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Physiological Measurement
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Bio-potential noise of dry printed electrodes: physiology versus the skin-
electrode impedance
To cite this article before publication: Ana Arche-Núñez
et al
2023
Physiol. Meas.
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Bio-potential noise of dry printed electrodes:
Physiology versus the skin-electrode impedance
Ana Arché-Núñez1‡, Peter Krebsbach2,3, Bara Levit4, Daniel
Possti7, Aaron Gerston7, Thorsten Knoll6, Thomas Velten6,
Chen Bar-Haim4, Shani Oz9,10, Shira Klorfeld-Auslender4,
Gerardo Hernandez-Sosa2,3,5, Anat Mirelman8,10,11, Yael
Hanein4,7,8,12
1Madrid Institute of Advanced Research in Nanoscience (IMDEA Nanociencia),
Madrid, Spain
2Light Technology Institute, Karlsruhe Institute of Technology (KIT), Karlsruhe,
Germany
3InnovationLab, Heidelberg, Germany
4School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel
5Institue of Microstructure, Karlsruhe Institute of Technology,
Eggenstein-Leopoldshafen, Germany
6Fraunhofer Institute of Biomedical Engineering IBMT, Sulzbach, Germany
7X-trodes, Herzliya, Israel
8Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
9Department of BioMedical Engineering, Tel Aviv University, Tel Aviv, Israel
10Laboratory for Early Markers of Neurodegeneration, Neurological Institute, Tel
Aviv Sourasky Medical Center, Tel Aviv, Israel
11Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
12 Tel Aviv University Center for Nanoscience and Nanotechnology, Tel Aviv
University, Tel Aviv, Israel
E-mail: hanein@eng.tau.ac.il
Abstract. Objective. To explore noise characteristics and the effect physiological
activity has on the link between impedance and noise. Approach. Dry-printed
electrodes are emerging as a new and exciting technology for skin electro-physiology.
Such electrode arrays offer many advantages including user convenience, quick
placement, and high resolution. Here we analyze extensive electro-physiological data
recorded from the arm and the face to study and quantify the noise of dry electrodes,
and to characterize the link between noise and impedance. In particular, we studied the
effect of the physiological state of the subject (e.g. REM sleep) on noise. Main Results.
We show that baseline noise values extracted from dry electrodes in the arm are in
agreement with the Nyquist equation. In the face, on the other hand, the measured
noise values were higher than the values predicted by the Nyquist equation. In addition,
we studied how different electrode properties affect performances, including electrode
size, shape, and material properties. Significance. Altogether, the results presented
here provide a basis for understanding dry electrode performances and substantiate
their great potential in electro-physiological investigations.
‡AAN, PK, and BL contributed equally to this work.
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Bio-potential noise of dry printed electrodes: Physiology versus the skin-electrode impedance2
1. Introduction
Dry-printed electrodes for electro-physiological monitoring are gaining increased atten-
tion owing to a range of benefits over gel electrodes [1, 2, 3, 4]. Foremost, is their
stability and simplicity, as they do not require gel application and are easy to place
on the body. Furthermore, dry electrodes benefit from a great design versatility that
can optimally accommodate a wide range of applications, such as facial EMG [5, 6],
gait analysis [7], gesture recognition [8], and sleep monitoring [9, 10]. With the ease
of their application to the skin, thin dimensions and dry nature, these electrodes are
ideal for electro-physiological investigations of freely behaving humans [5]. However, as
dry electrodes have no gel to mediate the contact between the electrode and the skin,
the skin-electrode impedance is a major concern and special care has to be directed to
designing the electrode arrays [11, 12].
Baseline noise is one of the most critical parameters in electro-physiological mea-
surements, in particular in applications where very low signals (in the µV range) are
anticipated. Commonly, noise values are predicted from the electrode-skin impedance
which is used to quantify the quality of the interface and to predict contact quality
[13, 14, 15, 16, 17, 4, 18]. In wet electrodes, the conducting gel reduces the skin-electrode
impedance and ensures low baseline noise levels [19]. In EEG, the gold standard is
5-10 kΩ at 30 Hz [20]. In EMG, reported numbers vary considerably, owing to large
variability in experimental conditions primarily electrode position and signal amplitude.
Indeed, the electrode skin impedance is expected to be affected by various parame-
ters. One crucial parameter is the electrode position on the body (e.g. hand, neck, face).
Specifically, significant differences in impedance values of wet electrodes were observed
between cephalic skin and palmar skin [21]. More recently, Bora and co-workers [22]
measured the contact impedance at 10 different body locations showing that impedance
values in the face have the highest inter-subject variability. Kappel et al. measured the
impedance at two different areas of the ear and demonstrated a significant change in
impedance values [23]. Skin electrodes also tend to show a process of time-dependent
stabilization [24]. Previous investigations showed that impedance values in the scalp
were 15-50 kΩ·cm2before stabilization and after 15 min, the impedance was reduced to
5-15 kΩ·cm2. In the realm of dry electrodes, several recent investigations reported novel
electrode materials and fabrications for bio-potential measurements. Impedance values
are within the range obtained with gel electrodes suggesting that good signal-to-noise
ratio (SNR) values could be obtained (see Table 2).
Although impedance values of dry electrodes were previously reported, studies
focusing on noise are scarce. This gap is particularly challenging as the link between
impedance and noise is not straightforward [17]. Primarily, although it is common
to attribute the noise to thermal noise associated with the skin-electrode interface
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Bio-potential noise of dry printed electrodes: Physiology versus the skin-electrode impedance3
impedance (Nyquist equation), this link was not substantiated in measurements
performed with wet electrodes. Clearly, a similar investigation is needed for dry
electrodes. In this paper, we revisit Huigen et al., [17] to explore the link between
electrode-skin impedance and noise in dry electrodes. To do so, we conducted extensive
mapping of electrode-skin impedance and noise values under various conditions. The
noise was derived from the baseline of multiple electro-physiological sessions. To explore
whether thermal noise plays a dominant role we used data recorded from the face and the
hand and compared it with thermal noise values derived from impedance measurements.
Finally, impedance values of different electrodes were measured to explore the effect of
size, location, and material properties.
2. Methods
2.1. Electrodes
Four electrode types were used in this investigation: Commercial pre-gelled electrodes,
inkjet-printed PEDOT:PSS electrodes, screen-printed carbon electrodes (soft and hard),
and inkjet-printed carbon electrodes.
2.1.1. Commercial pre-gelled Ambu Commercial pre-gelled Ambu electrodes of 40 mm
in diameter (Ambu®BlueSensor Q ECG electrodes) were used. These electrodes
contain a wet gel area in the silver/silver chloride sensor region and an adhesive
surrounding to stick them into the skin.
2.1.2. Inkjet-printed PEDOT:PSS electrodes A fabrication process for inkjet-printed
electrodes was used as described previously [24]. In short, a PixDro LP50 inkjet printer
was used to fabricate silver - poly(3,4-ethylene dioxythiophene):polystyrene sulfonate
(PEDOT:PSS) dry electrodes on TPU substrates. The substrates were of the same type
as the ones used for the screen-printed samples. To optimize ink wetting, the TPU was
heated in a vacuum oven (120 °Cfor 10 min,5 mbar, Memmert VO) and subsequently
treated in an Ar plasma oven (Pico, Diener) for 30 s. All inks were filtered through a
0.45 µmPVDF filter prior to deposition. The silver ink (Silverjet, Sigma-Aldrich) was
printed with a Sapphire QS-256/10 AAA printhead (drop volume of 10 pL, Fujifilm) at
a resolution of 1000 dpi and cured on a hotplate at 120 °Cfor 5 min.
Before the deposition of the second layer (PEDOT:PSS), the samples were treated
with an additional 60 s of Ar plasma. The PEDOT:PSS ink (Clevios F HC Solar,
Heraeus) was degassed in an ultrasonic bath for 20 min and then printed with a Dimatix
Materials Cartridge (10 pL, Fujifilm; 1200 dpi). Subsequent heat treatment on a hotplate
(120 °C,10 min) was used to enable the crosslinking process of the (3-Glycidoxypropyl)-
methyldiethoxysilane in the ink (for details see [24]) and thereby increase the resistance
to water and delamination of the PEDOT:PSS film. Finally, a double-sided adhesive
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was used as passivation and the samples were mounted on a PCB analogously to the
screen-printed carbon electrodes.
2.1.3. Screen-printed carbon electrodes Screen-printed carbon electrodes for electro-
physiological and bio-impedance measurements were fabricated as described previously
[5, 6]. First, electrodes traces were screen-printed with silver ink (from Creative Mate-
rials) (125-13T) on 50 and 80 µmpolyurethane sheet (Breathable transparent medical
grade polyurethane/urethane / TPU film on a paper carrier from DelStar Technologies,
inc.). Following silver printing, films were dried on a heater at 50 °Cfor 15 min. Next,
carbon electrodes (124-50T and C200 (Creative Materials) were printed in alignment
with the silver traces. Next, the printed electrodes were dried again on the heating plate
at 50 ◦C for 15 min. After printing, traces were passivated with a double adhesive 80 µm
PU film (from Delstar EU94DS) which was cut to leave the carbon electrodes exposed.
For impedance measurements, the arrays were bonded to metallic traces on a custom-
made printed circuit board (PCB) which was designed to support BNC connections.
2.1.4. Inkjet-printed carbon electrodes Inkjet-printing of the carbon electrodes was
performed using the industrial inkjet printer njet lab of Notion Systems GmbH
(Schwetzingen, Germany) with an industrial Konica Minolta KM1024i print head.
PU substrates (Delstar EU94DS) were first activated by UV ozone treatment. After
this pretreatment, two layers of the silver ink Ag-LT-20 (Fraunhofer IKTS, Dresden,
Germany) were printed at a resolution of 720 dpi and sintered in an oven at 150 °C. These
silver structures serve as conductor paths and contact pads. Onto these structures, the
electrodes were then printed with the carbon ink JR-700HV (Novacentrix, Austin, USA).
Two layers of carbon were printed at a resolution of 720 dpi. The carbon electrodes
were larger than the underlying silver to guarantee the covering of the entire silver in
the electrode area, which is in contact with the skin. After printing, a pre-structured
medical grade double-sided adhesive (3M 1524) was laminated on the PU substrate with
the electrodes. This tape has openings in the electrode areas and acts as an insulation
layer and as an interface to the skin. [25].
2.1.5. Electrode rigidity characterization A set-up for rigidity characterization of the
flexible electrodes was developed to assess the mechanical properties of various electrode
configurations and material combinations. The test samples were placed on a metal
block that comprised two small holes with 1 mm diameter and was connected to a pump
(Supplementary Fig. A1). Negative pressure sucked the foil samples (one without and
one with printed layers) into the small hole. Pressure differences of 250, 500, and 750
mbar were applied and the resulting deformation of the samples was directly measured
by a mechanical profilometer (DektakXT Stylus). The test samples comprised carbon
electrodes, silver electrodes, and combinations of carbon and silver, each produced
on a 80 µmthin PU film by screen-printing, performed by partner TAU and inkjet-
printing, performed by partner Fraunhofer IBMT. All samples showed the expected
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linear deformation behavior and the measurements demonstrated the dependency of
the extent of deformation on the layer thickness (Supplementary Fig. A1). The thickest
screen-printed electrode (C200) had the lowest flexibility, whereas the thinner screen-
printed electrodes (silver and carbon) and the inkjet-printed electrodes from one single
material (carbon or silver) were most deformed. The thin inkjet-printed structures
with thicknesses below 10 µmhave a similar influence on the deformation as the thicker
screen-printed structures.
2.2. Impedance measurements
Bio-impedance measurements were performed with MFIA Impedance Analyzer (Zurich
Instruments) on the skin of 6 healthy volunteers (3 male and 3 female). Bio-impedance
measurements were conducted under 2-terminal (2T) conditions in the 1-1000 Hz range.
Electrodes were connected to the MFIA impedance analyzer and the impedance was
measured 10 min after placement to allow electrodes-skin interface stabilization. The
skin surface was cleaned thoroughly with an alcohol pad prior to electrode placement.
For the bio-impedance measurements, as well as their corresponding bio-potential mea-
surements, participants were sitting at a resting position. When measurements were
taken from the forearm the participant’s arm was relaxed and placed comfortably on a
table.
Thermal noise is evaluated from the Nyquist formula [17]:
V2
th = 4kBT R (1)
where kBis the Boltzmann constant, Tis the temperature, Bis the bandwidth and R
is the resistance. At room temperature the thermal noise is given by [17]:
Vth = 0.13√R(2)
where the units are nV (√Hz)−1.
We compared the thermal noise to the "measured noise", which we dub as the
spectrum bio-potential signal. A 50 Hz notch was applied to the signal before the
spectrum was calculated. Then, using Welch’s method, the spectrum was calculated
over a segment of 30 s. We evaluated the similarity between the estimated (thermal)
noise and the measured noise using relative difference (in percentage relative to the
relax/REM state). Not to skew the measure, detected peaks in the spectra originating
from harmonic noise were smoothed (substrating running average).
2.3. Electrophysiology and noise analysis
We used baseline noise extracted from two data sets: Forearm EMG (16 electrodes, 73
sessions, 14 subjects - 7 females and 7 males) from a finger gesture recognition study [8]
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and facial EMG (8 electrodes, 18 sessions, 12 subjects - 4 females and 8 males) from a
sleep study [10]. In the sleep study, participants were lying in bed. In the finger gesture
recognition study, sEMG signals were measured with participants in three positions:
With the hand resting comfortably on the table while the participant was sitting, with
the hand in an upright position on the table while the participant was sitting, and with
the hand resting comfortably by the participant’s side while the participant was stand-
ing.
Data were recorded with a miniature wireless data acquisition unit (DAU, X-trodes
Inc.), which was developed to allow electrophysiological measurements under natural
conditions. The DAU supports up to 16 unipolar channels (2 µV noise root-mean-square
(RMS), 0.5-700 Hz) with a sampling rate of 4000 S/s, 16 bit resolution, an input range of
±12.5 mV and input impedance of 107Ω. 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 on the Cloud for further analysis. The DAU also includes a 3-axis
inertial sensor in order to measure the acceleration of the hand during the measurements.
The noise level was assessed within the frequency ranges: 0.3-35 Hz for EEG band-
width and 30-350 Hz for EMG bandwidth. To extract the desired signals, a 4th-order
bandpass filter was applied, with the respective cutoff frequencies. Additionally, a 4th
order 50 Hz notch filter was applied to eliminate interference and its harmonics. The
baseline noise was calculated for four different stages and modalities: Wake stage, rapid
eye movement (REM) sleep stage using the sleep array, and forearm EMG.
For the Wake stage, the median root mean square (RMS) was determined based
on the lowest 10 sec of activity during 2 min of relaxation with eyes closed. This phase
is characterized by relaxed muscles and the absence of eye movements, allowing the
evaluation of noise levels during this quiet period. In the REM stage, the median
RMS values were calculated from the lowest 10 sec across all REM epochs, which were
scored by sleep specialists. During REM stages, the absence of muscle atonia allows for
evaluating baseline noise with minimal muscle activity. In the case of forearm EMG,
the median RMS was computed for the relaxation time intervals between sessions of
performing different hand gestures. Calculations were performed using a Python code.
2.4. Participants
All experiments on human skin were conducted on volunteers in accordance with rele-
vant guidelines and regulations under approval from the Institutional Ethics Committee
Review Board at Tel Aviv University (approvals 0005229-1 and 0004877-2) and the
Institutional Ethics Committee Review Board at Tel Aviv Sourasky Medical Center,
(approval 0336-20) in accordance with the Helsinki guidelines and regulations for hu-
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Bio-potential noise of dry printed electrodes: Physiology versus the skin-electrode impedance7
man research. Informed consent was obtained from all subjects. The authors confirm
that any identifiable participants in this study have given their consent for publication.
3. Results
Bio-potential measurements with soft and dry electrode arrays are typified by a high
signal-to-noise ratio (SNR) and stability against mechanical artifacts [11, 6]. Fig. 1(a-d)
shows several examples of bio-potential signals recorded with screen-printed dry carbon
electrodes: (a) EEG alpha waves recorded from the forehead during relaxation with eyes
closed, (b) EOG REM patterns recorded with electrodes positioned at close proximity
to the eyes and (c) EMG signals recorded from the chin during swallowing (calibration
step), and (d) EMG recorded from the arm during finger gesturing. Figs. 1(e) and 1(f)
show the electrode arrays used to capture the signals from the face Fig. 1(a-c) and the
arm Fig. 1(d), respectively. Electrodes were 9.5 and 4.5 mm in diameter for the facial
and forearm arrays, respectively.
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Figure 1: Screen-printed carbon electrode arrays for EEG and EMG applications
demonstrate high SNR. (a) EEG signal recorded from the forehead during relaxation.
(b) EOG signal recorded at close proximity to the eyes during REM. (c) EMG signal
recorded from the face. (d) EMG signal recorded from the forearm. Shaded areas in
the data indicate noise. (e) Facial EMG array. (f ) EMG array on the forearm.
Although signal-to-noise (SNR) is an important parameter, it is limited in
comparing different electrode technologies. Signal values vary markedly (i.e. depending
on the subject and measured activity) and evaluation of data quality from SNR values
is insufficient. Therefore, baseline noise estimates are needed. Here we use data from
two multi-subject multi-session studies, in which we collected an extensive amount of
noise data with the dry carbon electrodes (the results are published elsewhere, [10]):
A sleep study ([10]) with 18 sessions using the facial array (1(e)), and a finger
gesture recognition study [8] (73 sessions) using a 4 by 4 electrode array (Fig. 1(f)).
Importantly, all recorded sessions started with an initial calibration stage that included
a relaxation period which was used to evaluate the baseline signal.
Baseline noise can be readily estimated from low-activity sections of the data as
can be seen in Fig. 2. Yet, a major interfering factor in such measurements is residual
electro-physiological activity (i.e. muscles, heart, brain) that may contribute to higher
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than expected noise values [17] [26]. To demonstrate this challenge, we analyzed bio-
potential data recorded before and during REM sleep. Owing to muscle atonia, typical
for REM sleep in healthy individuals, EMG, EOG, and EEG signals during REM show
reduced baseline, compared with other sleep stages (see Fig. 2 for a comparison of
REM versus wakefulness recordings). Notably, the histogram of noise values (Fig. 2
lower panel) demonstrates the significant difference in the baseline noise that is due to
changes in physiological conditions (REM: 4.8µVversus wakefulness: 9.0µVfor EMG).
Figure 2: The effect of physiological condition on noise. EEG, EOG, and EMG
data during wake (a) and REM (b) recorded with 9.5 mm dry carbon electrodes. (c)
Histogram of noise levels for different dry electrodes. EEG and EOG noise levels was
calculated for 0.3-35 Hz and EMG was calculated for 30-350 Hz.
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Noise values are commonly estimated using the Nyquist equation (3√KBT·R=
0.13·√R), although its accuracy in physiological measurements is under debate. Specif-
ically, it was previously argued that noise values measured in gel electrodes at rest are
significantly higher than those expected from the Nyquist equation [17][27][26]. Here we
revisit this observation for dry electrodes in the EMG and EEG frequency bands, both
at the face and the arm. We hypothesized that the previously reported discrepancy in
physiological noise is associated with the electrode’s location. Fig. 3(a) shows mea-
sured noise spectra, of carbon electrodes positioned on the forearm during fist clenching
(orange) and rest (green). The spectra were evaluated on bio-potential signals (with
50 Hz notch filter) over 30 s. Also plotted are the estimated noise derived from a
two-terminal impedance measurement from the same location (blue), and the amplifier
noise, obtained by short-circuiting the inputs (purple). As expected, during muscle ac-
tivity (fist clenching) the signal increases in the EMG frequencies. Importantly, during
relaxation, the measured noise (green) shows good agreement with the estimated noise
(blue).Additionally, the magnitude of the thermal noise and the amplifier noise are close
(approximately 20% averaged over the entire frequency range). The overall measured
noise is the square root of the sum of the squares of the different noise sources including
that of the amplifier, the skin-electrode interface thermal noise, and the physiological
background noise. Since the amplitude of the amplifier noise is relatively low under
most conditions, its contribution is generally insignificant. A similar measurement was
performed with inkjet-printed carbon and is shown in Supplementary Fig. C2.
Next, we compared the estimated and measured noise of electrophysiological signals
recorded from the face. Fig. 3(b) presents the thermal and measured noise (the spectra)
versus frequency for carbon electrodes positioned on the face during wake (the subject
was in bed and just before falling asleep) and during REM sleep. The wake segment
(orange) has a clear alpha peak and significant tonic EMG activity (even though the
subject was in a relaxed state, as evident by the alpha signature). The spectrum (mea-
sured noise) of the REM segment (green) has no EMG activity, and thus the noise is
significantly reduced compared to the spectra during wakefulness. As in the case of the
arm, muscle activity increases the noise, compared to the relaxed state. However, unlike
the arm, the difference between the estimation (derived from the Nyquist equation) and
the measured noise is much more pronounced, in particular for the low-frequency range.
Lastly, we make note that the estimated noise, derived from the Nyquist equation and
two-terminal skin-electrode impedance measurement is lower than the amplifier noise
(as also reported in [28]). The difference between the two quantities increases with fre-
quency. In the face, the noise of the amplifier is the limiting factor, and lowering the
skin-electrode impedance does not greatly impact the overall measured noise.
To generalize these results, in Table 1, we summarize baseline noise levels for screen-
printed carbon electrodes (4.5 and 9.5 mm positioned at the arm and face, respectively)
from multiple recording sessions (73 forearms EMG and 18 sleep sessions, see Methods).
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Figure 3: Thermal noise (0.13√R) and measured noise (over 30 s) versus frequency (a)
For the forearm during muscle activity and rest. (b) For the face during alpha activity
and REM.
For each such session, a low-activity (relax) period was automatically identified and the
RMS value of the noise was calculated. Typical EMG noise (30-350 Hz) values were 8.3,
9.0, and 4.8 µV for the arm, the face during wake, and during REM respectively. Typical
EEG noise (0.3-35 Hz) was 9.9 and 7.2 µV for wake and REM respectively. Comparing
the estimated and measured noise it is evident that in the forearm, unlike the face,
measured noise values are closer to their predicted values in a relaxed state (relative
difference of 27% and 87% in the forearm and face respectively, see Supplamanetry Fig.
D1-D2 for additional examples). In the face, even in REM where muscle activity is re-
duced, noise values are still higher than expected, especially in the low-frequency range,
indicating the effect of other ongoing physiological activity on baseline values.
Table 1: RMS noise in the EEG (0.3-35 Hz) and EMG (30-350 Hz) bands measured
from baseline noise at different locations. Sleep study sessions: 18 sessions, 8 electrodes,
forearm study: 73 sessions, 16 electrodes.
Location State Noise [µV] Noise [µV]
(0.3-35 Hz) (30-350 Hz)
Face Wake 9.9 ±3.5 9.0 ±3.7
Face REM 7.2 ±2.9 4.8 ±2.2
Face (0.13 ·√R) Rest 0.61 ±0.055 1.04 ±0.14
Outer Forearm Rest 6.2 ±5.2 8.3 ±3.7
Outer Forearm (0.13 ·√R) Rest 3.5 ±0.15 8.4 ±0.14
Having established the complex link between baseline noise and the impedance of
screen-printed electrodes, we now turn to explore in more detail electrode impedance
values, focusing on how different parameters affect the impedance and whether it is pos-
sible to identify parameters that may contribute to better electrode performances. We
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tested several alternative dry electrodes to study the effect of electrode material on the
skin-electrode impedance: Screen-printed (harder (C200) carbon, and softer (124-50T)
carbon inks) carbon, inkjet-printed carbon and inkjet-printed PEDOT:PSS electrodes.
For simplicity, we performed most of the impedance measurements of the printed elec-
trodes at the neck and the arm with varying electrode parameters: Electrode size,
passivation size, printing ink, passivation shape, and PU thickness film.
As a reference, we first present the behavior of commercial gel electrodes. In Fig.
4a we show the contact impedance (CI) of gel electrodes at three different positions:
Arm, neck, and forehead for one subject. The results show that the arm demonstrates
higher impedance values than the forehead and the neck, in agreement with previous
reports [22]. Impedance values at the neck are higher than the forehead but share with
the face a similar frequency dependence. In Fig. 4b we compare the commercial gel
electrodes alongside the three types of dry electrodes (PEDOT:PSS, soft carbon, and
hard carbon) at the neck (values are normalized by the area of the electrode). The
diameter of the commercial gel electrodes is 18 mm, and the diameter of the dry elec-
trodes is 9 mm. Notably, the gel electrodes have a lower CI compared to all of the dry
electrodes. However, this difference is reduced following normalization. In particular,
close to the 1 kHz, the impedance of the different electrode types converges, suggesting
negligible differences for higher frequencies. Moreover, while the difference between the
dry electrodes is not striking, it should be noted that the hard carbon has the highest
impedance values, followed by the SC, and finally PEDOT:PSS. Evaluation of inkjet-
printed carbon compared to SC and gel electrodes is shown in Supplementary Fig. C1.
Fig. 4c shows the dependence of the CI on size. As expected, electrode size is
negatively correlated with impedance values (i.e., big electrodes show small impedance
values), independent of the electrode type. Of note, at 4 mm diameter, the soft and
hard carbon electrodes have similar impedance values, and the PEDOT:PSS electrode
has the lowest impedance. To evaluate the impact of the shape on the impedance
values, we designed and tested two-star shapes: 5-pointed star and 8 pointed-star (see
Supplementary Fig. E1). Fig. 4(d) shows the impedance values for both shapes (dry
electrodes), at the neck, normalized by area to exclude the influence of the electrode
surface area on the measurements. We observe that the 8-pointed star shape has
lower impedance values. The superiority of the larger electrode size as well as the
8-pointed star shape is independent of the type of electrode used and is likely to be
associated with the manner by which the dry electrode achieves conformal contact with
the skin. Furthermore, the three dry electrodes appear to exhibit a distinct dependence
on frequency. This is most apparent when comparing the slope of the carbon electrodes
relative to the PEDOT:PSS electrodes. The PEDOT:PSS electrode has a flatter slope
for very low frequencies (up to 10 Hz), compared to the carbon electrodes which exhibit
a sharper trend. Further comparison of 9 mm,4 mm, 5-pointed and 8-pointed star,
across PEDOT:PSS, SC and HC, is shown in Supplementary Fig. B1.
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Figure 4: (a) Contact impedance of gel electrodes for varying locations (arm, neck, and
head). (b) Comparison of the gel vs. dry electrodes at the neck, normalized by area.
Shaded areas indicate the variance across repetitions. (c) Comparison of dry electrodes
for 9mm and 4mm (at the neck). (d) Comparison of dry electrodes for different star
shapes (at the neck).
4. Discussion
In this investigation, we presented the performances of dry-printed electrodes for elec-
trophysiological applications, specifically focusing on impedance and noise values. Here
we make the distinction between printed dry electrodes which are made via a printing
process (i.e. screenprinting or inkjet-printing) on soft substrates and a wide range of
other dry electrodes which have been suggested in the past and utilize a wide range
of fabrication techniques (e.g. casting, microelectromechanical (MEMS) fabrication)
[29, 30]. We showed that normalized impedance values of screen-printed carbon and
inkjet-printed PEDOT:PSS are similar to those obtained with gel electrodes. Further-
more, the dry-printed electrodes presented here appear to show many of the hallmarks
of gel electrodes: Strong dependence on size, strong dependence on position on the body,
and large variability between subjects and experiments. Of the various systems we char-
acterized, inkjet-printed PEDOT:PSS electrodes appear to have the lowest impedance
values and appear to be excellent candidates for future applications. What is more,
the dry-printed electrodes are printed on soft substrates allowing both easy and quick
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placement of large arrays and high conformity on the skin. The conformity in particular,
enables subjects to move without hindering the quality of the measurement. Overall,
with their excellent stability on the skin along with their stable and low noise levels,
dry-printed electrodes are indeed an excellent alternative technology for many electro-
physiological applications.
The main focus of our investigations was the analysis of noise values under dif-
ferent physiological conditions. We showed that physiological states can have a major
impact on noise. In the forearm, muscle activation, as expected, impacts noise levels
even at very low frequencies. In the face, noise during sleep is lower than baseline
noise during wake but still higher than expected thermal noise values. An interesting
and puzzling phenomenon is the persistent physiological noise under what is seemingly
rest conditions. Initial measurements exploring this phenomenon are presented in the
Supplementary Material (Fig. D2). By exploring the noise at different locations, and
different electrode sizes (Fig. D1) we can clearly see locations where there is almost no
discrepancy between the measured and calculated noise (Nyquist), while in some regions
a clear discrepancy is observed (for example comparing the face to the arm). To explore
if this issue is affected by blood pulsation, as a possible source of noise, we looked at
nearby electrodes positioned on the wrist (Fig. D3) and how their noise was affected
by blood flow blockage. Some electrodes show a pronounced increase in the noise in
response to blood blockage. A possible origin for this behavior is proximity to blood
vessels and their effect on the low-frequency noise (Fig. D3). In the face, matters are
more complex: Although we expect blood flow to affect the measurements in the face,
we also expect some baseline neuronal activity to play a role, even in the lower part
of the face. Overall, as was previously reported for gel electrodes [17], it appears that
background physiological noise (which depends on the physiological state of the subject
and position of the electrodes on the body) dominates measured baseline noise levels
in a wide range of frequencies. This topic is beyond the scope of this paper and in the
Supplementary Material we provide some more insights regarding future directions.
We contrast our results with previously reported noise data for dry electrodes
(printed and otherwise). In Table 2, we summarize previously reported noise and
impedance values for EMG and EEG frequency bands along with results from this inves-
tigation. It is evident that low-impedance values do not contribute to reducing baseline
noise, in particular for the low-frequency range and the face. This result is consistent
with the results we presented above and echoes the results presented previously for gel
electrodes [17]. The same effect is observed in other dry electrode systems. For exam-
ple, the effect of impedance on background noise was considered in dry MEMS-based
electrodes. MEMS-based pyramid micro-needle electrodes for long-term electrophysio-
logical measurement is an extensively studied approach. In these dry electrodes, the
electrode-skin impedance is reduced owing to improved contact between the electrode
and the skin. In agreement with the results we discussed here, the quality of EEG
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signals recorded by micro-needle electrodes is similar with those recorded with stan-
dard wet electrodes, despite much lower impedance [31]. Another type of commonly
explored dry electrodes is textile electrodes. In Ref. [28] the skin-electrode interface
noise performance of several un-gelled, textile-based electrodes has been characterized
and contrasted with a gelled adhesive electrode. The noise associated with the electrodes
themselves was found to be lower than that introduced by the amplifier, in agreement
with our analysis of dry-printed electrodes. For many applications, modern high-input
impedance amplifier technology supports high contact impedance measurements and the
focus on low electrode-skin impedance values should be taken with more careful consid-
eration of technical needs (such as stability against line interference when relevant). It
is likely that some of the high noise values reported previously for the EMG range (even
for very low contact impedance values) are related to experimental conditions.
Finally, in our measurements, we used very little or no skin preparation. Abrasion
was not used in any of the experiments to prevent skin irritation and discomfort. For
sEMG noise values obtained are sufficient for most applications and further reduction
of the impedance is not necessary (save stability against line interference). For sen-
sitive EEG measurements requiring reduced noised levels (e.g. ERP measurements),
skin abrasion can help in reducing electrode-skin contact impedance, but this reduction
may not necessarily contribute to reduced noise. The skin-electrode contact impedance
depends not only on the condition of the skin, but also on the absence of hair, gender,
and ethnicity of the subject. In the design of the experiment, there was an effort to have
about the same number of female and male participants. Even so, variability is notice-
able (see for example Fig. 4(a-b), and the variability presented in Table 1) should be
taken into account when proceeding with electro-physiological measurements. Although
we did not specifically investigate the impact of gender, we anticipate that these varia-
tions will influence only the skin-electrode impedance rather than significantly affecting
the main conclusions of this paper, which is the significant impact of physiological ac-
tivity.
To summarize, in this investigation we established the baseline noise values of
printed electrodes at different locations and conditions. By analyzing impedance and
noise data, we demonstrated that the noise can be associated with the Nyquist equation
(Table. 1) under some conditions (outer forearm). The association between impedance
and noise can be evidenced only at a full relaxation state. Finally, we presented an
extensive investigation of dry electrode impedance showing how better electrodes with
better impedance can be produced.
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Table 2: Impedance values and noise for EMG and EEG frequency bands, from the head and neck*
Electrode Type
Surface
Area
[mm2]
CI
(10 Hz)
[kΩ]
Norm.
CI (10 Hz)
[kΩ·mm2]
CI
(30 Hz)
[kΩ]
Norm.
CI (30 Hz)
[kΩ·mm2]
RMS Noise
[µV] Source
3D-printed Polylactic
acid coated with silver
88 < 3 260 < 2 16 8 (EEG)
[18]
110 < 3 340 < 2 230 5 (EEG)
140 < 3 410 < 2 280 16 (EEG)
64 < 4 250 < 2 130 16 (EEG)
28 < 4 110 < 2 56 6 (EEG)
Drytrode (Ag/AgCl Dry) 31 < 2 62 < 2 62 1 (EEG)
Polyimide-based flexible microneedle
array (PI-MNA) by micromolfding 36 4 150 4 130 < 10 (EMG) [32]
Polyimide-based flexible microneedle
array (PI-MNA) by micromolding
coated with Au
36 110 4000 56 2000 < 10 (EMG)
Pre-gelled Ag/AgCl J92SG (Covidien) 1900 250 480000 - - 150 (EMG)
[33]
Polyamide coated with
silver textile electrode
1600 180 280000 - - 130(EMG)
630 330 200000 - - 130 (EMG)
23% Copper, 20% Nickel and
57% Polyester textile electrode
1600 450 720000 - - 130 (EMG)
630 650 410000 - - 130 (EMG)
17% Silver and 83%
Nylon textile electrode
1600 580 930000 - - 130 (EMG)
630 770 48000 - - 130 (EMG)
Dry screen-printed SC* 64 140-670 9000-42000 93-430 5900-28000 4.8 (EMG) This
study7.2 (EEG)
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*CI measurements are evaluated from the head and neck.
Acknowledgments
This work was financially supported by the Deutsche Forschungsgemeinschaft (DFG,
German Research Foundation) through grant HE 7056/4-1, by the German Federal
Ministry of Education and Research (BMBF) in the "Innovations for Production,
Services, and Work of Tomorrow" program with the funding numbers 02P17W000 and
02P17W001, managed by the Project Management Agency Karlsruhe (PTKA), and
by the Israel Science Foundation (1355/17). The authors have confirmed that any
identifiable participants in this study have given their consent for publication.
5. 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. SO,
DP, and AG are employees of X-trodes Ltd.
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