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Investigation of cortisol dynamics in human sweat using a
graphene-based wireless mHealth system
Rebeca M. Torrente-Rodríguez
1,3
,
Jiaobing Tu
1,3
,
Yiran Yang
1
,
Jihong Min
1
,
Minqiang
Wang
1
,
Yu Song
1
,
You Yu
1
,
Changhao Xu
1
,
Cui Ye
1
,
Waguih William IsHak
2
,
Wei Gao
1,4,*
1
Department of Medical Engineering, Division of Engineering and Applied Science, California
Institute of Technology, Pasadena, California, 91125, USA
2
Department of Psychiatry and Behavioral Neurosciences, Cedars-Sinai Medical Center, Los
Angeles, CA 90048, USA
3
These authors contributed equally to this work
4
Lead Contact
SUMMARY
Understanding and assessing endocrine response to stress is crucial to human performance
analysis, stress-related disorder diagnosis, and mental health monitoring. Current approaches for
stress monitoring are largely based on questionnaires, which could be very subjective. To avoid
stress-inducing blood sampling and to realize continuous, non-invasive, and real-time stress
analysis at the molecular levels, we investigate the dynamics of a stress hormone, cortisol, in
human sweat using an integrated wireless sensing device. Highly sensitive, selective, and efficient
cortisol sensing is enabled by a flexible sensor array that exploits the exceptional performance of
laser-induced graphene for electrochemical sensing. Herein, we report the first cortisol diurnal
cycle and the dynamic stress response profile constructed from human sweat. Our pilot study
demonstrates a strong empirical correlation between serum and sweat cortisol, revealing exciting
opportunities offered by sweat analysis toward non-invasive dynamic stress monitoring via
wearable and portable sensing platforms.
Graphical Abstract
*
Correspondence: weigao@caltech.edu.
AUTHOR CONTRIBUTIONS
W.G., R.M.T.R., and J.T. initiated the concept. W.G., R.M.T.R., J.T., and W.I. designed the experiments; R.M.T.R. and J.T. led the
experiments and collected the overall data; Y.Y. performed electrode fabrication and characterization; J.M. performed the circuit
design and test; C.X., C.Y., M.W., Y.S., and Y.Y. contributed to sensor characterization; W.G., R.M.T.R., and J.T. contributed the data
analysis and co-wrote the paper. All authors provided the feedback on the manuscript.
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DECLARATION OF INTEREST
The authors declare no competing financial interest.
DATA AVAILABILITY
The data that support the plots within this paper and other findings of this study are available from the corresponding author upon
reasonable request.
HHS Public Access
Author manuscript
Matter
. Author manuscript; available in PMC 2021 April 01.
Published in final edited form as:
Matter
. 2020 April 1; 2(4): 921–937. doi:10.1016/j.matt.2020.01.021.
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e-TOC
A fully integrated, flexible and miniaturized wireless mHealth sensing device based on laser-
engraved graphene and immunosensing with proven utility for fast, reliable, sensitive and non-
invasive monitoring of stress hormone cortisol is developed. Pilot human study results revealed a
strong correlation between sweat and circulating hormone for the first time. Both cortisol diurnal
cycle and dynamic stress response profiles were established from human sweat, reflecting the
potential of such mHealth device in personalized healthcare and human performance evaluation.
Keywords
graphene; flexible sensors; mHealth; stress hormone; sweat; cortisol; stress response
INTRODUCTION
The exponential increase in the pace of life in the 21
st
century constantly demands intense
and prolonged mental as well as physical efforts from individuals,
1
both of which are
potential triggers of stress. Chronic stress has been associated with higher risks of anxiety,
depression, suicide, weakening immune response as well as cardiovascular diseases (CVD).
2
The need for measurable stress indicators has never been more than apparent, be it in the
contexts of posttraumatic stress disorder (PTSD) screening and depression evaluation, or a
more general mental and somatic health monitoring setting. Although psychosocial and
physiological stresses are induced by distinct stimuli, they share similar neuroendocrine and
behavioral responses regulated by the hypothalamic-pituitary-adrenal (HPA) axis.
3
Activation of the HPA axis stimulates the secretion of glucocorticoids (e.g., cortisol), a
group of hormones that mobilize energy in the body to cope with stress (Figure 1A).
4
While
short-term alterations in the HPA axis are deemed as normal and adaptive responses of the
body, chronic dysregulation of the HPA axis, an energetically costly state, is associated with
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various pathological processes. As such, stress and individuals’ stress-coping responses, are
perceived as dynamic processes; absolute quantification of stress level provides much richer
information and greater diagnostic value in the context of time and environment.
5
Experience sampling methods (ESM) such as questionnaires and diary studies play a pivotal
role in establishing the situational contexts of stressors in relevant longitudinal stress-
response studies; however, their inherent idiosyncrasy imposed by subjective interpretations
challenges the accuracy of “stress level” assessment.
6
,
7
Quantification of stress hormones in
biological fluids provides measurable physiological indicators for mental distress. For
example, the disturbances in circadian patterns of a key stress hormone, cortisol, are linked
to PTSD and major depressive disorder (MDD) (Figure 1B).
8
,
9
In addition, the cortisol
dynamics in stress response plays a crucial role in human performance (Figure 1C).
10
Other
than the direct assessment of stress, stress hormones are also important in the understanding
of pain and fear neural circuits,
11
,
12
both of which are subjective sensation or emotion that
are hard to quantify. Blood test, albeit being the most well-studied hormone assessment
method, is afflicted by its invasive nature and potential role as a stress stimulus. Saliva and
sweat analyses, on the other hand, offer an attractive alternative for non-invasive stress
hormones dynamics studies.
Recent advances in wearable and mobile health (mHealth) sensing systems have opened up a
window of opportunities for hassle-free, real-time, personalized physiological data
collection.
13
21
Substantial progress in the realm of wearable physical sensing platform has
been made with systems capable of documenting physical and kinematic data such as
temperature,
22
pulse rate
23
and ECG
24
in real time. Although human sweat contains rich
health information and could allow non-invasive molecular monitoring, the majority of the
wearable or portable systems available for sweat chemical biomarker dynamics studies are
still limited to high concentration (usually at mM level) analytes like pH, sodium, chloride,
and glucose.
25
30
To date, the reported sweat hormone sensors were generally characterized
in either buffer or artificial sweat samples,
31
,
32
and the dynamics of the sweat stress
hormones has not yet been well studied.
In this work, we investigate the dynamics of the sweat stress hormone using an integrated
wireless mHealth device — graphene-based sweat stress sensing system (GS
4
) (Figure 1A).
As a proof-of-concept, cortisol is selected as the model stress hormone for dynamic
profiling. Highly sensitive, selective, and efficient cortisol sensing in human sweat and saliva
is achieved through a unique approach that combines the laser-induced graphene and
competitive immunosensing. We report here, for the first time, the cortisol diurnal cycle and
the dynamic stress response profile constructed from sweat using an integrated sensing
device (Figure 1A). A strong correlation between sweat and serum cortisol levels are
obtained from a small-scale pilot study. Such a wearable and point-of-care device-enabled
non-invasive sweat analysis would add another dimension to stress monitoring since it offers
minimal disturbance of daily routines and could provide instantaneous and continuous
assessments on subjects’ psychological state.
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RESULTS AND DISCUSSION
Design of the graphene-based cortisol sensor
The key component of our GS
4
platform is a flexible five-electrode graphene sensor patch
fabricated on a polyimide (PI) substrate via laser engraving as illustrated in Figure 1D–F. It
boasts the advantage of rapid, scalable, and low-cost production (Figure 1E), and does not
require elaborate lithography equipment or fabrication masks as compared with screen-
printed electrodes. The flexible sensor patch consists of three graphene working electrodes
(WEs), one Ag/AgCl reference electrode (RE), and one graphene counter electrode (CE) as
it is depicted in Figure 1F. Detection of cortisol in human sweat is achieved through the
combination of carboxylate-rich pyrrole-derivative grafting and subsequent modification on
graphene surface and a competitive sensing strategy. The large surface area and fast electron
mobility of graphene offers superior performance in electrochemical sensing (Figure 1G),
33
while competitive immunosensing strategies offer major advances in highly selective small
hormone molecule detection.
34
Electrochemical characterization and validation of the cortisol sensor
Figure 2A illustrates the process of sweat analysis and the sequential surface modification of
graphene electrodes for cortisol determination, respectively. In the event of sweat analysis,
sweat cortisol and horseradish peroxidase (HRP)-labeled cortisol compete for binding onto
antibody-modified graphene electrode surface; enzymatic reduction of hydrogen peroxide
mediated by hydroquinone (HQ) generates a cathodic current which is inversely proportional
to the amount of cortisol in biofluids. The detailed surface modification procedure of
graphene electrodes is schematized in Figure 2B and S1. Polymerization of pyrrole
propionic acid (PPA) improves the strength and adhesion of polymeric films to transducer
surfaces and facilitates subsequent surface modifications with carboxylate moieties for
affinity-based sensor fabrication. In contrast to conventional graphene modification
techniques such as acid reflux or monolayer formation of aryl hydrocarbon derivative, the
electro-grafting of pyrrole-derivative is fast (~260 s), controlled, and scalable (by connecting
electrodes in parallel). Upon electropolymerization of PPA, the graphene electrode is
activated by 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC) and N-
hydroxysulfosuccinimide (Sulfo-NHS) for covalent immobilization of anti-cortisol
monoclonal antibody (mAb), followed by deactivation of unreacted sites with bovine serum
albumin (BSA). This surface biomodification is universal to all bioaffinity receptors
immobilization and could be adapted for other hormone antibodies. After brief incubation of
the sensor with sweat containing the enzymatic tracer (HRP-labeled cortisol), amperometric
response at −0.2 V (vs. Ag/AgCl) in the presence of detection substrate (HQ/H
2
O
2
) is
recorded.
To confirm the successful sensor modification, material properties of the graphene surface
are characterized by scanning electron microscopy (SEM), Raman spectroscopy and X-ray
photoelectron spectroscopy (XPS) (Figure 2C–E). The decrease in I
D
/I
G
value in the Raman
spectrum after surface modification implies the improvement of defect concentration after a
thin uniform layer of pyrrole derivative is deposited (Figure 2D). The significantly increased
N1s and S2p peaks in XPS (Figure 2E) indicate the successful activation of the surface and
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the immobilization of the capture antibody (CAb) on the sensing electrode. Moreover, open
circuit potential-electrochemical impedance spectroscopy (OCP-EIS) and differential pulse
voltammetry (DPV) techniques are applied to electrochemically characterize the surface
after each modification step involved in the affinity-based assay. Nyquist plots for the
graphene electrode exhibit increasing resistance after each modification step as a
consequence of impeded interfacial electron transfer between the redox probe in solution
and the functionalized transducer surface (Figure 2F). The successful polymer deposition
and the effective affinity bioreceptor immobilization on the modified-graphene surface are
also confirmed by DPV (Figure S2). The effect of HRP-labeled cortisol concentration on
amperometric responses is investigated. A dilution factor of 200 is chosen as it yields the
largest ratio between currents for 0.0 (I
0.0
) and 10.0 ng/mL (I
10.0
) cortisol (Figure S3).
The performance of the as-prepared sensor is evaluated by measuring amperometric readout
in phosphate buffered (PB) solutions containing varied cortisol concentrations (Figure 2G).
Sensors prepared with laser-induced graphene electrodes (LGEs) demonstrate a much higher
sensitivity with six- and nearly two-folds reduction in current density between 0.0 and 1.0
ng/mL (3.72 vs. 0.68 and 3.72 vs. 2.41 nA/mm
2
) as compared with screen-printed carbon
electrodes (SPCEs) and glassy carbon electrodes (GCE), respectively (Figure 2H).
Amperometric signals (
I
) obtained with competitive strategies are best described by a
sigmoidal curve using the four-parameter logistic (4-PL) model following the equation:
35
I
=
i
1
+
i
2
i
1
1 + 10
logIC
50
x
*
p
where
i
2
and
i
1
indicate the maximum and minimum current values of the dose-response
curve obtained;
IC
50
represents the level of cortisol at which amperometric signal decreases
to 50% of the maximum current,
x
is the cortisol concentration in log scale, and
p
is the Hill
slope at the inflection point of the sigmoid curve. Sigmoidal calibration plots of cathodic
currents as a function of cortisol concentrations in buffer, sweat and saliva samples from a
healthy subject are demonstrated in Figure 2I. No significant slope variations are observed
between data obtained in human biospecimens and in buffered solutions. The limit of
detection (LOD), calculated as the concentration of cortisol that produces 10% inhibition
binding of HRP-labeled tracer to the immobilized affinity receptor (i.e., 10% signal
reduction) is 0.08 ng/mL. The concentration range for 20%–80% inhibition binding of the
enzymatic tracer is 0.43–50.2 ng/mL cortisol, covering the physiologically relevant range in
sweat and saliva samples reported in previous studies.
36
38
Considering that human sweat exhibits huge interpersonal variations in pH and salt content,
the performance of the sensors under various pH levels and ionic strength conditions is
evaluated (Figure S4A and S4B). The consistent sensor signals indicate the universality of
the sigmoidal calibration curve constructed. In addition, the selectivity of our cortisol sensor
is investigated by comparing the sensor responses in the presence of other non-target
hormones. As illustrated in Figure S4C, no cross-reactivity is observed for
β
-estradiol,
progesterone, and cortisone.
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Target binding is the rate determining factor in bioaffinity sensors. To ensure rapid analysis
and to allow sufficient time for binding, a crucial criterion at the point-of-care – the effect of
competition time on sensor responses is investigated. Figure 2J shows the amperometric
responses obtained for 0.0 and 5.0 ng/mL cortisol with different incubation times (30
seconds, 1, 5, 15, and 60 minutes). 15-minute recognition time is employed for real sample
analysis presented in this work in order to ensure accurate quantitation of ultra-low levels of
cortisol in biofluids with a high contrast-to-noise ratio. Here, the incubation time selected is
based on the experimental observation of the optimum competition rate rather than the time
for binding equilibrium, as the equilibrium time is long for a heterogeneous system.
Nonetheless, significant competition (47%) is observed for 5.0 ng/mL cortisol with even 1-
minute incubation, indicating that our sensor is capable of close to real-time analysis of
sweat cortisol at ng/mL level (much faster compared to recent published sensing
methodologies).
31
,
38
One potential strategy to further shorten the incubation time is through
enhanced mixing to promote the availability of unbound cortisol to antibodies on the
graphene surface.
Endogenous circulating cortisol levels in human body fluids measured with the proposed
methodology in human sweat samples (as well as saliva samples, collected from eight
healthy participants) are validated with the gold standard enzyme-linked immunosorbent
assay (ELISA). A high correlation between the results from the ELISA and the sensors (
r
=
0.973) is obtained (Figure 2K), endorsing the accuracy of rapid cortisol quantification with
our device. In addition, the sensors retained good amperometric responses (> 90%) after
storing at 4 °C for 7 days (Figure S5).
Systems integration and validation toward personalized sweat sampling and analysis
In the GS
4
, a 3WE sensor array design with a Ag/AgCl RE and a graphene CE that provides
simultaneous multichannel readings is employed. The multichannel design provides
additional accuracy via signal averaging and could potentially be adapted as a hormone
panel sensor for multiplexed detection of stress-related hormones. To minimize the variation
of current readout due to the ohmic drop in a non-ideal electrochemical cell (Figure S6), the
reference and counter electrodes are positioned in equidistance from each working electrode
with a suitable geometric design shown in Figures 3A. A microfluidic module is integrated
into the flexible graphene sensor patch to enable the on-body sweat sampling and in situ
cortisol recognition (Figure 3A). This design minimizes the errors caused from the sweat
evaporation and skin contamination from the traditional sweat collection, leading to nearly
real-time stress hormone monitoring. Figure 3B illustrates block diagrams of functional
units of the integrated electronic system that takes amperometric measurements from three
channels concurrently, and wirelessly transmits the acquired data to a user device over
Bluetooth Low Energy (BLE). The compact device, including a 3.7 V lithium-ion polymer
battery mounted underneath a printed circuit board (PCB), is 20 mm × 35 mm × 7.3 mm in
dimension. Fully functioning GS
4
drew 13.3 mA per second from a 150 mAh 3.7 V battery
during an amperometric measurement, enabling 330-minute continuous amperometric
measurements. The operation time can be significantly improved by incorporating the
sleeping mode for the microcontroller and Bluetooth modules.
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Representative 3-channel amperometric responses obtained with the GS
4
are demonstrated
in Figure 3C. The calibration plot was constructed from the potential difference obtained
with the GS
4
in the buffer solutions with five concentrations of cortisol in the pseudolinear
region of the full sigmoidal plot (Figure 3C inset). It should be noted that stable wireless
sensor readings can be achieved within 10-s measurement, indicating the rapid sensing
capability of the GS
4
. To validate that 3-channel averaging indeed provides more precise
reading, we collected current readouts for 0.0, 1.0 and 5.0 ng/mL cortisol solutions from
eight different sensors respectively. This is followed by enumerations of all 2-element and 3-
element combinations of the datasets and random selection of eight combinations in Matlab
to simulate 2-channel and 3-channel readings obtained with a sensor array. Error bars
representing standard deviations of the simulated 2WE and 3WE readings demonstrate that
the adoption of a 3WE system reduces inter-assay variation as shown in Figure 3D.
Recovery study performed on a real human sweat sample spiked with 0.0, 1.0, 2.5 and 5.0
ng/mL cortisol using the GS
4
shows an average 94.2% recovery (Figure S7), suggesting a
low systematic error.
The flexible, disposable microfluidic sensor patch shows excellent mechanical flexibility
and can conformally laminate on the skin (Figure 3E). To demonstrate the influence of the
mechanical deformation during the on-body recognition on the cortisol determination,
responses of the flexible graphene sensor patch in 1.0, 5.0, and 10.0 ng/mL cortisol solutions
incubated under different bending curvatures are recorded and illustrated in Figure 3F. No
apparent variations in the sensor readouts are observed with or without deformation,
indicating the great mechanical and electrochemical stability toward on-body use.
Considering that the actual temperature of the sensor patch during sweat collection could be
significantly higher than the room temperature (Figure S8), a temperature effect study was
performed to evaluate the performance of the GS
4
. The sensors present no significant
variation in the signals obtained for 0.0, 1.0 and 5.0 ng/mL cortisol under varied
temperatures (25, 31, and 37 °C) (Figure S9).
As compared to the current standard analytical methods for hormone analysis such as
ELISA, the GS
4
has distinct capabilities in multiplexed monitoring, miniaturization, short
assay time (down to 1 minute vs. 80 minutes), and smaller required sample volume (<10 μL
vs. 100 μL), making it an ideal platform for subsequent investigations on dynamic sweat
cortisol variations and potential applications in personalized health management.
Investigation of the circadian rhythm of sweat cortisol
Cortisol presents a distinct and robust diurnal pattern, which peaks shortly after awakening
and declines throughout the day in plasma
40
and saliva.
41
Early report shows that sweat
contains cortisol level comparable to those reported in saliva;
42
we postulate that, circulating
cortisol molecules are transported to and stored in eccrine and apocrine glands, secreted into
the sweat, and ultimately excreted through a sweat pore to the epidermal surface.
43
It is,
therefore, reasonable to hypothesize that cortisol level in sweat might present similar
circadian rhythm regulated by the internal clock and light/dark cycle (Figure 4A).
Considering that circadian pattern of circulating cortisol is highly informative for a number
of mental health conditions,
8
,
9
the fluctuations of the ultra-low levels of sweat cortisol are
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investigated with the graphene platform through a pilot human study. Sweat was sampled
with iontophoretic sweat stimulation as illustrated in Figure S10.
Figure 4B illustrates the reproducible patterns obtained from an exploratory study by
monitoring the sweat cortisol variations of a healthy subject in a period of six days. High
morning (AM) cortisol level and low afternoon (PM) level are observed each day; such
rhythm resembles diurnal cycles of circulating cortisol in blood. In order to further
characterize the correlation between sweat and circulating cortisol levels, sweat in the early
AM and in the late PM from four healthy subjects are analyzed along with saliva and serum.
A similar trend in AM/PM cortisol variations modulated by circadian rhythm are observed
from all the samples (Figures 4C–F), with the ratios ranging from 1.35 to 2.00. Although
several studies explored the correlation of cortisol found in various biofluids including
blood, urine, and saliva,
44
46
the relationship between sweat and circulating cortisol levels,
to the best of our knowledge, has barely been explored. A positive correlation between sweat
cortisol and serum cortisol (Pearson’s correlation coefficient
r
= 0.87) (Figure 4G) is
obtained based on data collected from eight healthy subjects. Similarly, the correlation
coefficient between sweat cortisol and salivary cortisol is determined to be 0.78 (Figure 4H).
Although the number of real samples analyzed is limited in this exploratory study, empirical
evidence suggests strong correlation exists between sweat cortisol and serum cortisol.
Dynamic cortisol response to stress stimuli
In addition to long-term profiling of the diurnal cycles, cortisol response to acute stressors
contains abundant information for psychoneurological investigations,
47
,
48
and plays a
critical role in human performance monitoring and management.
1
For instance, sensitization
of the HPA axis to external stimuli is another critical factor that distinguishes PTSD from
other psychiatric disorders.
8
Next, we set out to investigate if sweat analysis of cortisol
presents meaningful changes to acute stress of the human subjects induced by different
stressors in a short time frame. Aerobic exercises such as running and cycling are potent
stimuli/stressor of cortisol secretion.
49
In this study, a 50-minute stationary cycling exercise
at a constant workload is employed for sweat cortisol content analysis (Figure 5A). Sweat
sampling and analysis are performed with the GS
4
sequentially at 10-minute intervals for the
50-minute constant-load exercise in a cycling ergometer from three physically untrained and
one trained (athletic) subjects. In addition, serum cortisol levels before and immediately
after the cycling exercise are analyzed to validate if sweat cortisol variation is in accordance
with circulating cortisol levels. For all subjects under study, sweat cortisol increases
progressively and reaches the highest level after 40 minutes of continuous biking. From this
point, a slight decrease in cortisol level is detected near the end of the exercise in all
participants and more significantly in subject 4 (athlete) (Figure 5B). Cortisol contents in
pre- and post-exercise serum samples present good correlation to the change in cortisol from
the beginning of the perspiration (10 minutes) to the end of the exercise (50 minutes) (Figure
5C). The dynamic sweat hormone profiles observed for untrained subjects are similar to
reported trends of serum cortisol after high-intensity exercise,
50
indicating the activation of
HPA by physical exercise. In contrast, the blunted cortisol response observed in the trained
subject reflects exercise-induced adaptation. This is consistent with previous reports that
trained individuals likely perceived the given workload as a smaller stressor and demonstrate
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a lower degree of HPA activation in response to physical stressors
51
as well as psychosocial
stimuli.
52
Noting that circadian patterns in sweat cortisol level give rise to different baseline before
stress stimulation, cortisol variations in sweat for physical exercises conducted in the
morning and in the afternoon for the same subjects are studied. Sweat cortisol levels are
analyzed from two subjects in the beginning of the perspiration and in the end of the cycling
(Figure S11). Significantly increased sweat cortisol levels are observed at 50 minutes as
compared to that at 10 minutes, in response to the physiological stressor. Cortisol level for
the first time point is higher in the AM than in the PM for both subjects; higher relative
percentage change of cortisol is observed in the PM exercise. This relation is in agreement
with the diurnal sweat cortisol variation we observed in the circadian rhythm study, similar
to a previous report that shows the circadian rhythm of serum and salivary cortisol could
confound the magnitude of cortisol responses.
53
These results reveal the importance of
baseline construction in offsetting circadian baseline in the context of short-term dynamic
sweat cortisol stress response. Point-of-care and wearable devices-enabled sweat analysis
could conveniently facilitate personalized baseline construction as discussed for the
circadian rhythm study.
To study the response time frame of sweat cortisol to acute stressors, an exploratory cold
pressor test (CPT) was performed on four subjects. Subjects were asked to immerse their
non-dominant hand in ice water for 3 minutes (Figure 5D). CPT is a reliable acute
physiological stressor that triggers immediate HPA axis activation and significant cortisol
release.
54
Sweat was sampled at 8-minute interval with iontophoretic sweat stimulation as
illustrated in Figure S10. Sweat dynamic cortisol profile was evaluated in each case and we
observed that cortisol increased after completion of CPT, reaching the mean peak between 8
and 16 minutes after CPT (Figure 5E). Similar trends were also observed for serum (Figure
5F) and salivary cortisol (Figure S12); the former collected and tested before starting the
experiment (denoted as baseline), 8 and 24 minutes after CPT. These observations are
consistent with previously reported CPT studies for cortisol and other hormones release
evaluation in serum
55
and saliva.
56
The sweat cortisol profiles presented small to negligible
time lag as compared with serum cortisol trends in literature,
57
59
revealing the promptness
of sweat cortisol as a quasi-real-time stress indicator. Furthermore, given the clinical
applicability of CPT for pain tolerance evaluation,
60
sweat stress hormones sensors may
serve as an attractive quantification approach in pain perception studies.
CONCLUSION
This work demonstrates the potential of sweat hormone analysis enabled by an integrated
portable system – the GS
4
. Highly sensitive, selective, and efficient stress hormone sensing
was achieved through a unique combination of the laser-induced graphene and
immunosensing. The assay time could be as low as 1 minute. Using this graphene-based
wireless sensing platform, we have demonstrated that relevant information crucial to stress
response and adaptation analysis could be extracted from cortisol excreted in sweat. The
low-cost and mass-produced graphene sensor arrays enabled us to conduct several
meaningful stress-related physiological studies. To the best of our knowledge, the results we
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present here represent the first demonstration of cortisol diurnal cycle and the dynamic stress
response profile constructed from human sweat. On a longer timescale, characteristic
cortisol circadian rhythms could be monitored; in a short time frame, acute external stimuli
triggered stress response could be analyzed.
This study unveils the immense potential of sweat cortisol circadian variation monitoring.
Sweat’s accessibility to wearable continuous monitoring devices and its minimal
invasiveness enables the construction of long-term and comprehensive cortisol diurnal
patterns. To date, many clinical studies on psychological disorders-triggered cortisol
circadian rhythms variation rely heavily on data collected at sparsely spaced plasma or saliva
cortisol sampling timing
61
,
62
whereas those with narrow sampling intervals were achieved
with intravenous catheters;
63
confirmation of cortisol circadian rhythms in sweat might
revolutionize clinical research and mental health monitoring paradigm for both clinicians
and patients in the near future.
The possibility of continuous dynamic stress response profiling with sweat sensors offers
new opportunities for fundamental psychoneuroendocrinology studies and timely
documentation of stress level for day-to-day mental health monitoring. Although only
physical stress stimuli were investigated in the present study, given the fact that psychosocial
stress stimuli trigger similar neuroendocrine and behavioral responses regulated by HPA
axis,
3
similar information may be extracted from sweat cortisol in response to psychosocial
stresses. The good correlation with circulating hormones, the diurnal cycle, and dynamic
stress response profile demonstrated in this study using our integrated sensing approach will
lead the next wave of technological advancement in personalized human performance and
mental health management.
EXPERIMENTAL PROCEDURES
Materials and reagents
1-H pyrrole propionic acid (PPA, 97%), 1-ethyl-3-(3-dimethylamonipropyl)carbodiimide
(EDC), N-hydroxysulfosuccinimide (Sulfo-NHS), bovine serum albumin (BSA),
hydroquinone (HQ), 2-(N-morpholino)ethanesulfonic acid (MES), Tween® 20,
hydrocortisone, cortisone, progesterone,
β
-estradiol, sodium thiosulfate, sodium bisulfite
and potassium ferrocyanide (II) were purchased from Sigma Aldrich. Sodium dihydrogen
phosphate, potassium hydrogen phosphate, potassium chloride, hydrogen peroxide (30%
w/v) and sulfuric acid were purchased from Fischer Scientific. Potassium ferricyanide (III)
and silver nitrate, iron (III) chloride and 0.1 M PBS (pH 7.4) were purchased from Across
Organics and Alfa Aesar, respectively. Anti-cortisol murine monoclonal antibody and HRP-
labeled cortisol were purchased from EastCoastBio. Cortisol competitive human ELISA kit
(Catalog. No. EIAHCOR) was purchased from Thermo Fisher. Polyimide film (PI, 75 μm
thick) was purchased from DuPont.
Fabrication of three channel array electrode
For three channel graphene sensor fabrication, a PI film was attached onto a supporting
substrate in a 50 W CO
2
laser cutter (Universal Laser System). Selected laser-cutting
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parameters were: Power 5.0%, Speed 6%, Points Per Inch (PPI) 1000, in raster mode and at
focused height. Ag/AgCl reference electrodes (RE) were fabricated by electrodeposition in
20 μL of a mixture solution containing silver nitrate, sodium thiosulfate, and sodium
bisulfite (final concentrations 250 mM, 750 mM and 500 mM, respectively) for 100 seconds
at −0.2 mA, followed by drop casting 10 μL-aliquot of FeCl
3
for 1 minute.
Modification of sensing platform and electrochemical detection
PPA electropolymerization was conducted by CV from 0.0 to 0.85 V (vs. Ag/AgCl) for 20
cycles at a scan rate of 0.1 V/s in a fresh solution containing 5.0 mM carboxyl-
functionalized pyrrole monomer and 0.5 M KCl. After rinsing with deionized (DI) water and
drying under air flow, electrodes were incubated with 10 μL of a mixture solution containing
0.4 M EDC and 0.1 M Sulfo-NHS in 0.025 M MES, pH 5.0, for 35 minutes at room
temperature under humid ambient conditions. Covalent attachment of specific antibody onto
activated surface was carried out by drop casting 10 μL of anti-cortisol antibody solution
(100 μg/mL in MES buffer, pH 5.0) and incubated at room temperature for 90 minutes,
followed by a 1 hour blocking step with 1.0% BSA prepared in 0.01 M phosphate buffered
saline with Tween® 20 (PBST) of pH 7.4. After one washing step with same buffered
solution, 10 μL-aliquots of cortisol standards (or the biofluid to be analyzed properly
diluted) and HRP-cortisol (1/200 dilution) prepared in PBST, pH 7.4, were drop casted onto
the working electrode, allowing competition between labeled and circulating free cortisol
contained in the sample for the available free sites of the immobilized affinity receptor to
take place for 15 minutes. Amperometric readings were registered at −0.2 V (vs. Ag/AgCl)
in 50 mM sodium phosphate buffer of pH 6.0 containing 2.0 mM HQ. The readout signal
was obtained after a 30 μL-aliquot of 10 mM H
2
O
2
was injected to the system.
Characterization of the biosensing platform
The morphology and material properties of the graphene sensing electrodes before and after
surface modification were characterized by TEM, SEM, Raman and XPS. The SEM images
of graphene electrodes were obtained by focused ion beam SEM (FIB–SEM, FEI Nova 600
NanoLab). TEM images were obtained by transmission electron microscope (TecnaiTF-20).
The surface properties of the laser-induced graphene were characterized by X-ray
photoelectron spectroscopy (Escalab 250xi, Thermo Scientific). Raman spectrum of the
graphene was recorded using a 532.8 nm laser with an inVia Reflex (Renishaw, UK).
Amperometry, open circuit potential-electrochemical impedance spectroscopy (OCP-EIS),
cyclic voltammetry (CV), and differential pulse voltammetry (DPV) were carried out on a
CHI820 electrochemical station by means of an electrochemical setup comprising laser-
induced graphene electrodes (LGEs) as the working electrodes (WEs), a platinum wire as
the counter electrode (CE), and a commercial Ag/AgCl electrode as the reference electrode
(RE).
In order to characterize surface modification after each step electrochemically, DPV and
OCP-EIS readings were carried out in 0.01 M PBS, pH 7.4, containing 2.0 mM of
K
4
Fe(CN)
6
/K
3
Fe(CN)
6
(1:1) at detailed conditions: potential range, −0.3 and 0.6 V; pulse
width, 0.2 s; incremental potential, 4 mV; amplitude, 50 mV; frequency range, 0.1–10
6
Hz;
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amplitude, 5 mV. Performances of LGEs, glassy carbon electrodes (GCEs) and commercial
screen-printed carbon electrodes (SPCEs) were compared through current densities (nA/
mm
2
) obtained after developing the proposed competitive-based assay on both carbon
surfaces for target cortisol determination at 1.0 and 5.0 ng/mL levels under optimized
conditions. Dilution of HRP labeled cortisol was optimized by comparing amperometric
responses obtained for 1/100, 1/200 and 1/300 diluted enzymatic tracer for 0.0 and 10.0
ng/mL cortisol standards. Performance of our device was evaluated for different pHs and salt
contents ranging from 7.1 to 4.1 and from 0.1 M PBST to 0.001 M PBST, respectively.
Selectivity test was conducted in the presence of mixture solutions of 1/200 HRP-cortisol
enzymatic tracer containing 5.0 ng/mL cortisone, progesterone or
β
-estradiol, in the absence
or in the presence of target hormone at the same concentration level. Stability study was
conducted for target cortisol determination at 5.0 ng/mL levels under optimized conditions.
The electrodes for stability study were modified on the same day and stored at 4 °C for 0 to
35 days before carrying out the competitive assay.
System level development and evaluation
The electronic system for the integrated three channel electrochemical analyzer was
designed to be compact and efficient. A two-layer printed circuit board (PCB) (20 mm × 35
mm × 0.6 mm) had all the components on the top layer such that a 150 mAh 3.7 V lithium-
ion polymer battery (19.75 mm × 26 mm × 3.8 mm) could sit comfortably underneath the
PCB. The entire device is 20 mm × 35 mm × 7.3 mm, comparable to a USB thumb drive.
The small size, low power consumption, and rich analog peripherals of the STM32L432
ultra-low-power Arm Cortex-M4 32-bit microcontroller (MCU) enabled the compact size of
the overall electronic system. The MCU had a built in 12-bit analog-to-digital converter
(ADC) and two built-in 12-bit digital-to-analog converters (DAC). When a user initiates an
electrochemical measurement over Bluetooth, the built-in DACs generate a reference voltage
(V
ref
) and a working voltage (V
w
) that set the potentials at the reference electrode and
working electrodes through a potentiostat interface circuit. For the 3-channel amperometric
measurements required for cortisol analysis, the reference voltage was stabilized further by a
low pass filter (LPF), and the three working electrodes were biased at −0.2 V relative to the
reference electrode. The resultant currents flowing through each electrode were amplified
and converted to voltage by transimpedance amplifiers (TIA). Three channels of the MCU’s
ADC were utilized to acquire concurrent amperometric measurements, and the data was
transmitted to a user device over Bluetooth for further analysis.
To prepare the microfluidic module, a double-sided medical adhesive was attached to a
substrate and cut through to make the channels and reservoir using a 50 W CO
2
laser cutter
(Universal Laser System). Influence of mechanical deformation was investigated through
incubating the sensor patch in the cortisol solutions for 15 minutes under mechanical
deformation (with radii of bending curvature 2.3 and 3.8 cm).
Subjects and procedures
The performance of the GS
4
was evaluated in human sweat, saliva and sweat samples from
the human subjects in compliance with the protocols that were approved by the institutional
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review board (IRB) (No. 19–0895 and No. 19–0892) at California Institute of Technology
(Caltech). The participating subjects (twelve healthy subjects, age range 18–65) were
recruited from Caltech campus and the neighboring communities through advertisement by
posted notices, word of mouth, and email distribution. All subjects gave written, informed
consent before participation in the study.
Circadian rhythm study
Four healthy subjects who reported regular sleep-wake rhythm and no sleep disturbances
participated in this study. Subjects were informed to refrain from food intake at least 30
minutes before reporting to the laboratory. On experimental day, subjects reported to the
laboratory at 8:00 AM and at 7:00 PM on the same day for sweat, saliva and capillary blood
collection. Sweat stimulation was performed with a Model 3700 Macroduct® by placing
two electrodes on the pre-cleaned forearm region of the subject. After their connection to the
source, a 1.5 mA current was applied for 5 minutes and secreted sweat was sampled for a
period of 40 minutes and then analyzed. During the sweat sampling and test, fresh capillary
blood and saliva were collected from subject immediately after sweat stimulation following
the protocol described in the sample processing section.
Physiological stress response - stationary biking study
Three untrained participants and one trained participant were involved in this study. The
trained subject (an athlete from Caltech sport teams) exercised regularly for at least 9 hours
per week while the untrained subjects had an average of 1 hour of exercise per week.
Constant workload physical activity trials were performed in the morning (ranging from
8:00 to 10:00, denoted as AM) or afternoon (from 5:00 to 7:00, denoted as PM) in an
ergometer stationary bike (Kettler Axos Cycle M-LA). Subjects were informed to refrain
from food intake at least 30 minutes before the exercise. Subjects were asked to bike for 50
minutes at a constant speed of 60 revolutions per minute (rpm) and sweat samples were
collected every 10 minutes from the forehead. Before starting the aerobic trial, and after
sweat sampling and analysis at each time interval, participants’ foreheads were cleaned with
alcohol swabs and gauze. Blood collection were performed before the stationary bike
exercise and immediately after the exercise following the procedures described in sample
processing protocol section.
Physiological stress response - cold pressor test
Four participants were exposed to standard CPT in the afternoon (between 5:00 to 7:00 PM)
in order to control for the diurnal cortisol cycle. The experimental procedure was initiated by
collecting sweat through iontophoresis for a period of 8 minutes. At the same time, saliva
and capillary blood sample from each participant were collected with the purpose of
determining baseline values. Subsequently, recruited volunteers immersed their non-
dominant hand up to the wrist in a plastic tank containing cold-water (2 °C) for 3 minutes
(CPT) and after the immersion time they were instructed to remove the hand from the ice-
water. Sweat, saliva and capillary blood were collected following the detailed protocols at
different resting periods after CPT test (8, 16, and 24 minutes).
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Saliva and blood sample processing protocol
After rinsing mouth with water, volunteers deposited saliva in 1.5 mL Eppendorf tubes
which were subsequently centrifuged (10000 rpm, 10 minutes) and analyzed. Fresh capillary
blood samples were collected at same periods of time as saliva using a finger-prick
approach. After cleaning the fingertip with alcohol wipe and allowing it to air dry, the skin
was punctured with CareTouch lancing device. Samples were collected with 1.5 mL
Eppendorf tubes after wiping off the first drop of blood with gauze. Once standardized
clotting procedure finished, serum was separated by centrifuging at 3575 rpm for 15
minutes, and instantly stored at −20 °C.
Enzyme-linked immunosorbent assay for human sample analysis validation
ELISA tests for cortisol were performed in an accuSkan™ FC Filter-Based Microplate
Photometer at a detection wavelength of 450 nm, according to the manufacturer’s
instructions. Briefly, standards (or properly diluted samples), HRP-cortisol conjugate and
cortisol antibody were added to IgG coated microtiter plate wells and incubated during 1
hour at room temperature. After four washing steps with wash buffer, 100 μL of 3,3
,5,5
-
Tetramethylbenzidine (TMB) substrate was incubated for 30 minutes and absorbance values
were measured immediately after addition of 50 μL of 1M H
2
SO
4
in each well.
Thermal imaging of device and skin temperature
Thermal images of the sensor patch on human skin were taken by a long wave infrared
thermal camera (FLIR A655sc).
Supplementary Material
Refer to Web version on PubMed Central for supplementary material.
ACKNOWLEDGEMENTS
This project was supported by the Rothenberg Innovation Initiative (RI
2
) program, the Carver Mead New
Adventures Fund, Caltech-City of Hope Biomedical Research Initiative, and National Institute of Health
(#5R21NR018271) (all to W.G.). J.T. was supported by the National Science Scholarship (NSS) from the Agency of
Science Technology and Research (A*STAR) Singapore. We gratefully acknowledge critical support and
infrastructure provided for this work by the Kavli Nanoscience Institute and Jim Hall Design and Prototyping Lab
at Caltech, and we gratefully thank Dr. Matthew Hunt and Bruce Dominguez for their help. We also thank Dr.
Chiara Daraio and Vincenzo Costanza for the technical support and helpful assistance with IR imaging.
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Progress and Potential
Prompt and accurate detection of stress is essential to the monitoring and management of
mental health and human performance. Considering that current methods such as
questionnaires are very subjective, we propose a highly sensitive, selective, miniaturized
mHealth device based on laser-enabled flexible graphene sensor to non-invasively
monitor the level of stress hormones (e.g., cortisol). We report a strong correlation
between sweat and circulating cortisol and demonstrate the prompt determination of
sweat cortisol variation in response to acute stress stimuli. Moreover, we demonstrate, for
the first time, the diurnal cycle and stress response profile of sweat cortisol, revealing the
potential of dynamic stress monitoring enabled by this mHealth sensing system. We
believe that this platform could contribute to fast, reliable and decentralized healthcare
vigilance at the metabolic level, thus providing an accurate snapshot of our physical,
mental and behavioral changes.
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