali, G. Conti, A. Mega, and A. Gasparetto, “Noninvasive measurement of forearm blood flow and oxygen consumption by near-infrared spectroscopy,” J. Appl. Physiol. 76(3), 1388–1393 (1994).
[Crossref]

R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. 11(10), 2727–2741 (1994).
[Crossref]

1991 (1)

D. L. Kellogg Jr, J. M. Johnson, and W. A. Kosiba, “Competition between cutaneous active vasoconstriction and active vasodilation during exercise in humans,” Am. J. Physiol. 261(6), C1184–C1195 (1991).
[Crossref]

1987 (1)

J. Smolander, P. Kolari, O. Korhonen, and R. Ilmarinen, “Skin blood flow during incremental exercise in a thermoneutral and a hot dry environment,” Eur. J. Appl. Physiol. 56(3), 273–280 (1987).
[Crossref]

1982 (1)

J. M. Johnson and M. K. Park, “Effect of heat stress on cutaneous vascular responses to the initiation of exercise,” J. Appl. Physiol. Respir. Environ. Exerc. Physiol. 53(3), 744–749 (1982).
[Crossref]

1977 (2)

M. F. Roberts, C. B. Wenger, J. A. Stolwijk, and E. R. Nadel, “Skin blood flow and sweating changes following exercise training and heat acclimation,” J. Appl. Physiol. 43(1), 133–137 (1977).
[Crossref]

F. F. Jobsis, “Noninvasive infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science 198(4323), 1264–1267 (1977).
[Crossref]

Andersen, S. L.

J. Gonzalez-Alonso, C. Teller, S. L. Andersen, F. B. Jensen, T. Hyldig, and B. Nielsen, “Influence of body temperature on the development of fatigue during prolonged exercise in the heat,” J. Appl. Physiol. 86(3), 1032–1039 (1999).
[Crossref]

Arango, M.

J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” Br. J. Anaesth. Suppl. 103, Suppl. 1, I3-I13 (2009).

Awazu, K.

Y. Shimojo, T. Nishimura, H. Hazama, T. Ozawa, and K. Awazu, “Measurement of absorption and reduced scattering coefficients in Asian human epidermis, dermis, and subcutaneous fat tissues in the 400- to 1100-nm wavelength range for optical penetration depth and energy deposition analysis,” J. Biomed. Opt. 25(04), 1 (2020).
[Crossref]

Baker, W. B.

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref]

Barstow, T. J.

S. Koga, D. C. Poole, N. Kondo, A. Oue, E. Ohmae, and T. J. Barstow, “Effects of increased skin blood flow on muscle oxygantion/deoxygenation: comparison of time-resolved and continuous-wave near-infrared spectroscopy singals,” Eur. J. Appl. Physiol. 115(2), 335–343 (2015).
[Crossref]

L. F. Ferreira, D. M. Hueber, and T. J. Barstow, “Effects of assuming constant optical scattering on measurements of muscle oxygenation by near-infrared spectroscopy during exercise,” J. Appl. Physiol. 102(1), 358–367 (2007).
[Crossref]

Bauer, T. A.

P. M. McClatchey, T. A. Bauer, J. G. Regensteiner, I. E. Schauer, A. G. Huebschmann, and J. E. B. Reusch, “Dissociation of local and global skeletal muscle oxygen transport metrics in type 2 diabetes,” J. Diabetes Complications 31(8), 1311–1317 (2017).
[Crossref]

Beard, J. L.

C. W. Ho, J. L. Beard, P. A. Farrell, C. T. Minson, and W. L. Kenney, “Age, fitness, and regional blood flow during exercise in the heat,” J. Appl. Physiol. 82(4), 1126–1135 (1997).
[Crossref]

Beest, P.A.

P.A. Beest, J. J. Vos, M. Poterman, A. F. Kalmar, and T. W. L. Scheeren, “Tissue oxygenation as a target for goal-directed therapy in high-risk surgery: a pilot study,” BMC Anesthesiology 14(1), 122 (2014).
[Crossref]

Black, M. A.

M. A. Black, D. J. Green, and N. T. Cable, “Exercise prevents age-related decline in nitric-oxide-mediated vasodilator function in cutaneous microvessels,” J. Physiol. 586(14), 3511–3524 (2008).
[Crossref]

Blasi, R. A.

R. A. Blasi, M. Ferrari, A. Natali, G. Conti, A. Mega, and A. Gasparetto, “Noninvasive measurement of forearm blood flow and oxygen consumption by near-infrared spectroscopy,” J. Appl. Physiol. 76(3), 1388–1393 (1994).
[Crossref]

Bogdanis, G. C.

V. Carayanni, E. Vlachopadopoulou, D. Koutsouki, G. C. Bogdanis, T. Psaltopoulou, Y. Manios, F. Karachaliou, A. Hatzakis, and S. Michalacos, “Effects of body mass index (BMI), demographic and socioeconomic factors on organized physical activity (OPA) participation in children aged 6-15 years: a cross-sectional study comparing primary and secondary school children in Greece,” 20(1), 491 (2020).

Borghuis, M. S.

M. C. van Beekvelt, M. S. Borghuis, B. G. van Engelen, R. A. Wevers, and W. N. Colier, “Adipose tissue thickness affects in vivo quantitative near-IR spectroscopy in human skeletal muscle,” Clin. Sci. 101(1), 21 (2001).
[Crossref]

Cable, N. T.

M. A. Black, D. J. Green, and N. T. Cable, “Exercise prevents age-related decline in nitric-oxide-mediated vasodilator function in cutaneous microvessels,” J. Physiol. 586(14), 3511–3524 (2008).
[Crossref]

Caillaud, C.

J. D. Periard, M. W. Thompson, C. Caillaud, and V. Quaresima, “Influence of heat stress and exercise intensity on vastus lateralis muscle and prefrontal cortex oxygenation,” Eur. J. Appl. Physiol. 113(1), 211–222 (2013).
[Crossref]

Carayanni, V.

V. Carayanni, E. Vlachopadopoulou, D. Koutsouki, G. C. Bogdanis, T. Psaltopoulou, Y. Manios, F. Karachaliou, A. Hatzakis, and S. Michalacos, “Effects of body mass index (BMI), demographic and socioeconomic factors on organized physical activity (OPA) participation in children aged 6-15 years: a cross-sectional study comparing primary and secondary school children in Greece,” 20(1), 491 (2020).

Cerretelli, P.

B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003).
[Crossref]

B. Grassi, V. Quaresima, C. Marconi, M. Ferrari, and P. Cerretelli, “Blood lactate accumulation and muscle deoxygenation during incremental exercise,” J. Appl. Physiol. 87(1), 348–355 (1999).
[Crossref]

Chance, B.

T. Hamaoka, K. K. McCully, V. Quaresima, K. Yamamoto, and B. Chance, “Near-infrared spectroscopy/imaging for monitoring muscle oxygenation and oxidative metabolism in healthy and diseased humans,” J. Biomed. Opt. 12(6), 062105 (2007).
[Crossref]

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10(2), 024027 (2005).
[Crossref]

Chen, C. C.

Y. W. Chen, C. C. Chen, P. J. Huang, and S. H. Tseng, “Artificial neural networks for retrieving absorption and reduced scattering spectra from frequency-domain diffuse reflectance spectroscopy at short source-detector separation,” Biomed. Opt. Exp. 7(4), 1496–1510 (2016).
[Crossref]

Chen, Y. W.

Y. W. Chen, C. C. Chen, P. J. Huang, and S. H. Tseng, “Artificial neural networks for retrieving absorption and reduced scattering spectra from frequency-domain diffuse reflectance spectroscopy at short source-detector separation,” Biomed. Opt. Exp. 7(4), 1496–1510 (2016).
[Crossref]

Cheng, N. Y.

Choe, R.

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref]

Colier, W. N.

M. C. van Beekvelt, M. S. Borghuis, B. G. van Engelen, R. A. Wevers, and W. N. Colier, “Adipose tissue thickness affects in vivo quantitative near-IR spectroscopy in human skeletal muscle,” Clin. Sci. 101(1), 21 (2001).
[Crossref]

Conti, G.

R. A. Blasi, M. Ferrari, A. Natali, G. Conti, A. Mega, and A. Gasparetto, “Noninvasive measurement of forearm blood flow and oxygen consumption by near-infrared spectroscopy,” J. Appl. Physiol. 76(3), 1388–1393 (1994).
[Crossref]

Crandall, C. G.

S. L. Davis, P. J. Fadel, J. Cui, G. D. Thomas, and C. G. Crandall, “Skin blood flow influences near-infrared spectroscopy-derived measurements of tissue oxygenation during heat stress,” J. Appl. Physiol. 100(1), 221–224 (2006).
[Crossref]

Cui, J.

S. L. Davis, P. J. Fadel, J. Cui, G. D. Thomas, and C. G. Crandall, “Skin blood flow influences near-infrared spectroscopy-derived measurements of tissue oxygenation during heat stress,” J. Appl. Physiol. 100(1), 221–224 (2006).
[Crossref]

Damsgaard, R.

J. Gozalez-Alonso, S. P. Mortensen, E. A. Dawson, N. H. Secher, and R. Damsgaard, “Erythrocytes and the regulation of human skeletal muscle blood flow and oxygen delivery: role of erythrocyte count and oxygenation state of haemoglobin,” J. Physiol. 572(1), 295–305 (2006).
[Crossref]

Davis, S. L.

S. L. Davis, P. J. Fadel, J. Cui, G. D. Thomas, and C. G. Crandall, “Skin blood flow influences near-infrared spectroscopy-derived measurements of tissue oxygenation during heat stress,” J. Appl. Physiol. 100(1), 221–224 (2006).
[Crossref]

Dawson, E. A.

J. Gozalez-Alonso, S. P. Mortensen, E. A. Dawson, N. H. Secher, and R. Damsgaard, “Erythrocytes and the regulation of human skeletal muscle blood flow and oxygen delivery: role of erythrocyte count and oxygenation state of haemoglobin,” J. Physiol. 572(1), 295–305 (2006).
[Crossref]

de la Torre, I.

T. Del Rio, L. Valor, I. de la Torre, and E. Naredo, “Impact of the thickness of the subcutaneous tissue at the site of injection as measured by ultrasound on the therapeutic response to subcutaneous anti-tumour necrosis factor drugs,” Reumatol. Clin. 12(5), 300–301 (2016).
[Crossref]

Del Rio, T.

T. Del Rio, L. Valor, I. de la Torre, and E. Naredo, “Impact of the thickness of the subcutaneous tissue at the site of injection as measured by ultrasound on the therapeutic response to subcutaneous anti-tumour necrosis factor drugs,” Reumatol. Clin. 12(5), 300–301 (2016).
[Crossref]

DeLorey, D. S.

D. S. DeLorey, J. M. Kowalchuk, and D. H. Paterson, “Relationship between pulmonary O2 uptake kinetics and muscle deoxygenation during moderate-intensity exercise,” Js. Appl. Physiol. 95(1), 113–120 (2003).
[Crossref]

Dorschel, K.

A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, “Optical properties of circulating human blood in the wavelength range 400-2500 nm,” J. Biomed. Opt. 4(1), 36–46 (1999).
[Crossref]

Durduran, T.

T. Durduran, R. Choe, W. B. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73(7), 076701 (2010).
[Crossref]

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10(2), 024027 (2005).
[Crossref]

Durkin, A. J.

S. H. Tseng, A. Grant, and A. J. Durkin, “In vivo determination of skin near-infrared optical properties using diffuse optical spectroscopy,” J. Biomed. Opt. 13(1), 014016 (2008).
[Crossref]

Eriksen, H. R.

M. Grasdalsmoen, H. R. Eriksen, K. J. Lonning, and B. Sivertsen, “Physical exercise and body-mass index in young adults: a national survey of Norwegian university students,” BMC Public Health 19(1), 1354 (2019).
[Crossref]

Esposito, F.

F. Esposito, V. Reese, R. Shabetai, P. D. Wagner, and R. S. Richardson, “Isolated quadriceps training increases maximal exercise capacity in chronic heart failure,” J. Am. Coll. Cardiol. 58(13), 1353–1362 (2011).
[Crossref]

Fadel, P. J.

S. L. Davis, P. J. Fadel, J. Cui, G. D. Thomas, and C. G. Crandall, “Skin blood flow influences near-infrared spectroscopy-derived measurements of tissue oxygenation during heat stress,” J. Appl. Physiol. 100(1), 221–224 (2006).
[Crossref]

Fantini, S.

V. Quaresima, M. Ferrari, M. A. Franceschini, M. L. Hoimes, and S. Fantini, “Spatial distribution of vastus lateralis blood flow and oxyhemoglobin saturation measured at the end of isometric quadriceps contraction by multichannel near-infrared spectroscopy,” J. Biomed. Opt. 9(2), 413–420 (2004).
[Crossref]

M. A. Franceschini, S. Fantini, L. A. Paunescu, J. S. Maier, and E. Gratton, “Influence of a superficial layer in the quantitative spectroscopic study of strongly scattering media,” Appl. Opt. 37(31), 7447–7458 (1998).
[Crossref]

Farrell, P. A.

C. W. Ho, J. L. Beard, P. A. Farrell, C. T. Minson, and W. L. Kenney, “Age, fitness, and regional blood flow during exercise in the heat,” J. Appl. Physiol. 82(4), 1126–1135 (1997).
[Crossref]

Felix, F. N.

P. G. Rodriguez, F. N. Felix, D. T. Woodley, and E. K. Shim, “The role of oxygen in wound healing: a review of the literature,” Dermatol. Surg. 34(9), 1159–1169 (2008).
[Crossref]

Feng, T. C.

R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. 11(10), 2727–2741 (1994).
[Crossref]

Ferrari, M.

M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Phil. Trans. Soc. 369(1955), 4577–4590 (2011).
[Crossref]

V. Quaresima, M. Ferrari, M. A. Franceschini, M. L. Hoimes, and S. Fantini, “Spatial distribution of vastus lateralis blood flow and oxyhemoglobin saturation measured at the end of isometric quadriceps contraction by multichannel near-infrared spectroscopy,” J. Biomed. Opt. 9(2), 413–420 (2004).
[Crossref]

B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003).
[Crossref]

B. Grassi, V. Quaresima, C. Marconi, M. Ferrari, and P. Cerretelli, “Blood lactate accumulation and muscle deoxygenation during incremental exercise,” J. Appl. Physiol. 87(1), 348–355 (1999).
[Crossref]

R. A. Blasi, M. Ferrari, A. Natali, G. Conti, A. Mega, and A. Gasparetto, “Noninvasive measurement of forearm blood flow and oxygen consumption by near-infrared spectroscopy,” J. Appl. Physiol. 76(3), 1388–1393 (1994).
[Crossref]

Ferreira, L. F.

L. F. Ferreira, D. M. Hueber, and T. J. Barstow, “Effects of assuming constant optical scattering on measurements of muscle oxygenation by near-infrared spectroscopy during exercise,” J. Appl. Physiol. 102(1), 358–367 (2007).
[Crossref]

Franceschini, M. A.

V. Quaresima, M. Ferrari, M. A. Franceschini, M. L. Hoimes, and S. Fantini, “Spatial distribution of vastus lateralis blood flow and oxyhemoglobin saturation measured at the end of isometric quadriceps contraction by multichannel near-infrared spectroscopy,” J. Biomed. Opt. 9(2), 413–420 (2004).
[Crossref]

M. A. Franceschini, S. Fantini, L. A. Paunescu, J. S. Maier, and E. Gratton, “Influence of a superficial layer in the quantitative spectroscopic study of strongly scattering media,” Appl. Opt. 37(31), 7447–7458 (1998).
[Crossref]

Friebel, M.

A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, “Optical properties of circulating human blood in the wavelength range 400-2500 nm,” J. Biomed. Opt. 4(1), 36–46 (1999).
[Crossref]

Gasparetto, A.

R. A. Blasi, M. Ferrari, A. Natali, G. Conti, A. Mega, and A. Gasparetto, “Noninvasive measurement of forearm blood flow and oxygen consumption by near-infrared spectroscopy,” J. Appl. Physiol. 76(3), 1388–1393 (1994).
[Crossref]

Gonzalez-Alonso, J.

J. Gonzalez-Alonso, C. Teller, S. L. Andersen, F. B. Jensen, T. Hyldig, and B. Nielsen, “Influence of body temperature on the development of fatigue during prolonged exercise in the heat,” J. Appl. Physiol. 86(3), 1032–1039 (1999).
[Crossref]

Gozalez-Alonso, J.

J. Gozalez-Alonso, S. P. Mortensen, E. A. Dawson, N. H. Secher, and R. Damsgaard, “Erythrocytes and the regulation of human skeletal muscle blood flow and oxygen delivery: role of erythrocyte count and oxygenation state of haemoglobin,” J. Physiol. 572(1), 295–305 (2006).
[Crossref]

Grant, A.

S. H. Tseng, A. Grant, and A. J. Durkin, “In vivo determination of skin near-infrared optical properties using diffuse optical spectroscopy,” J. Biomed. Opt. 13(1), 014016 (2008).
[Crossref]

Grasdalsmoen, M.

M. Grasdalsmoen, H. R. Eriksen, K. J. Lonning, and B. Sivertsen, “Physical exercise and body-mass index in young adults: a national survey of Norwegian university students,” BMC Public Health 19(1), 1354 (2019).
[Crossref]

Grassi, B.

B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003).
[Crossref]

B. Grassi, V. Quaresima, C. Marconi, M. Ferrari, and P. Cerretelli, “Blood lactate accumulation and muscle deoxygenation during incremental exercise,” J. Appl. Physiol. 87(1), 348–355 (1999).
[Crossref]

Gratton, E.

Green, D. J.

M. A. Black, D. J. Green, and N. T. Cable, “Exercise prevents age-related decline in nitric-oxide-mediated vasodilator function in cutaneous microvessels,” J. Physiol. 586(14), 3511–3524 (2008).
[Crossref]

Green, H. J.

M. J. MacDonald, M. A. Tarnopolsky, H. J. Green, and R. L. Hughson, “Comparison of femoral blood gases and muscle near-infrared spectroscopy at exercise onset in humans,” J. Appl. Physiol. 86(2), 687–693 (1999).
[Crossref]

Hahn, A.

A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, “Optical properties of circulating human blood in the wavelength range 400-2500 nm,” J. Biomed. Opt. 4(1), 36–46 (1999).
[Crossref]

Hamaoka, T.

T. Hamaoka, K. K. McCully, V. Quaresima, K. Yamamoto, and B. Chance, “Near-infrared spectroscopy/imaging for monitoring muscle oxygenation and oxidative metabolism in healthy and diseased humans,” J. Biomed. Opt. 12(6), 062105 (2007).
[Crossref]

Haskell, R. C.

R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. 11(10), 2727–2741 (1994).
[Crossref]

Hatzakis, A.

V. Carayanni, E. Vlachopadopoulou, D. Koutsouki, G. C. Bogdanis, T. Psaltopoulou, Y. Manios, F. Karachaliou, A. Hatzakis, and S. Michalacos, “Effects of body mass index (BMI), demographic and socioeconomic factors on organized physical activity (OPA) participation in children aged 6-15 years: a cross-sectional study comparing primary and secondary school children in Greece,” 20(1), 491 (2020).

Hazama, H.

Y. Shimojo, T. Nishimura, H. Hazama, T. Ozawa, and K. Awazu, “Measurement of absorption and reduced scattering coefficients in Asian human epidermis, dermis, and subcutaneous fat tissues in the 400- to 1100-nm wavelength range for optical penetration depth and energy deposition analysis,” J. Biomed. Opt. 25(04), 1 (2020).
[Crossref]

Ho, C. W.

C. W. Ho, J. L. Beard, P. A. Farrell, C. T. Minson, and W. L. Kenney, “Age, fitness, and regional blood flow during exercise in the heat,” J. Appl. Physiol. 82(4), 1126–1135 (1997).
[Crossref]

Hoimes, M. L.

V. Quaresima, M. Ferrari, M. A. Franceschini, M. L. Hoimes, and S. Fantini, “Spatial distribution of vastus lateralis blood flow and oxyhemoglobin saturation measured at the end of isometric quadriceps contraction by multichannel near-infrared spectroscopy,” J. Biomed. Opt. 9(2), 413–420 (2004).
[Crossref]

Holowatz, L. A.

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M. J. MacDonald, M. A. Tarnopolsky, H. J. Green, and R. L. Hughson, “Comparison of femoral blood gases and muscle near-infrared spectroscopy at exercise onset in humans,” J. Appl. Physiol. 86(2), 687–693 (1999).
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J. Gonzalez-Alonso, C. Teller, S. L. Andersen, F. B. Jensen, T. Hyldig, and B. Nielsen, “Influence of body temperature on the development of fatigue during prolonged exercise in the heat,” J. Appl. Physiol. 86(3), 1032–1039 (1999).
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J. Smolander, P. Kolari, O. Korhonen, and R. Ilmarinen, “Skin blood flow during incremental exercise in a thermoneutral and a hot dry environment,” Eur. J. Appl. Physiol. 56(3), 273–280 (1987).
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J. Gonzalez-Alonso, C. Teller, S. L. Andersen, F. B. Jensen, T. Hyldig, and B. Nielsen, “Influence of body temperature on the development of fatigue during prolonged exercise in the heat,” J. Appl. Physiol. 86(3), 1032–1039 (1999).
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W. L. Kenny and J. M. Johnson, “Control of skin blood flow during exercise,” Med. Sci. Sports Exerc. 96(9), 822–828 (2011).

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J. M. Johnson and M. K. Park, “Effect of heat stress on cutaneous vascular responses to the initiation of exercise,” J. Appl. Physiol. Respir. Environ. Exerc. Physiol. 53(3), 744–749 (1982).
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J. M. Johnson and D. W. Proppe, “Cardiovascular adjustments to heat stress,” The handbook of physiology, section 4: Environmental Physiology, Vol. 1, American Physiological Society; Bethesda, MD. Ch. 11, P 215 (1996).

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P.A. Beest, J. J. Vos, M. Poterman, A. F. Kalmar, and T. W. L. Scheeren, “Tissue oxygenation as a target for goal-directed therapy in high-risk surgery: a pilot study,” BMC Anesthesiology 14(1), 122 (2014).
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Kellogg Jr, D. L.

D. L. Kellogg Jr, J. M. Johnson, and W. A. Kosiba, “Competition between cutaneous active vasoconstriction and active vasodilation during exercise in humans,” Am. J. Physiol. 261(6), C1184–C1195 (1991).
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G. H. Simmons, B. J. Wong, L. A. Holowatz, and W. L. Kenney, “Changes in the control of skin blood flow with exercise training: where do cutaneous vascular adaptations fit in?” Exp. Physiol. 96(9), 822–828 (2011).
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C. M. Thomas, J. M. Pierzga, and W. L. Kenney, “Aerobic training and cutaneous vasodilation in young and older men,” J. Appl. Physiol. 86(5), 1676–1686 (1999).
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C. W. Ho, J. L. Beard, P. A. Farrell, C. T. Minson, and W. L. Kenney, “Age, fitness, and regional blood flow during exercise in the heat,” J. Appl. Physiol. 82(4), 1126–1135 (1997).
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W. L. Kenny and J. M. Johnson, “Control of skin blood flow during exercise,” Med. Sci. Sports Exerc. 96(9), 822–828 (2011).

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S. Koga, D. C. Poole, N. Kondo, A. Oue, E. Ohmae, and T. J. Barstow, “Effects of increased skin blood flow on muscle oxygantion/deoxygenation: comparison of time-resolved and continuous-wave near-infrared spectroscopy singals,” Eur. J. Appl. Physiol. 115(2), 335–343 (2015).
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Kolari, P.

J. Smolander, P. Kolari, O. Korhonen, and R. Ilmarinen, “Skin blood flow during incremental exercise in a thermoneutral and a hot dry environment,” Eur. J. Appl. Physiol. 56(3), 273–280 (1987).
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S. Koga, D. C. Poole, N. Kondo, A. Oue, E. Ohmae, and T. J. Barstow, “Effects of increased skin blood flow on muscle oxygantion/deoxygenation: comparison of time-resolved and continuous-wave near-infrared spectroscopy singals,” Eur. J. Appl. Physiol. 115(2), 335–343 (2015).
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Korhonen, O.

J. Smolander, P. Kolari, O. Korhonen, and R. Ilmarinen, “Skin blood flow during incremental exercise in a thermoneutral and a hot dry environment,” Eur. J. Appl. Physiol. 56(3), 273–280 (1987).
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Kosiba, W. A.

D. L. Kellogg Jr, J. M. Johnson, and W. A. Kosiba, “Competition between cutaneous active vasoconstriction and active vasodilation during exercise in humans,” Am. J. Physiol. 261(6), C1184–C1195 (1991).
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Koutsouki, D.

V. Carayanni, E. Vlachopadopoulou, D. Koutsouki, G. C. Bogdanis, T. Psaltopoulou, Y. Manios, F. Karachaliou, A. Hatzakis, and S. Michalacos, “Effects of body mass index (BMI), demographic and socioeconomic factors on organized physical activity (OPA) participation in children aged 6-15 years: a cross-sectional study comparing primary and secondary school children in Greece,” 20(1), 491 (2020).

Kowalchuk, J. M.

D. S. DeLorey, J. M. Kowalchuk, and D. H. Paterson, “Relationship between pulmonary O2 uptake kinetics and muscle deoxygenation during moderate-intensity exercise,” Js. Appl. Physiol. 95(1), 113–120 (2003).
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Lech, G.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10(2), 024027 (2005).
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Lee, S. M.

Liao, J. L.

Lonning, K. J.

M. Grasdalsmoen, H. R. Eriksen, K. J. Lonning, and B. Sivertsen, “Physical exercise and body-mass index in young adults: a national survey of Norwegian university students,” BMC Public Health 19(1), 1354 (2019).
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M. J. MacDonald, M. A. Tarnopolsky, H. J. Green, and R. L. Hughson, “Comparison of femoral blood gases and muscle near-infrared spectroscopy at exercise onset in humans,” J. Appl. Physiol. 86(2), 687–693 (1999).
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Maier, J. S.

Manios, Y.

V. Carayanni, E. Vlachopadopoulou, D. Koutsouki, G. C. Bogdanis, T. Psaltopoulou, Y. Manios, F. Karachaliou, A. Hatzakis, and S. Michalacos, “Effects of body mass index (BMI), demographic and socioeconomic factors on organized physical activity (OPA) participation in children aged 6-15 years: a cross-sectional study comparing primary and secondary school children in Greece,” 20(1), 491 (2020).

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B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003).
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B. Grassi, V. Quaresima, C. Marconi, M. Ferrari, and P. Cerretelli, “Blood lactate accumulation and muscle deoxygenation during incremental exercise,” J. Appl. Physiol. 87(1), 348–355 (1999).
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McAdams, M. S.

R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. 11(10), 2727–2741 (1994).
[Crossref]

McClatchey, P. M.

P. M. McClatchey, T. A. Bauer, J. G. Regensteiner, I. E. Schauer, A. G. Huebschmann, and J. E. B. Reusch, “Dissociation of local and global skeletal muscle oxygen transport metrics in type 2 diabetes,” J. Diabetes Complications 31(8), 1311–1317 (2017).
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McCully, K. K.

T. Hamaoka, K. K. McCully, V. Quaresima, K. Yamamoto, and B. Chance, “Near-infrared spectroscopy/imaging for monitoring muscle oxygenation and oxidative metabolism in healthy and diseased humans,” J. Biomed. Opt. 12(6), 062105 (2007).
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Mega, A.

R. A. Blasi, M. Ferrari, A. Natali, G. Conti, A. Mega, and A. Gasparetto, “Noninvasive measurement of forearm blood flow and oxygen consumption by near-infrared spectroscopy,” J. Appl. Physiol. 76(3), 1388–1393 (1994).
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V. Carayanni, E. Vlachopadopoulou, D. Koutsouki, G. C. Bogdanis, T. Psaltopoulou, Y. Manios, F. Karachaliou, A. Hatzakis, and S. Michalacos, “Effects of body mass index (BMI), demographic and socioeconomic factors on organized physical activity (OPA) participation in children aged 6-15 years: a cross-sectional study comparing primary and secondary school children in Greece,” 20(1), 491 (2020).

Minson, C. T.

C. W. Ho, J. L. Beard, P. A. Farrell, C. T. Minson, and W. L. Kenney, “Age, fitness, and regional blood flow during exercise in the heat,” J. Appl. Physiol. 82(4), 1126–1135 (1997).
[Crossref]

Mohler, E. R.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10(2), 024027 (2005).
[Crossref]

Mortensen, S. P.

J. Gozalez-Alonso, S. P. Mortensen, E. A. Dawson, N. H. Secher, and R. Damsgaard, “Erythrocytes and the regulation of human skeletal muscle blood flow and oxygen delivery: role of erythrocyte count and oxygenation state of haemoglobin,” J. Physiol. 572(1), 295–305 (2006).
[Crossref]

Muller, G.

A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, “Optical properties of circulating human blood in the wavelength range 400-2500 nm,” J. Biomed. Opt. 4(1), 36–46 (1999).
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J. M. Murkin and M. Arango, “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” Br. J. Anaesth. Suppl. 103, Suppl. 1, I3-I13 (2009).

Muthalib, M.

M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Phil. Trans. Soc. 369(1955), 4577–4590 (2011).
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Nadel, E. R.

M. F. Roberts, C. B. Wenger, J. A. Stolwijk, and E. R. Nadel, “Skin blood flow and sweating changes following exercise training and heat acclimation,” J. Appl. Physiol. 43(1), 133–137 (1977).
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T. Del Rio, L. Valor, I. de la Torre, and E. Naredo, “Impact of the thickness of the subcutaneous tissue at the site of injection as measured by ultrasound on the therapeutic response to subcutaneous anti-tumour necrosis factor drugs,” Reumatol. Clin. 12(5), 300–301 (2016).
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Natali, A.

R. A. Blasi, M. Ferrari, A. Natali, G. Conti, A. Mega, and A. Gasparetto, “Noninvasive measurement of forearm blood flow and oxygen consumption by near-infrared spectroscopy,” J. Appl. Physiol. 76(3), 1388–1393 (1994).
[Crossref]

Nielsen, B.

J. Gonzalez-Alonso, C. Teller, S. L. Andersen, F. B. Jensen, T. Hyldig, and B. Nielsen, “Influence of body temperature on the development of fatigue during prolonged exercise in the heat,” J. Appl. Physiol. 86(3), 1032–1039 (1999).
[Crossref]

Nishimura, T.

Y. Shimojo, T. Nishimura, H. Hazama, T. Ozawa, and K. Awazu, “Measurement of absorption and reduced scattering coefficients in Asian human epidermis, dermis, and subcutaneous fat tissues in the 400- to 1100-nm wavelength range for optical penetration depth and energy deposition analysis,” J. Biomed. Opt. 25(04), 1 (2020).
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Ohmae, E.

S. Koga, D. C. Poole, N. Kondo, A. Oue, E. Ohmae, and T. J. Barstow, “Effects of increased skin blood flow on muscle oxygantion/deoxygenation: comparison of time-resolved and continuous-wave near-infrared spectroscopy singals,” Eur. J. Appl. Physiol. 115(2), 335–343 (2015).
[Crossref]

Oue, A.

S. Koga, D. C. Poole, N. Kondo, A. Oue, E. Ohmae, and T. J. Barstow, “Effects of increased skin blood flow on muscle oxygantion/deoxygenation: comparison of time-resolved and continuous-wave near-infrared spectroscopy singals,” Eur. J. Appl. Physiol. 115(2), 335–343 (2015).
[Crossref]

Ozawa, T.

Y. Shimojo, T. Nishimura, H. Hazama, T. Ozawa, and K. Awazu, “Measurement of absorption and reduced scattering coefficients in Asian human epidermis, dermis, and subcutaneous fat tissues in the 400- to 1100-nm wavelength range for optical penetration depth and energy deposition analysis,” J. Biomed. Opt. 25(04), 1 (2020).
[Crossref]

Park, M. K.

J. M. Johnson and M. K. Park, “Effect of heat stress on cutaneous vascular responses to the initiation of exercise,” J. Appl. Physiol. Respir. Environ. Exerc. Physiol. 53(3), 744–749 (1982).
[Crossref]

Paterson, D. H.

D. S. DeLorey, J. M. Kowalchuk, and D. H. Paterson, “Relationship between pulmonary O2 uptake kinetics and muscle deoxygenation during moderate-intensity exercise,” Js. Appl. Physiol. 95(1), 113–120 (2003).
[Crossref]

Paunescu, L. A.

Periard, J. D.

J. D. Periard, M. W. Thompson, C. Caillaud, and V. Quaresima, “Influence of heat stress and exercise intensity on vastus lateralis muscle and prefrontal cortex oxygenation,” Eur. J. Appl. Physiol. 113(1), 211–222 (2013).
[Crossref]

Pierzga, J. M.

C. M. Thomas, J. M. Pierzga, and W. L. Kenney, “Aerobic training and cutaneous vasodilation in young and older men,” J. Appl. Physiol. 86(5), 1676–1686 (1999).
[Crossref]

Pogliaghi, S.

B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003).
[Crossref]

Poole, D. C.

S. Koga, D. C. Poole, N. Kondo, A. Oue, E. Ohmae, and T. J. Barstow, “Effects of increased skin blood flow on muscle oxygantion/deoxygenation: comparison of time-resolved and continuous-wave near-infrared spectroscopy singals,” Eur. J. Appl. Physiol. 115(2), 335–343 (2015).
[Crossref]

Poterman, M.

P.A. Beest, J. J. Vos, M. Poterman, A. F. Kalmar, and T. W. L. Scheeren, “Tissue oxygenation as a target for goal-directed therapy in high-risk surgery: a pilot study,” BMC Anesthesiology 14(1), 122 (2014).
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Proppe, D. W.

J. M. Johnson and D. W. Proppe, “Cardiovascular adjustments to heat stress,” The handbook of physiology, section 4: Environmental Physiology, Vol. 1, American Physiological Society; Bethesda, MD. Ch. 11, P 215 (1996).

Psaltopoulou, T.

V. Carayanni, E. Vlachopadopoulou, D. Koutsouki, G. C. Bogdanis, T. Psaltopoulou, Y. Manios, F. Karachaliou, A. Hatzakis, and S. Michalacos, “Effects of body mass index (BMI), demographic and socioeconomic factors on organized physical activity (OPA) participation in children aged 6-15 years: a cross-sectional study comparing primary and secondary school children in Greece,” 20(1), 491 (2020).

Quaresima, V.

J. D. Periard, M. W. Thompson, C. Caillaud, and V. Quaresima, “Influence of heat stress and exercise intensity on vastus lateralis muscle and prefrontal cortex oxygenation,” Eur. J. Appl. Physiol. 113(1), 211–222 (2013).
[Crossref]

M. Ferrari, M. Muthalib, and V. Quaresima, “The use of near-infrared spectroscopy in understanding skeletal muscle physiology: recent developments,” Phil. Trans. Soc. 369(1955), 4577–4590 (2011).
[Crossref]

T. Hamaoka, K. K. McCully, V. Quaresima, K. Yamamoto, and B. Chance, “Near-infrared spectroscopy/imaging for monitoring muscle oxygenation and oxidative metabolism in healthy and diseased humans,” J. Biomed. Opt. 12(6), 062105 (2007).
[Crossref]

V. Quaresima, M. Ferrari, M. A. Franceschini, M. L. Hoimes, and S. Fantini, “Spatial distribution of vastus lateralis blood flow and oxyhemoglobin saturation measured at the end of isometric quadriceps contraction by multichannel near-infrared spectroscopy,” J. Biomed. Opt. 9(2), 413–420 (2004).
[Crossref]

B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003).
[Crossref]

B. Grassi, V. Quaresima, C. Marconi, M. Ferrari, and P. Cerretelli, “Blood lactate accumulation and muscle deoxygenation during incremental exercise,” J. Appl. Physiol. 87(1), 348–355 (1999).
[Crossref]

Rampichini, S.

B. Grassi, S. Pogliaghi, S. Rampichini, V. Quaresima, M. Ferrari, C. Marconi, and P. Cerretelli, “Muscle oxygenation and pulmonary gas exchange kinetics during cycling exercise on-transitions in humans,” J. Appl. Physiol. 95(1), 149–158 (2003).
[Crossref]

Reese, V.

F. Esposito, V. Reese, R. Shabetai, P. D. Wagner, and R. S. Richardson, “Isolated quadriceps training increases maximal exercise capacity in chronic heart failure,” J. Am. Coll. Cardiol. 58(13), 1353–1362 (2011).
[Crossref]

Regensteiner, J. G.

P. M. McClatchey, T. A. Bauer, J. G. Regensteiner, I. E. Schauer, A. G. Huebschmann, and J. E. B. Reusch, “Dissociation of local and global skeletal muscle oxygen transport metrics in type 2 diabetes,” J. Diabetes Complications 31(8), 1311–1317 (2017).
[Crossref]

Reusch, J. E. B.

P. M. McClatchey, T. A. Bauer, J. G. Regensteiner, I. E. Schauer, A. G. Huebschmann, and J. E. B. Reusch, “Dissociation of local and global skeletal muscle oxygen transport metrics in type 2 diabetes,” J. Diabetes Complications 31(8), 1311–1317 (2017).
[Crossref]

Richardson, R. S.

F. Esposito, V. Reese, R. Shabetai, P. D. Wagner, and R. S. Richardson, “Isolated quadriceps training increases maximal exercise capacity in chronic heart failure,” J. Am. Coll. Cardiol. 58(13), 1353–1362 (2011).
[Crossref]

Roberts, M. F.

M. F. Roberts, C. B. Wenger, J. A. Stolwijk, and E. R. Nadel, “Skin blood flow and sweating changes following exercise training and heat acclimation,” J. Appl. Physiol. 43(1), 133–137 (1977).
[Crossref]

Rodriguez, P. G.

P. G. Rodriguez, F. N. Felix, D. T. Woodley, and E. K. Shim, “The role of oxygen in wound healing: a review of the literature,” Dermatol. Surg. 34(9), 1159–1169 (2008).
[Crossref]

Roggan, A.

A. Roggan, M. Friebel, K. Dorschel, A. Hahn, and G. Muller, “Optical properties of circulating human blood in the wavelength range 400-2500 nm,” J. Biomed. Opt. 4(1), 36–46 (1999).
[Crossref]

Schauer, I. E.

P. M. McClatchey, T. A. Bauer, J. G. Regensteiner, I. E. Schauer, A. G. Huebschmann, and J. E. B. Reusch, “Dissociation of local and global skeletal muscle oxygen transport metrics in type 2 diabetes,” J. Diabetes Complications 31(8), 1311–1317 (2017).
[Crossref]

Scheeren, T. W. L.

P.A. Beest, J. J. Vos, M. Poterman, A. F. Kalmar, and T. W. L. Scheeren, “Tissue oxygenation as a target for goal-directed therapy in high-risk surgery: a pilot study,” BMC Anesthesiology 14(1), 122 (2014).
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K.-M. Scheufler, “Tissue oxygenation and capacity to deliver O2 do the two go together?” Transfus Apher. Sci. 31(1), 45–54 (2004).
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Scott, P. J.

Secher, N. H.

J. Gozalez-Alonso, S. P. Mortensen, E. A. Dawson, N. H. Secher, and R. Damsgaard, “Erythrocytes and the regulation of human skeletal muscle blood flow and oxygen delivery: role of erythrocyte count and oxygenation state of haemoglobin,” J. Physiol. 572(1), 295–305 (2006).
[Crossref]

Shabetai, R.

F. Esposito, V. Reese, R. Shabetai, P. D. Wagner, and R. S. Richardson, “Isolated quadriceps training increases maximal exercise capacity in chronic heart failure,” J. Am. Coll. Cardiol. 58(13), 1353–1362 (2011).
[Crossref]

Shim, E. K.

P. G. Rodriguez, F. N. Felix, D. T. Woodley, and E. K. Shim, “The role of oxygen in wound healing: a review of the literature,” Dermatol. Surg. 34(9), 1159–1169 (2008).
[Crossref]

Shimojo, Y.

Y. Shimojo, T. Nishimura, H. Hazama, T. Ozawa, and K. Awazu, “Measurement of absorption and reduced scattering coefficients in Asian human epidermis, dermis, and subcutaneous fat tissues in the 400- to 1100-nm wavelength range for optical penetration depth and energy deposition analysis,” J. Biomed. Opt. 25(04), 1 (2020).
[Crossref]

Simmons, G. H.

G. H. Simmons, B. J. Wong, L. A. Holowatz, and W. L. Kenney, “Changes in the control of skin blood flow with exercise training: where do cutaneous vascular adaptations fit in?” Exp. Physiol. 96(9), 822–828 (2011).
[Crossref]

Sivertsen, B.

M. Grasdalsmoen, H. R. Eriksen, K. J. Lonning, and B. Sivertsen, “Physical exercise and body-mass index in young adults: a national survey of Norwegian university students,” BMC Public Health 19(1), 1354 (2019).
[Crossref]

Smolander, J.

J. Smolander, P. Kolari, O. Korhonen, and R. Ilmarinen, “Skin blood flow during incremental exercise in a thermoneutral and a hot dry environment,” Eur. J. Appl. Physiol. 56(3), 273–280 (1987).
[Crossref]

Soller, B. R.

Soyemi, O.

Stolwijk, J. A.

M. F. Roberts, C. B. Wenger, J. A. Stolwijk, and E. R. Nadel, “Skin blood flow and sweating changes following exercise training and heat acclimation,” J. Appl. Physiol. 43(1), 133–137 (1977).
[Crossref]

Stroud, L.

Svaasand, L. O.

R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. 11(10), 2727–2741 (1994).
[Crossref]

Tarnopolsky, M. A.

M. J. MacDonald, M. A. Tarnopolsky, H. J. Green, and R. L. Hughson, “Comparison of femoral blood gases and muscle near-infrared spectroscopy at exercise onset in humans,” J. Appl. Physiol. 86(2), 687–693 (1999).
[Crossref]

Teller, C.

J. Gonzalez-Alonso, C. Teller, S. L. Andersen, F. B. Jensen, T. Hyldig, and B. Nielsen, “Influence of body temperature on the development of fatigue during prolonged exercise in the heat,” J. Appl. Physiol. 86(3), 1032–1039 (1999).
[Crossref]

Thomas, C. M.

C. M. Thomas, J. M. Pierzga, and W. L. Kenney, “Aerobic training and cutaneous vasodilation in young and older men,” J. Appl. Physiol. 86(5), 1676–1686 (1999).
[Crossref]

Thomas, G. D.

S. L. Davis, P. J. Fadel, J. Cui, G. D. Thomas, and C. G. Crandall, “Skin blood flow influences near-infrared spectroscopy-derived measurements of tissue oxygenation during heat stress,” J. Appl. Physiol. 100(1), 221–224 (2006).
[Crossref]

Thompson, M. W.

J. D. Periard, M. W. Thompson, C. Caillaud, and V. Quaresima, “Influence of heat stress and exercise intensity on vastus lateralis muscle and prefrontal cortex oxygenation,” Eur. J. Appl. Physiol. 113(1), 211–222 (2013).
[Crossref]

Tromberg, B. J.

R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. 11(10), 2727–2741 (1994).
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Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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Figures (8)

Fig. 1.
Fig. 1. Component-level schematic diagram of three-wavelength FD DRS system. This system is comprised of the modules of radio frequency (RF) electronics, laser diodes and controls, optical probe for sample interrogation and optoelectronic receiver. Blue and red line paths indicate electronic and optical routes. LM, IOF, DOF and BPF stand for laser module, input optical fiber, detection optical fiber and RF bandpass filter, respectively.
Fig. 2.
Fig. 2. Schematic diagrams of (a) somatic location of the measuring devices, the FDPM probe, heart rate belt and temperature sensor on the participants and (b) a temporal protocol of all stages of the cycling exercise in color zones are presented. TIL stands for training intensity level; in the brackets are the time dedicated to each zone, x means individual-dependent duration; the red arrow points from the start of the exercise to the recovery.
Fig. 3.
Fig. 3. Absorption and scattering coefficients of participant A. Time-course profiles of μa and μs at the laser wavelength of 660 nm, 780 nm and 830 nm are respectively presented by black, red and blue lines.
Fig. 4.
Fig. 4. Absorption and scattering coefficients of participant B. Time-course profiles of ${\mu _a}$ and ${\mu _s}^{\prime}$ at the laser wavelength of 660 nm, 780 nm and 830 nm are respectively presented by black, red and blue lines.
Fig. 5.
Fig. 5. Absorption and scattering coefficients of participant C. Time-course profiles of ${\mu _a}$ and ${\mu _s}^{\prime}$ at the laser wavelength of 660 nm, 780 nm and 830 nm are respectively presented by black, red and blue lines.
Fig. 6.
Fig. 6. Time-course profiles of the StO2, skin temperature, heart rate and THb concentration of participant A. The temporal duration and TIL of all color zones are depicted in Fig. 2(b).
Fig. 7.
Fig. 7. Time-course profiles of the StO2, skin temperature, heart rate and THb concentration of participant B. The temporal duration and TIL of all color zones are depicted in Fig. 2(b).
Fig. 8.
Fig. 8. Time-course profiles of the StO2, skin temperature, heart rate and THb concentration of participant C. The temporal duration and TIL of all color zones are depicted in Fig. 2(b).

Equations (5)

Equations on this page are rendered with MathJax. Learn more.

[ 1 c t + μ a [ D ( r ) ] ] Φ ( r , t ) = S ( r , t ,
Φ ( r , t ) = P exp ( k r e a l r ) 4 π D r exp [ i ( k i m a g r ω t ) ] ,
k r e a l = 3 2 μ a μ s { [ 1 + ( ω c μ a ) 2 ] 1 / 1 2 2 + 1 } 1 / 1 2 2
k i m a g = 3 2 μ a μ s { [ 1 + ( ω c μ a ) 2 ] 1 / 1 2 2 1 } 1 / 1 2 2 .
R = 2 π d Ω [ 1 R F ( c o s θ ) ] 1 4 π [ Φ Z = 0 + 3 D Φ z | z = 0 c o s θ ] c o s θ ,