Annemarijn S M Steijlen1, Kaspar M B Jansen2, Jeroen Bastemeijer1, Paddy J French1, Andre Bossche1. 1. Faculty of Electrical Engineering, Mathematics & Computer Science, Delft University of Technology, Mekelweg 4, Delft 2628 CD, The Netherlands. 2. Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, Delft 2628 CE, The Netherlands.
Abstract
Sweat sensors allow for new unobtrusive ways to continuously monitor an athlete's performance and health status. Significant advances have been made in the optimization of sensitivity, selectivity, and durability of electrochemical sweat sensors. However, comparing the in situ performance of these sensors in detail remains challenging because standardized sweat measurement methods to validate sweat sensors in a physiological setting do not yet exist. Current collection methods, such as the absorbent patch technique, are prone to contamination and are labor-intensive, which limits the number of samples that can be collected over time for offline reference measurements. We present an easy-to-fabricate sweat collection system that allows for continuous electrochemical monitoring, as well as chronological sampling of sweat for offline analysis. The patch consists of an analysis chamber hosting a conductivity sensor and a sequence of 5 to 10 reservoirs that contain level indicators that monitor the filling speed. After testing the performance of the patch in the laboratory, elaborate physiological validation experiments (3 patch locations, 6 participants) were executed. The continuous sweat conductivity measurements were compared with laboratory [Na+] and [Cl-] measurements of the samples, and a strong linear relationship (R2 = 0.97) was found. Furthermore, sweat rate derived from ventilated capsule measurement at the three locations was compared with patch filling speed and continuous conductivity readings. As expected from the literature, sweat conductivity was linearly related to sweat rate as well. In short, a successfully validated sweat collection patch is presented that enables sensor developers to systematically validate novel sweat sensors in a physiological setting.
Sweat sensors allow for new unobtrusive ways to continuously monitor an athlete's performance and health status. Significant advances have been made in the optimization of sensitivity, selectivity, and durability of electrochemical sweat sensors. However, comparing the in situ performance of these sensors in detail remains challenging because standardized sweat measurement methods to validate sweat sensors in a physiological setting do not yet exist. Current collection methods, such as the absorbent patch technique, are prone to contamination and are labor-intensive, which limits the number of samples that can be collected over time for offline reference measurements. We present an easy-to-fabricate sweat collection system that allows for continuous electrochemical monitoring, as well as chronological sampling of sweat for offline analysis. The patch consists of an analysis chamber hosting a conductivity sensor and a sequence of 5 to 10 reservoirs that contain level indicators that monitor the filling speed. After testing the performance of the patch in the laboratory, elaborate physiological validation experiments (3 patch locations, 6 participants) were executed. The continuous sweat conductivity measurements were compared with laboratory [Na+] and [Cl-] measurements of the samples, and a strong linear relationship (R2 = 0.97) was found. Furthermore, sweat rate derived from ventilated capsule measurement at the three locations was compared with patch filling speed and continuous conductivity readings. As expected from the literature, sweat conductivity was linearly related to sweat rate as well. In short, a successfully validated sweat collection patch is presented that enables sensor developers to systematically validate novel sweat sensors in a physiological setting.
Continuous
health monitoring
can contribute to the prevention of chronic diseases by creating awareness
about lifestyle and by stimulating physical activity.[1,2] Furthermore, it may support in the prevention of injuries[3,4] and it can contribute to the effective and efficient treatment of
diseases.[5,6] Common health monitoring devices include
heart rate monitors and movement sensors. Recent advances in wearable
sweat sensor systems show great potential to add new physical and
chemical information about a person’s health status. Sweat
samples can be collected unobtrusively and continuously, which are
the main advantages compared to the widely used blood tests. The unobtrusive
nature of sweat sensing and its potential use in real-time health
monitoring motivated researchers to develop electrochemical sweat
sensors to monitor sweat constituents. Literature reviews show a vast
number of recently developed sweat sensors.[7−11]Although sweat provides ways to unobtrusively
monitor biomarkers,
measuring sweat constituents introduces new challenges that are not
present in blood sampling. First, sweat rates vary over time and influence
the composition of sweat. Second, sweat rate and composition differ
per body location. Third, sweat rates can be very low, which results
in low sample volumes too. Fourth, skin and sweat gland metabolism
and skin contaminants influence the composition of sweat. And lastly,
sample collection is difficult due to quick evaporation and the irregular
skin surface.[12] Furthermore, scientific
knowledge about the physiological mechanisms of sweating and how sweat
analyte levels relate to blood levels is limited.[13] During strenuous exercise and/or exposure to hot environments,
body core temperature rises. Evaporation of sweat from the skin plays
a critical role in regulating body temperature.[14] The thermoregulatory function of sweating is well-accepted,
but the physiological knowledge about using sweat constituents, i.e., electrolytes and metabolites, as a biomarker is limited.
For most constituents in sweat, correlations between concentrations
in blood and concentrations in sweat are not known. For sodium and
chloride, with concentrations in sweat ranging from 10 to 100 mM,
secretion mechanisms are known.[15] Na+ and Cl– ions are secreted in the secretory
coil of the sweat glands and partially reabsorbed in the duct. The
number of reabsorbed ions has a direct relation to the sweat rate.
When sweat rates increase, a lower percentage of ions is reabsorbed
and the absolute concentration of these ions in sweat increases.[14,16] Several articles suggest that an increase in Na+ or Cl– levels can be used as a biomarker for dehydration.[17,18] There are also researchers who state that [Na+] and [Cl–] loss can indicate electrolyte imbalance.[19] However, in physiological literature, even for
these most available ions in sweat, equivocal and even contradictory
results can be found.[20] The main reason
for these existing gaps in literature is the lack of standardized
methods for chrono-sampling of sweat.[21] Sweat samples are mostly collected with simple devices, such as
absorbent patches and the Macroduct sweat collector.[22] Chrono-sampling with these devices requires a lot of repetitive
work. This results in a limited number of samples.To facilitate
chronological sampling of sweat and to enable continuous
sweat monitoring, many new sweat sensor systems have been developed
recently. Most sensors focus on continuous measurement of a sweat
constituent, such as electrolytes and metabolites, with a miniaturized
wearable device. Some researchers focus on the microfluidic system
that enables capture and transport of the sweat to the sensor,[23−25] while other researchers focus on the fabrication and improving the
specifications of the sensor itself.[26,27] In particular,
a lot of research is being executed in optimizing the sensitivity,
selectivity, and durability of the electrode materials.[28−30] Additionally, significant progress has been achieved in sweat rate
measurement[31,32] and design integration of the
fluidic system and the sensors.[25,33,34] These novel systems may support physiologists in their research
to find sweat biomarkers, but there are two major limitations. First,
the fabrication of the systems has high complexity and requires advanced
equipment and expensive materials. Second, the new systems are validated
in an exercise setting with a very limited number of participants.
Interpretation of the data and comparing them against results from
other articles is a challenge, because protocols are not standardized,
and in most cases, no sweat reference measurements are performed during
the exercise.The aim of this study is to develop and present
a sweat collection
patch that enables continuous in situ monitoring
of sweat composition and controlled sampling of sweat in reservoirs
for offline analysis. The patch distinguishes itself from other recently
developed patches by its easy and low-cost fabrication. Additionally,
the sweat collection area and sample volumes are generally larger
(typically >10 times) than in previously presented chronological
sweat
collection systems,[35,36] to increase the number of samples
in time and minimize the effects of skin contamination and increase
the reliability of the measurements. Patches that collect relatively
large samples do exist, but these patches comprise a single reservoir.[37,38] The new patch consists of an analysis chamber that hosts a conductivity
sensor for measuring ionic content continuously. Once the sweat passes
this chamber, it flows into a sequence of reservoirs, which include
level indicator electrodes. The level indicator electrodes measure
the filling speed, which is dependent on the sweat rate. The sweat
in the reservoirs can be analyzed offline. In this way, in
situ sweat composition measurements of the patch can be directly
compared with lab measurements. The new sweat patch is made with accessible
fabrication techniques. This means that the patch can be easily reproduced,
and other novel electrochemical can be placed in the analysis chamber
to perform controlled validation experiments in a physiological setting.To test the performance of the collector patch, lab validation
experiments are executed, followed by physiological experiments in
a climate chamber. In these experiments, the relationship between in situ sweat conductivity measurements and [Na+] and [Cl–] of the samples, measured by ion chromatography
in the lab, is researched. Thereafter, sweat rates measured with a
ventilated capsule measurement system are compared with the conductivity
measurements and filling rate measurements from the patch.
Materials
and Methods
Sweat Patch
To test the flow characteristics, a preliminary
collection patch was developed and tested without integrated electronics.
As can be seen in Figure a, the patch consists of a funnel-shaped structure that guides
the sweat to the collector inlet. By capillary and gravitational forces,
the sweat will flow to the first reservoir. Once this reservoir is
filled, the new fluid will pass to the subsequent reservoir. The collector
is fabricated from two layers of hydrophilic film (Visgard 275, a
poly(ethylene terephthalate) (PET) film with a polyurethane (PU) coating[39]) and a double-sided adhesive (3M 1522, a PE
tape with an acrylate adhesive[40]) in between.
The structure of the channels and reservoirs in the acrylate adhesive
and the contours of the hydrophilic foil are cut with a CO2 laser system (Merlin Lasers, Lion Laser Systems, The Netherlands).
Simulations and experiments with a syringe pump proved that the reservoirs
fill consecutively, and that sweat inflow is not significantly inhibited
by the resistance of the channels. This first version of the patch
was presented in a previous article in more detail.[41] The patch is designed to be placed at the back of a person.
This version has a collection surface of 40 cm2 and can
collect 5 samples of 130 μL. Sample volume and collection surface
can be adjusted to the type of physiological experiment.
Figure 1
(a) Front view
of the design of the preliminary collector patch
(left) and the new patch with integrated sensors (right). An extra
reservoir is added near the inlet (No. 7). All sweat will pass this
reservoir. Electrodes in this reservoir measure sweat conductivity.
Level indicator electrodes are placed in the bottom reservoir sequence.
(b) Exploded view of the new patch. (c) Setup for physiological tests
with the new sweat patch. The patch is placed at the subject’s
back and electronics are placed in a waist pocket. For the ventilated
capsule system, dry air flows through a capsule at the subject’s
back and the humidity and temperature are measured by the sensors
that are connected to the outlet of the capsule. (d) Measurement locations
of the patches (left) and the capsules (right).
(a) Front view
of the design of the preliminary collector patch
(left) and the new patch with integrated sensors (right). An extra
reservoir is added near the inlet (No. 7). All sweat will pass this
reservoir. Electrodes in this reservoir measure sweat conductivity.
Level indicator electrodes are placed in the bottom reservoir sequence.
(b) Exploded view of the new patch. (c) Setup for physiological tests
with the new sweat patch. The patch is placed at the subject’s
back and electronics are placed in a waist pocket. For the ventilated
capsule system, dry air flows through a capsule at the subject’s
back and the humidity and temperature are measured by the sensors
that are connected to the outlet of the capsule. (d) Measurement locations
of the patches (left) and the capsules (right).After testing the first patch in a physiological setting, a redesign
was made (Figure a).
An extra chamber, the analysis chamber (Figure a, No. 7), was placed near the inlet of the
reservoir system. This chamber has rounded corners so that there is
a constant renewal of sweat. Preferred marker-specific electrodes
can be placed in this reservoir. The extra air outlet in the top (Figure a, No. 5) ensures
that electrodes stay covered with sweat. In this design, the back
foil layer of the reservoir system was replaced with a thin printed
circuit board layer (0.6 mm) with gold electrodes. The gold electrodes
are located in the new chamber to measure the sweat conductivity over
time. Furthermore, electrodes were added in the sequence of reservoirs
to measure the filling rate which depends on the sweat rate (Figure a, No. 8). Two parallel
elongated gold electrodes were positioned in each of the five reservoirs,
which allows us to measure a conductance change when the reservoirs
are filling up. A temperature sensor (LM35, Texas Instruments) was
placed at the PCB as well. Since the PCB materials are less hydrophilic,
contact angle measurements and new syringe pump experiments were performed
to test whether the new collector fills at the same rate as the sweat
rate. Contact angles of the gold electrodes and the solder mask are
69.8 and 73.1°, respectively, while the contact angles for the
adhesive tape and the hydrophilic film are 92.2 and 50.5° (measured
with water at t = 10 s after contact with the surface,
with optical tensiometry, KSV Instruments Ltd.).For both sensors,
the AD5933 impedance converter (Analog Devices)
is used to measure the impedance. The integrated circuit contains
a frequency generator (up to 100 kHz, Vpp: 0.2–2 V), and a
12-bit analog-to-digital converter (ADC) to sample the impedance.
The chip also holds a digital signal processor (DSP) that performs
a discrete Fourier transform to return the magnitude of the impedance
and the phase of the impedance at the defined output frequency. An
8-channel multiplexer (ADG1408, Analog Devices) is used to switch
between the conductivity sensor, sweat rate sensors, and a calibration
resistor. The excitation voltage is set at 0.2 Vpp to prevent saturation
of the ADC at lower resistances, and the frequency is set at 80 kHz
to minimize double-layer effects. The AD5933 and the multiplexer are
placed in a pocket that can be carried around the waist. The patch
is connected to the readout electronics via simple header pins. Figure b shows an exploded
view of the patch design.To calibrate the conductivity sensor
in the lab, different solutions
of NaCl (from 10 to 150 mM) were placed in the top reservoir of a
patch. The impedance was measured for each solution to find the relationship
between the NaCl concentration and the conductance in the analysis
chamber. The functioning of the level indicator electrodes was tested
using the syringe pump (KD Scientific 200). Pump rates ranging between
12 and 60 μL/min were chosen. For patches with a collection
surface of 40 cm2, this translates to sweat rates of 0.15
to 1.5 mg/(cm2 min). For these experiments, a NaCl solution
of 75 mM was used.
Reference Measurement
To research
the performance of
the sweat collector patch in the physiological setting, two types
of reference measurements were performed. First, the continuous in situ conductivity measurements were compared to ion chromatography
measurements of the samples that were collected and stored in the
sequence of reservoirs. Second, to investigate whether sweat conductivity
measurements and patch filling rate relate to the actual sweat rate,
these measurements were compared against sweat rate measurements with
the ventilated capsule technique.
Ion Chromatography
This paragraph describes the procedure
for offline chemical analysis. In each collection patch, tiny outlets
are made in the PCB layer at the bottom of each reservoir (Figure a, No. 9). These
holes are covered with adhesive tape during collection. Once the patch
is removed, the tape can be removed and the sweat can be pushed into
a vial by injecting air in the reservoir with a syringe at the air
inlet. The sweat volume was weighed and diluted with ±3 mL of
ultrapure water, after which the vials are stored at −20°
C and analyzed in the laboratory. In this study, we focused on the
analysis of electrolytes using ion chromatography/high pressure liquid
chromatography (IC/HPLC). [Na+], [Cl–], and [K+] were measured. For the anions, a Metrohm 881
Anion system with a Metrosep A supp 5–150/4.0 column was used.
The cations were analyzed with the 883 Basic IC plus system and a
Metrosep C6–150/4.0 column (Metrohm, Switzerland). A more detailed
description of this method can be found in Steijlen et al.[41]
Ventilated Capsule Measurement
The
most common methods
for measuring local sweat rate in a lab setting are the ventilated
capsule (VC) technique and the absorbent patch technique.[42] Using absorbent patches requires a lot of repetitive
work, and a limited number of samples can be collected over time.
Therefore, the VC measurement is more suitable to measure sweat rate
continuously.[43] Capsules with a collection
surface of 5.3 cm2, made from a flexible three-dimensional
(3D)-printed photopolymer on a Connex 3 3D printer (Objet350, Stratasys
Ltd., Israel), were placed on the skin. The capsule is connected to
a dry air cylinder, and air flows through the capsule at a volumetric
flow rate between 0.1 and 1.2 L/min. The flow rate is measured with
a variable area flow meter (Key Instruments). A humidity sensor and
temperature sensor (HDC1080, Texas Instruments) are connected to the
outlet of the capsule. The sensors are controlled with an MSP430 microcontroller
(Texas Instruments). We used the Antoine equation in the conversion
of relative humidity to absolute humidity. Knowing the dry air flow
rate, absolute humidity, and sweat collection surface, the sweat rate
was calculated.Lab measurements were executed to test the performance
of our VC system. A detailed description of these experiments and
the results can be found in the Supporting Information (S1). To test whether the VC system measures all
sweat in the capsule and to test if there are no leakages, a predetermined
amount of water was placed in a closed capsule and the total amount
of sensed water was calculated by numerical integration of the evaporation
rate measurements. It was concluded that the deviation was adequately
small (1–5%). Furthermore, the response and recovery time of
the VC system were calculated. At a dry air flow rate of 1.2 L/min,
the response time is 118 s and the recovery time is 353 s. Because
sweat rates will always increase or decrease gradually, the actual
response time will be even faster in a physiological setting. This
means that the VC system can be used for continuous monitoring of
sweat rate. The maximal sweat rate that can be measured with the current
system is 2.75 mg/cm2/min.
Physiological Experiments
Healthy recreational athletes
(3 female and 3 male participants 20–30 years) cycled (Lode
Excalibur, The Netherlands) in a climate chamber (b-Cat, The Netherlands)
that was set to 33 °C and 65% relative humidity. Figure c shows the setup of the physiological
experiments. The patches were placed at three locations at the back
on the left side of the spine. Three ventilated capsules are attached
to the right side of the spine at the same heights, as can be seen
in Figure d. The locations
were chosen based on the study of Smith and Havenith, which showed
relatively high sweat rates at the back and similar sweat rates at
the left and right side of the sagittal plane.[44] The capsules are placed from the start of the exercise
and the dry air flow rate was set at 1.2 L/min to allow for the expected
high sweat rates in this climate. Heart rate was measured with a heart
rate belt (Polar H10, Finland), and body core temperature was measured
with a rectal temperature probe (Yellow Springs Instruments) during
the experiments. The participants cycled 30 min at 40–50% of
their maximum heart rate (HRmax), followed by 20 min at 60% HRmax
and 20 min at 70% HRmax. Afterward, the participants stopped cycling
and a cooling down period of 20 min at the stationary bike was included.
Sweat tests were approved by the Human Ethics Research Committee of
Delft University of Technology. The initial 30 min included the 20
min wash out period of the skin.[20] The
first sweat patch was placed after this initial 30 min. Once all reservoirs
were filled with sweat, the patch was replaced with a new one. Collectors
with 10 reservoirs of 70 μL and a collection surface of 20 cm2 were used.
Results and Discussion
Characterization of the
Collection Patch
During the
patch characterization experiments, two topics were addressed. First,
it was researched if the conductivity sensor in the analysis chamber
can measure NaCl concentrations in the desired range. Solutions of
NaCl (10–150 mM) were injected in the analysis chamber. By
performing a frequency sweep (from 5 to 100 kHz), when measuring the
different solutions, it was found that at 80 kHz, there were no significant
influences of stray capacitances on the measurements. Figure a shows the relationship between
the conductance measured with the conductivity sensor in the top reservoir
and the concentration NaCl of the standard solutions. A linear relationship
was found, and the sensitivity of the sensor system was 24 μS/mM.
Using the molar conductance of NaCl in water,[45] a cell constant of 5.223/cm was calculated.
Figure 2
(a) Conductance measurements
in the analysis chamber that is filled
with different solutions of NaCl. (b) Results of a filling rate measurement
when the syringe pump is set at 12 μL/min. Each color represents
the measurement of a separate pair of electrodes in a single reservoir.
Cumulative results show the course of the filling process. (c) Conductance
over time at 4 different pump rates. (d) Relationship between the
syringe pump rate in μL/s and the filling rate in S/s.
(a) Conductance measurements
in the analysis chamber that is filled
with different solutions of NaCl. (b) Results of a filling rate measurement
when the syringe pump is set at 12 μL/min. Each color represents
the measurement of a separate pair of electrodes in a single reservoir.
Cumulative results show the course of the filling process. (c) Conductance
over time at 4 different pump rates. (d) Relationship between the
syringe pump rate in μL/s and the filling rate in S/s.Second, the performance of the collection system
was tested with
the level indicator electrodes. It was researched whether the reservoirs
fill consecutively, and if the conductance change measured with the
level indicator electrodes are linearly related to the volumetric
flow rate settings of the syringe pump. To test the consecutive filling
of the reservoirs, the syringe pump was set at a flow rate of 12 μL/min. Figure b shows the results
of the measurement of the separate electrode pairs in pre-wetted reservoirs.
Once a previous reservoir is filled, the total conductance is added
to the next measurement to see the course of the filling process. Figure c shows that the
collectors fill at a constant speed at increased pump rates as well
and a linear relationship between the different pump rates and the
filling rate in Siemens per second was obtained (Figure d).All six participants completed
the protocol in the climate chamber. For most participants, the patches
started filling typically around 8 min after placement. Once a patch
was completely filled, it was immediately replaced by a new one. Sweat
rates highly varied among participants. For one participant at 2 locations
at the back, three patches of 10 reservoirs were completely filled,
while for another participant, only 3 reservoirs were filled during
the entire exercise. Body core temperature increased 1.03 ± 0.72°
during the exercise. Figure S2 shows real-time
rectal temperature and heart rate of participant 1 during the exercise.
A picture of the experimental setting is presented in Figure S3. Figure a shows the sweat rate over time measured with the
ventilated capsule system for the three different locations at the
back of participant 1. The sweat rate was calculated using the air
flow rate, humidity, and temperature measurements. Data were filtered
with a Savitzky–Golay sliding window filter[46] using a second-order polynomial and a window size of 150
data points. The sample frequency of the measurements was 1 Hz. In Figure b, the conductivity
measurements in the patch analysis chamber at the same locations on
the left side of the back of participant 1 are plotted. Low conductance
values (<0.5 × 10–3 S) and abrupt changes
in conductance, attributed to air bubbles in the system, were removed.
Subsequently, a similar sliding window filter was used to remove high-frequency
noise components (window size: 50, sample rate: 0.3 Hz, second-order
polynomial). Unfiltered data can be found in the appendix (Figure S4). Temperature changes over time varied
from 0 to 1.5 °C for each patch from the start of the filling
process. The temperature coefficient of conductivity of electrolyte
solutions is around 2%/°C at 25 °C.[47] Thus, the conductivity change due to temperature effects would be
estimated between 0 and 3% maximum. Given that the conductivity increased
more than 100% during the course of the exercise of participant 1,
temperature changes have limited influence.
Figure 3
(a) Continuous sweat
rate measurement from the VCs placed at the
3 locations at the back of participant 1. The incremental exercise
was performed until t = 4200 s, followed by a recovery
period of 1200 s. The patches were placed at t =
1800 s. (b) Conductivity measured in the analysis chamber of the patches
at the 3 locations of participant 1. Gaps are due to patch replacement
(e.g., patch 2-1 is replaced by patch 2-2). (c) [Na+], [Cl–], and [K+] data from
chromatographic analysis of the samples from the individual reservoirs.
Timestamps were derived from the filling rate measurements. Lines
indicate that the samples are from the same patch.
(a) Continuous sweat
rate measurement from the VCs placed at the
3 locations at the back of participant 1. The incremental exercise
was performed until t = 4200 s, followed by a recovery
period of 1200 s. The patches were placed at t =
1800 s. (b) Conductivity measured in the analysis chamber of the patches
at the 3 locations of participant 1. Gaps are due to patch replacement
(e.g., patch 2-1 is replaced by patch 2-2). (c) [Na+], [Cl–], and [K+] data from
chromatographic analysis of the samples from the individual reservoirs.
Timestamps were derived from the filling rate measurements. Lines
indicate that the samples are from the same patch.It can be noted that all 3 graphs from participant 1 show
a similar
trend during the exercise. The sweat rate increased as the heart rate
increased. After a few minutes from the start of the cooling down
period t = 4200 s, the sweat rate decreases again.
When the sweat rate increases, a lower percentage of ions will be
reabsorbed by the sweat duct.[14] Therefore,
the conductivity measurement shows an increasing trend when the sweat
rate increases. This corresponds to the ion chromatography results
from the samples that were collected in the reservoirs. In Figure c, it can be seen
that [Na+] and [Cl–] increase when the
participant exercises, and when the participant stops exercising,
the concentrations decrease again. [Na+] are on average
6.84 ± 0.98 mM higher than [Cl–]. This difference
is presumably being caused by the abundant presence of other negative
ions in sweat such as lactate and bicarbonate. [K+] concentrations
show a slightly decreasing trend during the entire exercise. For K+, secretion mechanisms are partly known and probably these
ions are not reabsorbed in the duct and therefore not influenced by
changes in sweat rate.[13] The results from
the other participants showed corresponding trends for the three different
measurements methods similar to the results presented in Figure .Parrilla
et al. also compared the results of newly developed sweat
sensors during physiological tests with ion chromatography measurements.[48] However, because they used the labor-intensive
absorbent patch method and they used a different physiological protocol,
the number of samples that were collected over time were limited to
1 for every 10–12.5 min. Ohashi et al. recently presented a
new sweat collection system with micropumps for chronological sweat
sampling, which proved to collect a sample approximately every 5 min.[49] Although a larger sequence of samples can be
collected, samples are highly diluted (typically four times) and the
sampling requires a strict protocol during the tests.
Sweat Conductivity
and [Na+] and [Cl–]
In this
study, it was aimed to test the performance of
the sensor patch in situ by validating whether the
lab measurements of the samples from the reservoirs can be used as
a reference for the sensor in the analysis chamber. Therefore, a comparison
between all ion chromatography results and conductivity measurements
was made, by investigating the relationship between sweat conductivity
and [Na+] and [Cl–] in sweat. First,
the time intervals of the filling process of each reservoir were identified
by detecting the starting times and end times of filling each reservoir.
Subsequently, the time that it takes for the sweat to move from the
top reservoir to the bottom reservoirs was subtracted from the time
intervals. The mean conductance values of the top electrodes at the
resulting time intervals were compared with the ion chromatography
results. Because each electrode pair covers two reservoirs, concentration
levels of two samples were averaged. In Figure S5, the results, including an error estimation of the three
locations for each participant, can be found. A large range of concentrations
was measured (from 18 to 105 mM). Participants that reached higher
sweat rates also had significantly higher sweat Na+ and
Cl– concentrations. Figure a shows all measurements in one graph. [Na+] and [Cl–] are plotted against conductivity,
and a strong linear relationship (R2 =
0.97) for both ions was found.
Figure 4
(a) [Na+] and [Cl–] plotted against
conductivity of all samples (n = 97) of the physiological
experiments. The different marker types represent the different participants.
(b) Sweat rate of the VC plotted against the sweat rate of the patch.
The dashed line represents the identity line. (c) Relationship between
sweat conductivity and sweat rate of the VC at the upper back of participant
2.
(a) [Na+] and [Cl–] plotted against
conductivity of all samples (n = 97) of the physiological
experiments. The different marker types represent the different participants.
(b) Sweat rate of the VC plotted against the sweat rate of the patch.
The dashed line represents the identity line. (c) Relationship between
sweat conductivity and sweat rate of the VC at the upper back of participant
2.From these results, it can be
concluded that the collector patch
showed good performance because the continuous measurements in the
analysis chamber were well related to the offline measurements of
the two most abundant ions in sweat. Furthermore, it can be concluded
that a 2-point AC conductivity measurement with gold electrodes can
be used to obtain [Na+] and [Cl–] levels
with good accuracy in these physiological conditions. Because of the
higher stability and less complex fabrication process of the electrodes,
conductivity sensors might be a more accessible choice than potentiometric
sensors[50−52] for integration in smart sweat patches that are aimed
to monitor [Na+] and [Cl–] levels of
healthy individuals. To find out if conductivity measurements can
be used to obtain [Na+] and [Cl–] concentrations
in other physical or specific dietary conditions, further research
is required.
Sweat Conductivity and Sweat Rate
The filling rate
of the reservoirs of the patch can possibly be used as an indicator
of the sweat rate. Therefore, it was researched whether this filling
rate correlates well with the sweat rate derived from the VC technique.
To obtain the actual filling speed from the level indicator readings,
several data processing steps are required. The conductance will increase
during the course of the filling process, but ionic content changes
influence the conductance measurement as well. The cumulative average
of the conductance data from the analysis chamber is used to compensate
for the change in sweat conductivity due to ionic content change. eq shows the relationship
between the level indicator conductance (C2) and the cumulative average of the conductance in the analysis chamber
(C1).in which K1 and K2 denote the cell constant in the analysis chamber
and the cell constant of the level indicator electrodes, respectively. V is the current volume, t is time, and Vtot is the total volume of the sweat that is
covered by 1 level indicator electrode pair. A time delay (Δt), which is the time that it takes before incoming sweat
at the inlet reaches the reservoirs, is included as well. In Figure S6, a graph of the filling rate (volume
plotted against time) of two patches can be found. The abrupt changes
in conductance over time are caused by droplet formation, and a linear
fit was made to derive the average filling rate of a collector. The
slope of this fit, or the filling rate, is plotted against the average
VC sweat rate. For one participant, who had exceptionally high sweat
rates, sweat rates were above the maximum evaporation rate of the
system. So these data were excluded. Patches that showed leaks or
patches that collected less than 4 samples were excluded as well.
As can be seen in Figure b, the data of both techniques correspond reasonably well.
However, a wider range of sweat rate measurements should be performed
to draw a solid conclusion about the correlation. The main source
of error appeared to be caused by the reading accuracy of the flow
meters of the ventilated capsule system. Reading errors can result
in an offset of maximum 8.3% of the measured sweat rate. These errors
are represented by the horizontal error bars in Figure b. Furthermore, errors in the filling rate
occur when small air bubbles are enclosed in a reservoir. The R2 value relative to the regression line of the
best fit is 0.71 and that relative to the identity line (y = x) is 0.65.Lastly, the relationship between
the sweat conductivity and the VC data was studied. The time interval
of continuous flow of sweat through the reservoir was identified,
and the continuous measurements at this time interval were compared
for each patch location. Figure c shows the results at one location of participant
1. A significant relationship was found for all patch locations (mean R2 = 0.87), except for one case. In this case,
the sweat rate did not increase significantly (Table S7). The results show that conductivity is directly
related to sweat rate. When sweat rate increases, the relative ion
reabsorption rate changes and sweat conductivity increases, which
corresponds to the theory described by Baker and Wolfe.[20] Thus, the patches can be used to accurately
monitor sweat rate changes during exercise.To summarize the
results, the physiological experiments showed
that the new patch can be used to test continuous sweat monitoring
techniques and to simultaneously collect and store this sweat for
separate, offline analysis. The sweat collection system enabled collection
of 38 samples of 70 μL on average per participant during the
physiological tests of 90 min. It was found that the [Na+] and [Cl–] of the samples were linearly related
to conductivity, and conductivity data were related to VC sweat rate
data as well. The current version of the patch was shown to work well,
but the system can possibly be expanded with an extra sensor for semicontinuous
absolute measurement of sweat rate with the patch. A new narrow microfluidic
channel with a small collection surface could be integrated to minimize
droplet formation and enclosure of air during sweat rate measurement.
The filling of this new channel could be detected by placing tiny
electrodes at multiple places along the channel and counting the moments
that the fluid passes the channel, like in the patch of Yuan et al.[32] The current filling rate electrodes should be
maintained in this alternative version of the patch to use them for
timing purposes.In short, the new sweat patch facilitates real-time
measurement
and chronological sampling of sweat. The process is less labor-intensive
per sample and less prone to contaminations during the protocol than
alternative methods such as the absorbent patch technique. The simple
fabrication process of the collection patch enables other researchers
to easily replicate this system to compare their own sensors, such
as electrochemical glucose sensors,[53] or
lactate sensors,[54] against a reference. Figure S8 shows an example of how an external
screen-printed potentiometric sensor can be integrated in the system.
Furthermore, the reservoir volume and collection surface can be easily
adapted to physiological tests performed in alternative conditions
that evoke sweat rate levels of different orders of magnitude. In Figure S9, a technical drawing is shown which
includes a system with reservoirs of 70 μL and a system with
reservoirs of 130 μL. With this new patch, novel sweat sensors
can be validated. Thereafter, the sensors can be used by physiologists
to learn more about the mechanisms behind sweating and to identify
new sweat biomarkers or markers for athlete performance monitoring.
Conclusions
In this paper, we presented a new low-cost sweat
collector patch
for both continuous monitoring of analytes and chronological sampling
of sweat for offline analysis. A conductivity sensor was integrated
in the patch for continuous measurement, and level indicator electrodes
measure the filling rate of the sweat in the sequence of reservoirs
that store sweat for offline analysis. The new sweat patch was characterized
in the lab. The sensitivity of the conductivity sensor was 24 μS/mM
NaCl, and the reservoirs fill at the same speed as the sweat rate
in the desired range (12 to 60 μL/min). In physiological experiments,
continuous conductivity measurements were successfully compared to
ventilated capsule (VC) sweat rate measurements and offline analysis
of [Na+] and [Cl–] by ion chromatography.
Results (n = 6, 3 locations for each participant)
showed that VC sweat rate data were related to the conductivity measurements.
Furthermore, sweat conductivity data were linearly related to [Na+] and [Cl–] from the samples stored in the
reservoir sequence of the patch (R2 =
0.97). Thus, the new sweat collector patch allows to continuously
measure sweat analyte concentrations during physiological experiments
and to store the sweat in a sequence of reservoirs for offline reference
measurement, as an in situ validation strategy for
new sweat sensors.
Authors: Z Sonner; E Wilder; J Heikenfeld; G Kasting; F Beyette; D Swaile; F Sherman; J Joyce; J Hagen; N Kelley-Loughnane; R Naik Journal: Biomicrofluidics Date: 2015-05-15 Impact factor: 2.800
Authors: Paolo Pirovano; Matthew Dorrian; Akshay Shinde; Andrew Donohoe; Aidan J Brady; Niall M Moyna; Gordon Wallace; Dermot Diamond; Margaret McCaul Journal: Talanta Date: 2020-05-30 Impact factor: 6.057
Authors: Maura M Rutherford; Ashley P Akerman; Sean R Notley; Robert D Meade; Madison D Schmidt; Glen P Kenny Journal: Exp Physiol Date: 2020-12-17 Impact factor: 2.969