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Biomed. Phys. Eng. Express 10 (2024)025036 https://doi.org/10.1088/2057-1976/ad28cb
PAPER
Soft electrodes for simultaneous bio-potential and bio-impedance
study of the face
Bara Levit
1
, Paul F Funk
2,3,4
and Yael Hanein
3,4
1
School of Physics, Tel Aviv University, Tel Aviv, Israel
2
Department of Otolaryngology, Head and Neck Surgery, University Hospital Jena, Friedrich Schiller University Jena, Jena, Germany
3
School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel
4
Tel Aviv University Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv, Israel
E-mail: yaelha@tauex.tau.ac.il
Keywords: bio-potential, bio-impedance, soft electrodes, facial EMG, dry electrodes, blood flow
Supplementary material for this article is available online
Abstract
The human body’s vascular system is a finely regulated network: blood vessels can change in shape (i.e.
constrict, or dilate), their elastic response may shift and they may undergo temporary and partial
blockages due to pressure applied by skeletal muscles in their immediate vicinity. Simultaneous
measurement of muscle activation and the corresponding changes in vessel diameter, in particular at
anatomical regions such as the face, is challenging, and how muscle activation constricts blood vessels
has been experimentally largely overlooked. Here we report on a new electronic skin technology for
facial investigations to address this challenge. The technology consists of screen-printed dry carbon
electrodes on soft polyurethane substrate. Two dry electrode arrays were placed on the face: One array
for bio-potential measurements to capture muscle activity and a second array for bio-impedance. For
the bio-potential signals, independent component analysis (ICA)was used to differentiate different
muscle activations. Four-contact bio-impedance measurements were used to extract changes (related
to artery volume change), as well as beats per minute (BPM). We performed concurrent bio-potential
and bio-impedance measurements in the face. From the simultaneous measurements we successfully
captured fluctuations in the superficial temporal artery diameter in response to facial muscle activity,
which ultimately changes blood flow. The observed changes in the face, following muscle activation,
were consistent with measurements in the forearm and were found to be notably more intricate. Both
at the arm and the face, a clear increase in the baseline impedance was recorded during muscle
activation (artery narrowing), while the impedance changes signifying the pulse had a clear repetitive
trend only at the forearm. These results reveal the direct connection between muscle activation and
the blood vessels in their vicinity and start to unveil the complex mechanisms through which facial
muscles might modulate blood flow and possibly affect human physiology.
1. Introduction
The control of blood flow in the face holds significance
in facial physiology, encompassing aspects like facial
expressions and skin well-being [1,2]. Blood circula-
tion is subject to a range of factors, including the
expansion and narrowing of blood vessels. Muscle
contraction in the proximity of blood vessels can cause
them to narrow, and thus blood circulation in the face
can potentially be locally influenced by facial muscles
[1,3]. Facial muscles, compared to other skeletal
muscles of the body, are unique: they are connected to
the skin (rather than being fixed to bone-based
insertion points), they are interwoven and they
partially overlap each other [4,5]. Consequently, facial
movements have complex activation patterns, where
nearly all facial muscles are co-active [6]. Scientific
explorations spanning over decades explored many
phenomena regarding the physiological, psychologi-
cal, and cognitive effects of facial muscle activation.
For example, expansive evidence implicates facial
muscle activation with the expression of emotions
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[7–10]. Moreover, facial muscles are associated with a
wide range of medical disorders including Parkinson’s
disease (hypomimia, the reduction or loss of sponta-
neous facial expressions)[11], Tourette syndrome
(fast, brief, and repetitive facial movements in the form
of tics)[12]and chronic facial palsy (might lead to
synkinetic muscle activity or muscle atrophy)[13,14].
Anatomically, facial muscles and the vascular net-
work are interwoven [15,16], suggesting a mechanical
mechanism in which dynamic changes in facial muscle
activation may affect blood flow. It was long ago
empirically suggested that facial muscles play a role in
modulating blood flow [17,18]. Recently, several
approaches were used to explore the dynamic interac-
tion between blood flow and facial muscles. Ultra-
sound was used to study blood flow blockage caused
by muscle activation during smiling [1]. The interac-
tion between facial muscles and blood flow was also
recorded in photoplethysmography (PPG)measure-
ments in the ear during facial expressions [3]. In paral-
lel, attempts were made to show an indirect effect of
this interaction. Mainly, if facial expressions have an
effect on blood flow or temperature in the brain [19].
For example, using functional magnetic resonance
imaging (fMRI), lower brain activity (in the amygdala)
was reported during a mimicry of angry expressions
when the forehead’s muscles were paralyzed [20].
Similarly, an emotional state from spontaneous
expressions was assessed using functional near-infra-
red spectroscopy (fNIRS)and electroencephalography
(EEG)[21]. However, such attempts do not
offer insight into local mechanical muscle-vessel
interactions.
Overall, the study of the link between facial mus-
cles and a change in blood flow due to changes in local
vessel diameter was so far limited, with existing tools
allowing only low-resolution investigation under sta-
tic conditions. To facilitate the investigation of the
interaction between facial muscles and blood flow in
the face under natural conditions, we introduce a
novel skin electronic approach, consisting of impe-
dance plethysmography (IPG), combined with a high-
resolution surface electromyography (sEMG). IPG,
sEMG, and EEG from the face under natural condi-
tions were achieved with printed soft electrode arrays.
Using this method, we recorded high-resolution facial
muscle activation and simultaneous minute changes
in IPG at the superficial temporal artery to investigate
the impact of facial muscle activation on vessel dia-
meter, which potentially affects blood flow. We fur-
ther explore how this relation differs at the forearm.
2. Methods
2.1. Subjects
Four healthy volunteers (ages 27-30)participated in
the study. For both the sEMG and IPG measurements,
an electrode array was adhered to the skin. All
experiments were conducted in accordance with
relevant guidelines and regulations under approval
from the Institutional Ethics Committee Review
Board at Tel Aviv University. Informed consent was
obtained from all subjects. The research was con-
ducted in accordance with the principles embodied in
the Declaration of Helsinki and in accordance with
local statutory requirements.
2.2. Soft IPG and sEMG electrodes
The electrode arrays used in this study are based on a
screen-printing process on soft substrates, as pre-
viously described [22,23]. Briefly, carbon electrodes
and silver traces were screen-printed on a thin and soft
polyurethane (PU)film (80μm from Delstar EU94DS).
A second double-sided adhesive PU film was used for
passivation and skin adhesive material. The sEMG
arrays (X-trodes Inc.)consisted of 16 electrodes with
an additional internal ground.
2.3. sEMG measurement and analysis
sEMG data were recorded with a miniature wireless
data acquisition unit (DAU, X-trodes Inc.). The DAU
supports up to 16 unipolar channels (2μV noise RMS,
0.5-700 Hz)with a sampling rate of 4000 S/s, 16 bit
resolution and input range of ±12.5 mV. A 620 mAh
battery supports DAU operation for a duration of up
to 16 hr. A Bluetooth (BT)module is used for
continuous data transfer. The DAU is controlled by an
Android application and the data are stored on a built-
in SD card and the Cloud for further analysis. The
DAU also includes a 3-axis inertial sensor, to measure
the acceleration of the hand or face during the
measurements.
The face electrode array was placed at close esti-
mated proximity to major facial muscles, such as the
zygomaticus, frontalis, and orbicularis oris muscle.
The forearm electrode array was positioned at the
flexor carpi radialis and pronator teres muscles region.
A 16-electrode array was placed such it is centered
approximately at one-third of the forearm anterior
length measured from the wrist to the elbow (see
figure 1). The array was connected to a wireless DAU.
ICA was performed following the scheme pre-
sented previously [22,23]. Here we implemented the
algorithm in Python, using python-picard [24,25].
We also implemented the heat maps described pre-
viously to visually present the sources on the face,
allowing us to discern the different segments of mus-
cles that were activated. The interpolation was done
using Scipy (griddata, linear method). In addition, to
evaluate the dominance of each ICA source, we calcu-
lated their intensities in each action: First, the absolute
value of the amplitude of each source during each
action was calculated, then the intensity was defined as
the average of the absolute value.
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Biomed. Phys. Eng. Express 10 (2024)025036 B Levit et al
2.4. IPG measurement and analysis
The IPG array consisted of four electrodes to support a
4-terminal measurement. The four-contact IPG was
measured using an impedance analyzer (MFIA by
Zurich Instruments). A custom-made printed circuit
board (PCB)was produced to facilitate contact
between the MFIA and the soft electrodes which were
connected directly to flat conducting traces on the
PCB using a z-axis adhesive. IPG data were analyzed
with Python code. First, a running average over the
raw data was performed, using Scipy (uniform_fil-
ter1d). Then, the detection of the maximum and
minimum peaks of the pulse was performed (Scipy,
find_peaks). Next, the impedance change and beats
per minute (BPM)were calculated as follows: The
impedance change ΔZwas defined as the difference
between the absolute impedance at the maximum and
the absolute impedance at the minimum of each pulse
(see figure 1). As pulsation measurements included
dynamic actions, only reliable pulses were kept.
Reliable pulses were defined as those with a repetitive
pulse shape and behavior, with approximately equal
spacing. For the BPM, we calculated the time between
each peak minima (each pulse),Δt, then the BPM was
defined as one over Δt, multiplied by 60 (as Δtis in
seconds). See figure 1.
The impedance can be related to the diameter of
the blood vessel by modeling the artery as a cylindrical
resistor [26]:
rrp==ZlAlr 1
aa
2
() ()
where Z
a
is the impedance of the artery, r
a
is the artery
radius, lis length of the measured segment, and ρis the
blood resistivity.
The overall bio-impedance is also sensitive to
blood pulsation and can be therefore described by a
baseline impedance (Z)and ΔZ- the change in the
impedance due to pulsation. ΔZcan be expressed by
equation (2)[27]:
prD= DZZrl 2
a
22
() ()
where
D
=¢-rrr
aaa
22
is the (artery)radius pulsa-
tion amplitude change.
Further detail can be found in Supplementary
Material E.
2.5. Fist clenching protocol
A 16 electrode sEMG array was placed on the forearm,
together with four commercial pre-gelled Ambu
Figure 1. Simultaneous sEMG and IPG measurements. (a1)IPG measurement from the ulnar artery during relaxation. Extremal
points signifying the pulse are marked in circles. (a2)sEMG (most intense ICA source during fist clenching)during relaxation and fist
clenching. (a3)Placement of the gel electrodes and sEMG array on the forearm. (b1)IPG measurement from the superficial temporal
artery during relaxation. (b2)sEMG (most intense ICA source for the lips condition)during relaxation, ‘lips’and ‘teeth’condition.
(b3)Placement of the 4-electrode IPG array on the superficial temporal artery. (b4)Placement of the sEMG facial array.
3
Biomed. Phys. Eng. Express 10 (2024)025036 B Levit et al
electrodes of 40 mm in diameter (Ambu® BlueSensor
Q ECG electrodes)along the ulnar artery. Subjects
were instructed to rest and then to clench their fist.
Muscle activity (sEMG)and blood pulsation (IPG)
were recorded during fist clenching and release.
2.6. Facial muscle activation protocol
Subjects with sEMG and IPG electrodes were recorded
while performing three facial activation tasks: ‘lips’
(holding a pen in the mouth with the lips),‘teeth’
(holding a pen in the mouth with the teeth), and facial
expressions. The ‘lips’and ‘teeth’tasks were adapted
from Strack and coworkers [28]. We chose this task as
it is a simple mechanical facial ‘expression’that can be
activated for longer without feeling overly self-con-
scious. We also tested sEMG and IPG during facial
expressions. IPG measurements were taken from the
superficial temporal artery, as it is easily accessible with
minimal discomfort to the subject.
3. Results
Soft and dry electrodes were used for simultaneous
IPG and sEMG measurements, to study how muscle
activation affects the diameter of the superficial
temporal artery in the face. We used unique screen-
printed dry carbon electrodes which were extensively
validated previously for bio-potential [29]and bio-
impedance [30]measurements. As a reference, we also
performed similar measurements on the forearm. In
both cases, sEMG data were recorded with soft 16
electrode arrays and a miniaturized and wireless DAU.
IPG was measured using a 4-terminal impedance
measurement. For IPG from the forearm, both dry
and conventional gelled electrodes were used (see
supplementary figure B1-B2). Clearly, to access
arteries in the face, IPG measurements had to be
performed using low form factor and soft electrodes
that can conform to the curvature of the face.
In figure 1, we show the two electrode arrays (i.e.
IPG and sEMG)placed on the forearm and the face
(figure 1(a3)) and IPG electrodes along the ulnar artery
and on the face (figure 1(b3)). The advantage of the
dry-printed electrodes to study the face is readily
apparent.
In figure 1we also show typical IPG and sEMG
data from the arm and the face. For the sEMG data, we
used independent component analysis (ICA), to mini-
mize noise and to reduce the effect of cross-talk [23].
For clarity, the onset of muscle activity is marked by
orange in figure 1(a2)for the forearm and orange and
blue in figure 1(b2)for the face. IPG data was recorded
simultaneously. As clearly seen in figure 1(a1)and
1(a2), IPG records blood pulsation that can be readily
seen when the electrodes are positioned in close proxi-
mity to an artery (ulnar artery in the forearm or super-
ficial temporal artery in the face). As we recently
demonstrated in [30], IPG recordings with soft-
printed dry electrodes are characterized by high-qual-
ity signals and good stability, even under muscle
activation.
IPG data can be used to derive artery properties.
Foremost, we observe that the pulse shape differs
between the forearm and face, with the secondary
notch (the dicrotic notch [31])being less pronounced
at the face. Indeed pulse shape has a strong association
with the electrode location [30,32]. Additionally, from
the extremal points (corresponding to the pulsation
itself), we can extract the pulse amplitude (ΔZ)and
duration (Δt)(see figure 1(a1)), which characterize
blood flow. Pulsation amplitude provides information
about the artery mechanical parameters (equation
E.3), and the heart rate. Moreover, baseline impedance
can be associated with artery cross-section (equation
E.1-E.2). Simultaneous IPG and sEMG measurements
reveal how muscle activation impacts artery properties
at rest and during muscle action.
In figure 2, we examine how fist clenching affected
the diameter of the ulnar artery. Figure 2shows sEMG
activity at the forearm muscle of the left hand during
five repetitions of fist clenching and relaxation. The
IPG signal is directly affected by muscle activation in a
very consistent manner (figure 2(a)). At the onset of
muscle activation, the baseline IPG signal shifted
upward (i.e. the impedance Zincreases, the artery dia-
meter decreases, figure 2(a)bottom panel)and the
pulse amplitude ΔZslightly increased (figure 2(b)top
panel). At the release of the force, the IPG signal
returned to the baseline (artery diameter returns to its
original state). After the release of the force, we also
observed a change in IPG pulsation amplitude. It first
deflected downwards and gradually returned back to
the baseline value (figure 2(b)middle panel). Finally,
we make note of the elevated heart rate during fist
clenching (from 75 ±5.6 BPM at initial relaxation to
an average of 92 ±6.8 BPM across all fist clenching
repetitions, figure 2(b)bottom panel).
Under manual obstruction of the artery (both
above the elbow, far from the measurement site (Sup-
plementary figure (A1)-(A3)), and at the forearm at
close proximity to the measurement site), we observed
similar behavior in Z(increase during blockage and
return to the baseline after release). In both fist clench-
ing and mechanical blockage, the increase in Zcan be
associated with artery radius reduction, followed by a
return to the baseline when the blockage is lifted. ΔZ
was slightly larger during fist clenching than during
relaxation (figure 2). As explained in the Supplemen-
tary, how Δr
a
changes reflects on the viscoelasticity of
the artery and may depend on the manner the block-
age is applied and released. The measurements were
repeated both with gel electrodes and printed carbon
electrodes and similar results were obtained (Supple-
mentary figure (B1)-(B2)).
For the study of facial muscles, we followed the
approach of Strack and co-authors [28]to generate
different activations. Two facial actions were used:
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Biomed. Phys. Eng. Express 10 (2024)025036 B Levit et al
‘lips’and ‘teeth’.In‘lips’, the participants were asked
to hold a pen with their lips, while in ‘teeth’, a pen was
held with their teeth. In this extensively studied para-
digm, the ‘lips’action supposedly inhibits smiling,
while the ‘teeth’action activates muscles necessary for
smiling [28]. In fact, in our high-resolution facial
sEMG data (data discussed below), we can map which
muscles are active, and show how these activations
change from action to action.
As portrayed in figure 3, simultaneous IPG and
sEMG measurements from the face reveal a con-
spicuous link between muscle activation and vessel
diameter. Foremost, at the onset of muscle activation,
the baseline IPG signal shifts upward (increase in
impedance, decrease in artery radius), as shown in the
bottom panel of figure 3(a). The increase or decrease
of pulse amplitude, both during and after muscle acti-
vation, differed between the two actions. In figure 3(b)
(top and middle panels)we show an example where
the pulsation amplitude increased slightly during
muscle activation in the ‘lips’condition and increased
more substantially in the ‘teeth’condition (see other
examples in Supplementary Material C). Interestingly,
in contrast to the effect observed during fist clenching,
after the force is released, the pulsation amplitude does
not exhibit an abrupt decrease with a gradual increase
to the baseline (across all repetitions). In general, and
as shown here (in figure 3(b), top and middle panels),
after muscle activation, pulse amplitude increased.
The qualitative difference between the ulnar and the
superficial temporal artery may be attributed to their
different arterial properties, taking into account that
the determining factors for arterial stiffness stem from
the cellular and extracellular composition of the
artery, as well as its geometry [33,34].
Altogether these results show that the difference
between the two movements (smile and non-smile)is
manifested in different muscle activations (amplitude
and composition)as well as changes in vessel dia-
meter. The implications of these results are further
discussed below.
Unlike the robust and consistent behavior
observed during fist clenching, the effect observed in
the face is more complicated, potentially reflecting
the higher complexity of the facial muscle-blood net-
work and the intricate manner in which arteries are
Figure 2. sEMG and IPG response to fist clenching. (a). Most intense ICA source during fist clenching (top)and 4-terminal IPG signal
at the ulnar artery as a function of time (bottom).(b). Running average of the impedance as a function of time (top), relative impedance
changes as a function of time (middle), BPM as a function of time (bottom). Vertical dashed lines signify a transition between states
and the solid black line signifies the average at the first relaxation period. Only data from detectable pulses are shown.
5
Biomed. Phys. Eng. Express 10 (2024)025036 B Levit et al
interwoven between the muscles [2]. Repetition of
the protocol showed different responses in the pulsa-
tion amplitude. We hypothesize that the cause for the
variability in the IPG responses (in the face)is due to
differences in muscle activation, even when similar
action is performed. We explore this in figure 4.
Figure 4demonstrates the distinct difference between
the forearm and the face. We plot all ICA sources dur-
ing each activation, ordered by intensity (highest to
lowest, left to right), the color denotes the average
intensity of the source throughout all sessions. The
case of fist clenching is typified by close similarity
between repetitions. This result is echoed in the IPG
data: for all repetitions ΔZduring fist clenching
increases between 2.6—5.8 standard deviations (σ)
from ΔZ
0
(changes during initial relax). Similarly,
post fist clenching, ΔZdecreases between 0.72–1.9 σ
from ΔZ
0
. In the face, each activation is different. We
can see how the contribution of the source varies in
different sessions, despite the fact that the measure-
ments were taken from the same participant, on the
same day, using the same electrode arrays and on the
same location. In particular, source 6 (forehead)was
weak in the first sessions, but is one of the top most
intense sources in the last three lips/teeth activations.
Similarly, source 10 (corner of the lips),wasthe
strongest source for both the ‘lips’and ‘teeth’condi-
tion in the first and second sessions, drops to the sec-
ond and third least intense sources for the third and
fourth sessions. This is in contrast to the muscle acti-
vation in the forearm, where variability of the mus-
cles activated is much smaller (figure 4(a)). Indeed,
the variability of muscle activation between each fist
clenching is on average 0.58, meaning on average the
intensity of the sources varies up to 1 ranking. The
average variation for the face, on the other hand, is
1.6 for the ‘lips’and 2 for the ‘teeth’condition. This
means the ranking of the intensity varies on average
by 2 rankings in the face, twice as much as in the fore-
arm (Supplementary figure D(1)).Thisvariabilityis
particularly manifested in ΔZfor the teeth condition,
as well as the post-action relaxation period in both
‘teeth’and ‘lips’. For the former, ΔZdiffers from ΔZ
0
anywhere from 2.4 to 8.8 σ, and the latter has a wider
range still of 1.5-24 σ.
Figure 3. sEMG and IPG response to Strack conditions (‘lips’and ‘teeth’).(a). sEMG activity versus time (most intense ICA source
during the ‘lips’condition)and 4-terminal IPG signal at the superficial temporal artery versus time (bottom).(b). Running average of
the impedance versus time (top), relative impedance change versus time (middle), and beats per minute (BPM)versus time (bottom).
Dashed lines signify a transition between states and the solid black line is the average at the first relaxation period.
6
Biomed. Phys. Eng. Express 10 (2024)025036 B Levit et al
4. Discussion
In this paper, we discussed a novel electronic skin
technology designed for analyzing facial characteris-
tics. Through the utilization of soft and non-invasive
electrode arrays, we achieved the capability to simulta-
neously record both bio-potential and bio-impedance
data. This allowed us to effectively record delicate
variations in the diameter of the superficial temporal
artery as a response to facial muscle movements.
We report on direct evidence for a mechanical
muscle-vessel connection. Both in the forearm and the
face, simultaneous sEMG and IPG data reveal a clear
change in the baseline impedance (Z)during muscle
action. The baseline impedance increases, indicating
blood vessel narrowing.
A second phenomenon we investigated in this
paper is the effect of muscle activation on pulse ampl-
itude. During fist clenching, the observed impedance
change due to pulsation (ΔZ)consistently increased
under repetitive actions. In the face, the increase (if
occurs)varied from activation to activation, in part-
icular for the ‘teeth’condition.
Finally, we examined the post-action impedance
change. Unlike the consistent effect in the forearm, in
the face, we observed a change that depends on the
exact muscle action as revealed by the high-resolution
sEMG analysis. In the forearm, the post-action impe-
dance change ΔZdecreased with a stable recovery to
the baseline. No such trend was observed in facial
muscle activation. It is interesting to see that the impe-
dance change (ΔZ)post-action is comparable, if not
even greater, to the impedance change in the ‘lips’or
‘teeth’condition, despite the fact that muscle activity is
stronger during the actions. The variability in this
effect emphasizes the importance of what combina-
tion of muscles is activated over their magnitude. It
demonstrates the complexity of the facial muscle-ves-
sel network: In the face, seemingly similar expressions
could activate different combinations of muscles,
which could lead to a different outcome. Each combi-
nation of activated muscles could result in a different
effect on the IPG signal.
Thus, an important result of our investigation is
how the ‘lips’and ‘teeth’actions differ in their IPG
response: Both lower amplitude and faster recovery
are observed in ‘teeth’versus ‘lips’. Clear responses of
the IPG signals to spontaneous facial expressions
(Supplementary figure C10-C15)and to yawning
(Supplementary figure C8-C9)suggest an underlying
mechanical mechanism. A more expansive invest-
igation is needed to corroborate these findings.
The experimental approach we discussed here
allowed us to observe the direct mechanical link
between muscles and blood vessels, both in the fore-
arm and in the face. Increased blood supply to active
muscles is the most studied muscle-blood phenom-
enon [35–37]. Direct mechanical muscle-blood con-
nection is a documented mechanism in which
contracting skeletal muscles squeeze vasculature,
Figure 4. sEMG and IPG comparison of fist clenching and Strack. (a)Five repeated fist clenching measurements. (Left)Sources
ordered by intensity. (Middle)Pulsation amplitude during and after fist clenching. (Right)Source 6 and 7 during fist clenching. (b)
Four repeated Strack sessions (two measurements in each session).(Top)‘Lips ’condition and (bottom)‘teeth’condition. (Left)
Sources ordered by intensity. (Middle)Pulsation amplitude during and after ‘lips’or ‘teeth’condition. (Right)Source 6, 7, 8, and 10
during facial muscle activity.
7
Biomed. Phys. Eng. Express 10 (2024)025036 B Levit et al
against underlying tissue or bones, causing an effective
narrowing of these blood vessels. The most well-
known example of this regulatory interaction is the
muscular pump in the leg [38–40]. Evidence for a
mechanical muscle-blood connection in the forearm
is also reported [41]. And here, for the first time, we
mapped these effects in the face.
Human blood circulation is complex. It is a care-
fully regulated system in which chemical, neural, and
mechanical processes take place in concert to reach
proper flow through the network of arteries and veins
in response to changing physiological demands.
Abnormalities such aschanges in wall rigidity, mechan-
ical constrictions or long-term application of pressure
change the properties ofvessels and indicate potentially
fatal medical conditions such as stroke and cardiovas-
cular diseases [42–44]. Thus, the reaction of vessels to
the mechanical pressure of muscles can serve as a prog-
nostic tool, and perhaps early detection. The results we
discussed here reveal the complex manner by which
facial muscles can influence blood flow through chan-
ging vessel diameter in the face, shedding new light on
how facial motion can affect physiology, and perhaps
even our psychological state [8,17,18,28]. Future stu-
dies looking into the link between facial expressions and
emotion might benefit from inspecting both muscle
activity and blood flow. A possible additional sig-
nificance of the action of facial muscles on blood vessels
is in assessing clinical outcomes of facial surgeries
[43–45]. Lastly, the results point out a possible route
towards expanding in-vivo analysis of bio-mechanical
properties of arteries [1], for example, investigation of
the active response of arteries [46].
Acknowledgments
This research was co-funded by the European Union
(ERC, Outer-Ret, 101053186), by an Israel Science
Foundation grant (538/22), and by the Ministry of
Innovation, Science & Technology, Israel (3-17857).
The authors thank Anat Mirelman, Galit Yovel, Shira
Klorfeld-Auslender, Zohar Yosibash, and Peter Krebs-
bach for insightful discussions.
Data availability statement
The datasets generated and/or analyzed during the
current study are not publicly available as they rely on
face images. The data that support the findings of this
study are available upon reasonable request from the
authors.
Conflict of interest
YH declares a financial interest in X-trodes Ltd, which
developed the screen-printed electrode technology
used in this paper. YH has no other relevant financial
involvement with any organization or entity with a
financial interest in or financial conflict with
the subject matter or materials discussed in the
manuscript apart from those disclosed.
ORCID iDs
Bara Levit https://orcid.org/0000-0001-9509-2750
Paul F Funk https://orcid.org/0009-0000-4316-4249
Yael Hanein https://orcid.org/0000-0002-4213-9575
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