Signal Quality in Dry Electrode EEG and the Relation to

Skin-electrode Contact Impedance Magnitude

Alexandra-Maria T

aut¸an

, Vojkan Mihajlovi

, Yun-Hsuan Chen

, Bernard Grundlehner

Julien Penders

and Wouter Serdijn

Faculty of Electrical Engineering M & CS, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands

Holst Centre / imec-nl, 5656 AE Eindhoven, The Netherlands

imec, Kapeldreef 75, 3001 Leuven, Belgium

Keywords:

EEG, Dry Electrodes, Gel Electrodes, Signal Quality, Evaluation Framework, SSVEPs, Skin-electrode

Contact Impedance, SNR, Correlations, Coherence.

Abstract:

Current EEG research approaches are focusing on developing new dry electrode EEG (electroencephalogram)

systems providing a high enough signal quality for a wide range of applications. This study proposes several

parameters for evaluating signal quality of dry electrodes and relates the results to skin-electrode contact

impedance magnitude values. The EEG recordings of a Ag/AgCl pinned electrode and a ﬂexible polymer

pinned electrode are evaluated through a comparison to conductive gel electrode recordings. The experimental

setup was made up of two EEG acquisition systems connected in parallel. The protocol included open eyes,

closed eyes and steady-state visually evoked potentials (SSVEP) sessions in both seated and walking in place

conditions. The parameters used for evaluation were signal correlations, signal coherence and signal-to-noise

ratios (SNRs). Results showed that the three proposed parameters provided equivalent outcome for signal

quality estimation for the same recordings. There was no relation reported between the deﬁned signal quality

and the skin-electrode contact impedance in either dry or gel electrodes, although high impedance variations

were present among subjects. However, larger impedance magnitude and impedance magnitude variations,

and lower signal quality is observed for dry electrodes compared to gel ones.

1 INTRODUCTION

Research in the ﬁeld of medical technology is

currently focusing on developing devices that

can facilitate disease prevention and remote

monitoring for an easier, more successful patient

treatment, while also reducing costs. Due to its

non-invasive nature and high temporal resolution,

scalp electroencephalographic signals (EEGs)

have good prospects for many applications.

Electrical activity of the brain can be useful in

the diagnosis and monitoring of several neurological

conditions, including the detection of epileptic

seizures, diagnosis of sleep disorders or stroke

rehabilitation (Teplan, 2002). Other applications

include brain computer interfaces (BCIs) used either

in rehabilitation of impaired individuals or for

communication with locked in patients (Minguez

et al., 2009), cognitive enhancement trainings

for ADHD (Moriyama et al., 2012), and remote

monitoring of drivers (Lin et al., 2005).

Currently available EEG technologies are mostly

used in controlled research and clinical environments.

One of the biggest limitation comes from the

electrodes used to obtain good signal quality. A

widely accepted method of acquiring high quality

EEG signals is through conductive gel electrodes and

involves skin preparation. Skin preparation includes

skin abrasion and cleansing to remove dead cells from

the top layer of the epidermis, causing a decrease

in the skin-electrode contact impedance. After this

step, the electrodes with conductive gel are applied.

This procedure is cumbersome, uncomfortable and

can be painful for the patient. If proper care is not

taken, adjacent electrodes might get short circuited

in high electrode density montages. Moreover, the

conductive paste might dry over time, increasing

the skin-electrode contact impedance. Therefore, to

ensure proper EEG recordings, a trained technician

is required for both gel electrode application and for

maintenance throughout the entire measurement.

Several research groups are focusing on

Tautan A., Mihajlovic V., Chen Y., Grundlehner B., Penders J. and Serdijn W..

Signal Quality in Dry Electrode EEG and the Relation to Skin-electrode Contact Impedance Magnitude.

DOI: 10.5220/0004738700120022

In Proceedings of the International Conference on Biomedical Electronics and Devices (BIODEVICES-2014), pages 12-22

ISBN: 978-989-758-013-0

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

improving dry sensor technologies to develop a

more practical, easy-to-use, EEG measurement

system. Although several types of dry electrodes

are already commercially available, EEG users

and clinicians are reluctant to adopt them in their

regular practices as the lack of conductive gel

implies a higher skin-electrode contact impedance

and makes the recordings more susceptible to noise

and interference. To this day, the quality of these

electrode types has not been proven to reach that of

the standard gel electrodes. Hence, there is a need

to develop a method of testing the quality of the

signal obtained from the newly designed biomedical

sensors.

A literature survey on the available state-of-the-art

EEG signal quality evaluation methods revealed that

several protocols are available but there is no clear

consensus on the best evaluation procedure (T

aut¸an

et al., 2013). The lack of agreement on what high

EEG signal quality means comes from the fact that

different applications require high quality in different

aspects of the EEG signal, i.e., a signal that provides

good performance in BCIs might prove insufﬁcient

for clinical diagnosis. A general purpose evaluation

framework should take into account as many signal

features as possible, from the time, frequency and

spatial domain, to ensure a good quality for a wider

variety of applications.

Due to the temporal, spatial and subject variability

of the EEG signal, all procedures of evaluating dry

electrode recordings make use of a comparison to

gel electrode recordings through either a parallel

method (the two sensor types record concurrently)

or a serial method (the two sensor types record in

turn from the same scalp positions) (Rufﬁni et al.,

2008). Most encountered parameters for evaluating

EEG signal quality are dry-gel signal correlations

and comparisons of the power spectral densities

(Rufﬁni et al., 2008; Gargiulo et al., 2010; Estepp

et al., 2005). Other evaluation parameters include

signal-to-noise ratios of steady-state visually evoked

potentials (Chi et al., 2012) and deﬂection amplitudes

of P300 components of event related potentials

(ERPs) (Zander et al., 2011). Performance of the

electrodes in several applications, such as BCIs and

cognitive monitoring, are also used as an indication

of signal quality (Estepp et al., 2005; Gargiulo et al.,

2010; Sellers et al., 2009).

When using gel electrodes, it is generally

considered that the signal quality is good when

the impedance magnitude value measured is low

(typically below 5kΩ). Only one study found in

literature reported that EEG signal quality did not

modify when skin abrasion was not used and the

skin-electrode contact impedance reached values of

40kΩ (Ferree et al., 2001). However, it is not known

whether even higher impedance, or difference in

impedance among electrodes would result in a lower

signal quality. Also, to the best of our knowledge,

the relation between signal quality and skin-electrode

contact impedance is not addressed in the case of dry

electrodes. We believe that since the impedance is

much higher and since it can be quite different among

electrodes it can also be used to estimate the signal

quality obtained.

This paper builds on a previous study of EEG

signal quality evaluation (T

aut¸an et al., 2013),

improving the experimental setup and incorporating

skin-electrode contact impedance measurements. In

our previous study, several parameters were deﬁned

to characterize signal quality. The limitations we tried

to overcome in this evaluation are the accuracy of

the visual stimulation rendering, the synchronization

of the stimulation with the recordings and improper

contact of the electrodes with the scalp for some

subjects due to inadequate headset design. The

procedures used for signal quality evaluation include

open eyes, closed eyes and steady-state-visually

evoked potentials (SSVEPs) recordings performed

both while the participant is seated and walking.

The parameters deﬁned to quantify signal quality

include: signal correlations, signal coherence and

signal-to-noise ratios.

The paper is organized as follows. The second

section describes the experimental setup, the protocol

and the data analysis methods. In the third

section, results are presented and discussed. Lastly,

conclusions are drawn and suggestions for further

research are presented.

2 METHODS

2.1 Experimental Setup

The materials used to build the experimental setup are

the following:

• 6 standard gel-ﬁlled Ag/AgCl cup electrodes

(10mm diameter) used as a reference system

• 4 BioPac EL120 Ag/AgCl dry pin electrodes

(10.2mm diameter with 12 pins of 1mm width)

used as test electrodes

• 4 conductive polymer electrodes with ﬂexible pins

(13mm diameter with 15 pins of 1.2mm width)

used as test electrodes (Chen et al., 2013)

• wireless EEG headset used as rigid support for the

dry electrodes (Patki et al., 2012)

SignalQualityinDryElectrodeEEGandtheRelationtoSkin-electrodeContactImpedanceMagnitude

• EEG boxed system used for connecting the gel

electrodes (Mihajlovi

c et al., 2013)

• PC for recording and displaying visual

stimulation

This setup is consistent with that found in the

previous work: a parallel measurement system is

used to make a comparison between signals recorded

with dry and gel electrodes. Here, different tools

are used to incorporate impedance measurements

and to improve the shortcomings of the previous

setup by providing more accurate stimulation and

better synchronization. To prove the validity of

the developed evaluation framework, two types of

dry electrodes are tested: Ag/AgCl and polymer

electrodes.

2.1.1 Data Acquisition and Stimulation Display

EEG signals and impedance data are acquired

concurrently from dry and gel electrodes using

the EEG v2.0 wireless headset and boxed system,

respectively. These two systems include the same

electronics, ensuring that all signals are collected in

the same way. Each measurement system contains the

following: proprietary active electrodes, EEG analog

front-end application-speciﬁc integrated circuits

(ASIC) with an input impedance of 1.2 GΩ at 10Hz

and a built-in current generator, microcontroller,

radio and power management circuitry (Patki et al.,

2012).

These systems enable continuous skin-electrode

contact impedance monitoring per channel. This is

done by injecting a square wave current at a frequency

of 1024 Hz through the active electrode front ends

(Patki et al., 2012). The amplitude of the wave is set

manually by the operator for each subject according

to his/her skin characteristics and the electrodes

used. Typical values are 10nA, 20nA or 50nA.

Impedance magnitude is obtained by combining the

demodulated ﬁrst harmonic of the in-phase and

quadrature components of the impedance signals.

The acquisition system is limited by the 5mV

dynamic range of the input ampliﬁer. In order to keep

the acquired signal unattenuated, the maximum input

resistance is 500kΩ when the injected current is at the

minimum of 10nA.

Functions from the MatLab Psychtoolbox were

used to obtain accurate rendering of the SSVEP,

while taking into account the different processes

running in the background (Brainard, 1997). Since

both EEG systems communicate wirelessly to their

corresponding receivers, time synchronization is

performed in the software through a Matlab script.

The script handles the data packets received from both

systems and synchronizes them with respect to each

other and to the rendered stimuli.

2.1.2 Electrode Positions

As the framework aims at comparing dry and gel

sensors, the electrode arrangement is extremely

important. First, consistency in positioning must be

maintained between participants. Second, relevant

locations should be chosen according to the type of

information that needs to be obtained (from the type

of sensory information provided as stimuli). Third,

the EEG signal represents the summed activity of

millions of neurons and thus the spatial variability

introduced should be accounted for.

To this end, the electrode conﬁguration is similar

to that presented by (Estepp et al., 2005). Two

groups of one dry electrode and two gel electrodes

were placed on the scalp of the participant on

the vertices of an equilateral triangle with a 2cm

edge (Fig. 1). The dry electrodes were positioned

using the EEG headset. They were centred at

the Cz and Pz positions of the standard 10-20

International Positioning system. The gel electrodes

were positioned with the help of metal markers.

Separate reference and ground electrodes are used

for the dry and gel systems to avoid any additional

differences introduced by the different skin-electrode

contact impedance. The two references are placed

close together behind the right ear, while the two

ground electrodes are located behind the left ear.

Comparisons are made between the dry test

electrode and one of the gel electrodes placed in its

vicinity. To give an estimate of the effects of spatial

variability, the same computations are made between

the two adjacent gel electrodes.

Figure 1: Electrode positioning system. The yellow circles

represent dry electrodes, whereas the blue circles are gel

electrodes.

BIODEVICES2014-InternationalConferenceonBiomedicalElectronicsandDevices

2.2 Protocol

Six subjects (all male) aged between 25 and 37 years

volunteered for participation in the experiment. After

being informed of the content of the experiment and

making sure that they do not present any skin allergies

or disorders triggered by oscillatory light stimuli,

participants signed a consent form. All of them

presented normal or corrected to normal sight.

The protocol was approved by the internal review

board of Holst Centre. The total experimentation

time per participant amounted to 60 minutes. The

participants were comfortably seated at a distance

of 50 cm from the LCD display where the visual

stimulation was presented. They were advised to

avoid movement as much as possible to reduce the

appearance of motion artifacts. First, the wireless

headset was equipped with the four Ag/AgCl dry

electrodes and was mounted on the head of the

participant. After that, the skin was abraded to

eliminate dead cells and the gel electrodes were

applied. The quality of the recordings was checked

by the operator through visual inspection of the

obtained signal. Also, setting the appropriate value

of the injected current such that the system can

perform reliable impedance measurement was done

by the operator. Then, the ﬁrst recording stage was

performed. In the second stage, the Ag/AgCl dry

electrodes were replaced with the polymer electrodes

and the same protocol was repeated. The protocol

consisted of the following paradigms: continuous

recordings and SSVEP stimulation.

2.2.1 Continuous Recordings

Continuous EEG recordings are obtained from four

paradigms. In the ﬁrst one, the participant had to

keep his/her eyes open for approximately 1 minute

(open eyes) while seated. In the second one, the

participant had to close his/her eyes for about 1

minute (closed eyes) while seated. For the last two

paradigms the subject performed the same two actions

while walking in place for about 1 minute.

2.2.2 SSVEP Stimulation

The stimulation in this case was a white ﬂickering

square centered on a black screen. The stimulation

frequency was 4Hz. This value was chosen to have

the ﬁrst harmonic of the response outside the alpha

range (8-13Hz) and so avoid interference. Subjects

had to observe the stimulation for approximately 1

minute in two conditions: once while seated (SSVEP

seated) and once while walking in place (SSVEP

walking).

2.3 Data Analysis

Data processing was performed in Matlab. In the

pre-processing stage, both the EEG and impedance

signals were band pass ﬁltered between 2-30Hz. A

Chebyshev type II ﬁlter was applied forward and

backwards on the data to eliminate distortion (Acunzo

et al., 2012). Severe artifacts are removed from all

recordings. This is done manually by the operator

with the help of a thresholding algorithm based on the

standard deviation of the signal (T

aut¸an et al., 2013).

The comparison of the dry and gel recordings

should provide information from both the time and

frequency domain. Thus, several parameters were

computed in both domains: signal correlations (time),

signal coherence (frequency) and SNR (frequency).

For validation of the framework, mean skin-electrode

contact impedance values are also reported and they

are compared to the signal quality obtained at each

electrode. This section presents the methods used for

deﬁning and computing these parameters.

2.3.1 Signal Correlations

Pearson’s product moment correlations are used

to quantify the similarity between the dry and

wet recordings as they provide information on the

time coupling and wave morphology (Guevara and

Corsi-Cabrera, 1996). Correlation coefﬁcients are

computed between dry-gel electrode pairs (1-5, 2-7)

and also between gel-gel pairs (5-6, 7-8) on the open

eyes and closed eyes recordings.

2.3.2 Signal Coherence

While signal correlations give an idea of the time

domain similarity of two signals, signal coherence

shows the stability of the similarity by looking at

the frequency content. They provide information on

the changes in power and phase of the signals with

respect to each other, disregarding signal polarity

(Guevara and Corsi-Cabrera, 1996). The coherence

function between the two signals is computed using

Welch’s method on a window of 1 second and with

a window overlap of 75%. The mean coherence is

computed over the band between 2-30Hz. Values are

obtained for the dry-gel pairs (1-5, 2-7) and for the

gel-gel pairs (5-6, 7-8) on the open eyes and closed

eyes recordings.

2.3.3 Signal-to-Noise Ratio

A signal-to-noise ratio (SNR) is deﬁned to quantify

the level of contamination of the recordings observed

in the frequency spectrum. The alpha wave peaks and

SignalQualityinDryElectrodeEEGandtheRelationtoSkin-electrodeContactImpedanceMagnitude

Table 1: Mean correlation values across participants.

Cz Pz

Paradigm 1-5 1-6 5-6 2-7 2-8 7-8

Open eyes seated 0.77 0.75 0.93 0.71 0.70 0.91

Electrode A Closed eyes seated 0.82 0.81 0.97 0.80 0.78 0.94

Ag/AgCl Open eyes walking 0.27 0.29 0.78 0.30 0.32 0.83

Closed eyes walking 0.43 0.42 0.79 0.46 0.43 0.79

Open eyes seated 0.48 0.37 0.85 0.46 0.46 0.93

Electrode B Closed eyes seated 0.60 0.59 0.96 0.53 0.50 0.95

Polymer Open eyes walking 0.35 0.29 0.83 0.32 0.26 0.71

Closed eyes walking 0.50 0.41 0.80 0.44 0.24 0.65

the SSVEP responses are stronger when less noise

is present on the recordings and thus can be used to

estimate the difference in noise content of the dry and

gel electrode signals. Assuming that the noise signal

is proportional to the standard deviation of the signal

(Mihajlovi

c et al., 2012), the following deﬁnition is

proposed:

SNR =

mean(PSD

band o f interest

)

mean(PSD

signal band−band o f interest

)

(1)

The signal power is deﬁned as the mean power

spectral density (PSD) in the band of interest, while

the noise power is the mean PSD outside this band.

For the closed eyes recordings, the band of interest

corresponds to the alpha band (8-13Hz) while for

the SSVEP recordings, it is between the following

intervals: 3-5, 7-9, 11-13, 15-17 corresponding to the

stimulation frequency and its harmonics. The PSD

of all recordings is computed with Welch’s spectrum

estimation method on a 1 second window with 75%

window overlap.

2.3.4 Impedance Value Analysis

For the analysis of the impedance data, the magnitude

is extracted from the in-phase and quadrature

components of the impedance signal by taking into

account the amplitude of the injected current. Mean

values and standard deviations are reported for all dry

and gel electrodes.

3 RESULTS

3.1 Signal Correlations

Mean correlation values across participants are

presented in Table 1, classiﬁed according to the

electrode types tested and the paradigms used for

recording. In the case of the Ag/AgCl test electrodes,

one participant was excluded due to improper contact

of the gel electrodes. For the polymer electrodes,

recordings on the Cz site of one participant, for

the walking paradigms, were excluded also due

to improper gel electrode contact. Additionally,

measurements with polymer electrodes could not be

performed on two of the subjects as the skin-electrode

contact impedance was higher than the limit imposed

by the ampliﬁer. An example of the signals obtained

with different electrodes in seated and walking

conditions can be seen in Fig. 2a-d.

Gel-gel signal comparisons resulted in high values

for the correlation coefﬁcients in the case of the seated

paradigms, indicating a strong similarity between the

recordings. These values are useful in estimating

the effect of spatial variability on the content of

the signal. Stronger correlations are reported when

the participants had their eyes closed, due to the

increased alpha activity. For the walking paradigms,

the coefﬁcients decreased due to the motion artifacts

introduced and ranged between 0.65 to 0.83. Also,

differences in correlation for eyes closed and eyes

open conditions was not consistent.

Coefﬁcients obtained for the dry-gel comparison

varied substantially with electrode type and paradigm.

Generally, they followed a decreasing trend, from

Cz to Pz electrodes and from closed eyes to open

eyes paradigms, in both the seated and walking cases.

This is consistent with literature (Estepp et al., 2009).

The computed values for the Ag/AgCl electrodes

were higher than those obtained in our previous

seated study. This is caused mainly by the use of

active electrodes designed to cope with higher input

impedance. The walking paradigms induced a more

drastic decrease in the dry-gel correlation values than

in the gel-gel ones, revealing a greater sensitivity of

dry electrodes to motion artifacts.

The polymer electrodes had a poorer performance

than the silver ones: in two cases signal acquisition

was not possible while the correlation coefﬁcients

obtained were lower for the seated paradigms. For the

walking paradigms, the coefﬁcients were in the same

BIODEVICES2014-InternationalConferenceonBiomedicalElectronicsandDevices

Table 2: Mean coherence values in the frequency band 2-30Hz across participants.

Cz Pz

Paradigm 1-5 1-6 5-6 2-7 2-8 7-8

Open eyes seated 0.54 0.51 0.84 0.50 0.49 0.77

Electrode A Closed eyes seated 0.59 0.55 0.86 0.54 0.54 0.77

Ag/AgCl Open eyes walking 0.12 0.11 0.70 0.16 0.15 0.64

Closed eyes walking 0.20 0.19 0.77 0.26 0.23 0.62

Open eyes seated 0.27 0.24 0.83 0.24 0.23 0.79

Electrode B Closed eyes seated 0.34 0.34 0.87 0.32 0.29 0.81

Polymer Open eyes walking 0.18 0.14 0.70 0.17 0.10 0.50

Closed eyes walking 0.24 0.18 0.71 0.23 0.11 0.46

Table 3: Mean SNR values in dB.

Cz Pz

Paradigm 1 5 6 2 7 8

Electrode A Closed eyes seated 7.80 7.98 7.58 8.72 9.87 10.14

Ag/AgCl Closed eyes walking 2.12 3.72 3.12 1.80 3.73 4.57

Electrode B Closed eyes seated 4.30 6.31 6.17 5.24 8.90 8.42

Polymer Closed eyes walking 1.90 2.15 1.55 1.91 2.24 4.52

range as for the Ag/AgCl electrodes. However, a

comparison of the behavior of the two electrodes with

respect to gel ones in motion recordings is difﬁcult to

make since gel-gel correlations have also changed.

3.2 Signal Coherence

Table 2 reports the mean coherence values obtained

from the same recordings as those used for

determining signal correlations. Coherence values

are slightly lower than the correlation values. This

indicates power asymmetries between recordings

that could be caused by the different skin-electrode

contact impedance and its variation over time. It is

expected that the dry electrode impedance slightly

decreases over time as the contact with the skin

stabilizes and the signal settles, while the gel

electrode impedance increases over time due to the

drying of the gel.

Nevertheless, the results obtained follow the

same trends as those of the correlation computations.

Gel-gel comparisons present the highest values across

all paradigms. Dry-gel results are substantially lower

than the gel-gel ones and values decrease drastically

in the case of the walking paradigms. The artifacts

introduced through walking are superimposed

on the EEG signal, introducing new frequency

components in the recordings. Each electrode records

the additional interference differently due to the

differences in skin contacts as a result of motion.

The results conﬁrm that gel electrodes are still

better when dealing with motion. Without the gel

to ensure adhesion, dry electrode recordings are

more susceptible to walking artifacts. Here as well,

Electrode A presents higher values than Electrode B.

3.3 SNR

Signal to noise ratios were computed on the closed

eyes and SSVEP paradigms while walking and seated.

The values obtained are summarized in Table 3 and

examples of spectra for the closed eyes paradigms are

shown in Fig. 2e-f. For the closed eyes paradigms, the

same recordings were excluded from the analysis as in

the case of correlation and coherence computations.

For the SSVEP, one subject was eliminated due to

improper gel contacts for the silver electrode and

for the polymer electrode, the same two subjects as

in the case of continuous recordings presented no

measurable signal.

The SNR values for the SSVEP paradigm were

not reported in Table 3 as they did not reﬂect the

observations made through the visual inspection of

the signals’ spectra. The visual stimulation frequency

was too low and thus the ﬁrst harmonic of the

SSVEP response was superimposed on the strong low

frequency components present in the dry electrode

recordings. As the electrodes are distant from the

visual cortex, higher harmonics could be observed on

some of the recordings, however their intensity was

too low. Thus, no accurate distinction could be made

between the peaks of the speciﬁc cortical response

and the background EEG and noise.

As can be seen in Table 3, the SNRs of the closed

SignalQualityinDryElectrodeEEGandtheRelationtoSkin-electrodeContactImpedanceMagnitude

(a) (b) (c) (d)

(e) (f) (g) (h)

Figure 2: Closed eyes seated and walking recordings of Subject 1 for electrode 1 and 2 at the Cz position. First row presents

approximately 2 seconds of the time course of the EEGs while the second row shows the spectrum of the entire recordings.

For the legend, see Fig. 1 for the electrode position numbering.

eyes recordings were positive for all electrodes as

the alpha wave phenomena could be observed on the

spectra of both seated and walking recordings (see

Fig. 2e-f). Generally, the values obtained from the

parietal site are higher than those from the central

position. For the closed eyes seated paradigms,

the results for the gel electrodes are comparable

to those obtained in our previous study. The

Ag/AgCl electrodes exhibited higher SNRs mostly

due to the active electrodes used for acquisition.

Their performance is now comparable to that of gel

electrodes. The polymer electrodes presented higher

differences between the SNRs of dry electrodes and

of gel electrodes indicating a higher level of noise.

For the walking recordings, as expected, the

SNR values decrease. However, the alpha peak

can still be seen (Fig. 2f and Fig 2h). For

Electrode A, the walking spectra indicates strong low

frequency components introduced by the motions.

These components are not present on the spectra

of the corresponding gel recordings (Fig. 2f) or

on the spectra of the seated paradigm (Fig. 2e).

These observations are conﬁrmed by the SNR values

reported, where a stronger difference exists between

the dry and gel SNRs for the walking paradigms than

for the seated ones. For Electrode B, the values

obtained are lower than those found for Electrode

A. A higher sensitivity to motion artifacts causes

stronger low frequency components that interfere

with the alpha response as their band extends over

10Hz (Fig. 2h).

Figure 3: Comparison of the Correlations and SNRs of dry

electrodes per subject for the closed eyes seated recording.

Fig. 3 shows a plot of the correlation values

obtained for all dry electrodes per subject versus

their corresponding SNR. Correlation coefﬁcients

were computed to characterize the relationship

between the two variables. The r value for each

electrode is mentioned in the legend of Fig. 3. A

strong correlation exists between the two deﬁned

parameters. Thus, the quality deﬁned in the time

domain by the correlation coefﬁcients is comparable

to the one deﬁned in the frequency domain by the

SNR.

3.4 Impedance and Signal Quality

Table 4 summarizes the results obtained for the

BIODEVICES2014-InternationalConferenceonBiomedicalElectronicsandDevices

Table 4: Mean (M) and standard deviation (S) skin-electrode contact impedance values in kΩ.

Cz Pz

Paradigm 1 5 2 7

M S M S M S M S

Electrode 1 Open eyes seated 54.2 61.6 13.6 12.7 34.4 18.7 15.2 16.7

Ag/AgCl Closed eyes seated 47.8 52.9 14.6 13.0 37.6 11.2 21.3 26.2

SSVEP seated 56.4 48.1 26.7 31.4 40.3 16.1 26.9 35.5

Electrode 2 Closed eyes seated 212.4 147.1 29.5 21.9 530.0 43.8 23.9 19.5

Polymer Closed eyes seated 183.5 146.8 33.3 25.1 453.9 339.8 27.0 21.3

SSVEP seated 184.7 127.7 36.6 25.7 396.8 268.7 34.5 30.5

(a) (b) (c)

(d) (e) (f)

Figure 4: Comparison of parameters deﬁning signal quality to skin-electrode contact impedance.

continuous impedance analysis. For each

measurement electrode, the average of the impedance

signal mean values across all included participants

and their corresponding standard deviation are

presented. The analysis was performed only on the

seated paradigms as the walking paradigms introduce

artifacts on the impedance signals which inﬂuence

the mean impedance value in an unpredictable

way. Results found for both dry electrode types

were greater than those of the gel electrodes. Gel

electrodes presented a minimum mean impedance

value of 13.6 kΩ and a maximum of 36.6 kΩ

both found for electrode 5 in the Cz position. The

Ag/AgCl electrodes had values ranging from 34.4 kΩ

in the Pz position to 56.4 kΩ in the Cz position, while

the polymer electrode impedance was larger, having a

minimum of 183.5kΩ at Cz and a maximum of 530.0

kΩ at Pz. The large discrepancies between the values

of the skin-electrode impedance of the same electrode

type at different locations might be connected to the

different contacts between the sensor and the scalp of

the participant. High standard deviations are reported

for all electrodes. This can be motivated by the

different skin properties of each participant and by

the differences in measurement conditions. However,

larger variations can be observed in the dry electrode

impedance values than in the gel ones.

A comparison between the parameters deﬁned

for quantifying signal quality and the corresponding

skin-electrode contact impedance obtained is made in

Fig. 4. Correlations and SNR values of the ”test”

electrodes are plotted with respect to their impedance

values for each subject. No relation can be observed

between the impedance and the corresponding dry-gel

SignalQualityinDryElectrodeEEGandtheRelationtoSkin-electrodeContactImpedanceMagnitude

correlations for Electrode A (Fig. 4a). Electrode

B presents a decrease in quality and an increase

in impedance compared to Electrode B. Although

its impedance values vary a lot, the signal quality

obtained seems unaffected. This also suggest no

connection between the two variables. Note that the

acquired EEG signals for which the skin-electrode

contact impedance was higher than 500kΩ were

attenuated due to the ampliﬁer saturation and so they

are not included in this analysis (see Figure 4b and

Fig. 4e).

The same trend is observed for the SNR

investigation. Measurements for Subject 4 were not

taken with Electrode B due to a very large impedance

value. Also, outliers in the SNR and correlation

plots of this electrode type represent measurements

that were excluded from previous analysis as no EEG

signal was observed during visual inspection of the

recordings. The results obtained indicate that a large

increase in the skin-electrode contact impedance has

no effect on the signal quality deﬁned through our

parameters. However, a larger data set should be used

to conﬁrm these results as the number of available

data points was limited to 12 per electrode type.

Gel electrode performance was also evaluated

with respect to the corresponding skin-electrode

contact impedance. Impedance values presented a

large variation and included values above 40 kΩ.

Both in the case of correlations and SNR, gel

electrodes presented high scores regardless of their

impedance value (Figure 4(c) and 4(f)). A lower

performance was seen in several gel electrodes, but

their impedance value was inside the mean range.

These results conﬁrm the ﬁndings of Ferree et. al

(Ferree et al., 2001) and point out that signal quality

is not depended on the impedance magnitude, even

when these values are much higher than 40kΩ.

However, they also show that electrode material has

an impact on both impedance magnitude and obtained

EEG signal quality.

4 DISCUSSION

The dry-gel comparison made by using a gel-gel

comparison as a benchmark, proved to be a

reliable framework for dry electrode EEG signal

quality evaluation. Differences between subjects

and electrode types could easily be observed and

compared, providing useful information on the

introduced variability.

All three parameters proposed for evaluation,

namely signal correlations, signal coherence and

SNR, presented lower values for dry electrodes when

compared to gel electrodes. The results suggest

that better EEG signal quality is obtained through

gel electrodes, followed by the Ag/AgCl electrodes

and then by the polymer electrodes. Compared to

our previous study, the performance of the Ag/AgCl

electrodes was better as a consequence of the use of

active electrodes designed to cope with dry electrode

recording conditions. The mean coherence values

reported were lower than the correlation coefﬁcients

obtained, but followed the same decreasing trends.

For the electrodes that presented strong dry-gel

correlations, high SNR values were also reported.

Since the mean coherence, correlation coefﬁcients

and SNRs present the same trends and thus equivalent

conclusions regarding signal quality, one of them can

be considered sufﬁcient for a fast characterization of

EEG recordings.

The mean values for the skin-electrode contact

impedance magnitude of the gel electrodes was the

lowest reported, while the highest was that of the

polymer electrodes. When comparing the deﬁned

signal quality to the values of the impedance, no

trend was observed for different recordings with

the same electrode although impedance variations

were present. Skin-electrode contact impedance

magnitude values that exceeded the recommended

5kΩ threshold were reported for the gel electrodes.

However, there was no indication of a decrease in

performance, either from the visual inspection of

the recordings or from the values obtained for our

parameters. The lack of a relationship between EEG

signal quality and skin-electrode contact impedance

magnitude can be a consequence of the system

features: active electrodes combined with high input

impedance ASICs that were developed speciﬁcally

to eliminate the inﬂuence of high impedance values.

Thus, the recordings are expected to be less dependent

on the contact impedance. Nevertheless, differences

in recording quality can still be observed between

different electrode types.

The evaluation performed on the dry electrodes

revealed several disadvantages of this technology.

During the walking paradigms, a higher susceptibility

to motion artifacts was observed in the dry electrode

types. Less adhesion to the skin is one of the

factors that contributes the most to this effect. Also,

the spectra of dry electrode recordings presented

strong low frequency components that extended over

the 4Hz SSVEP stimulation frequency even in the

case of the seated paradigm. These low frequency

components are attributed to signal drifts due to the

changes in the skin-electrode contact over time. To

cope with these disadvantages, a solution for handling

motion needs to be found, either through system

BIODEVICES2014-InternationalConferenceonBiomedicalElectronicsandDevices

or algorithm design or by creating electrodes with

different contact properties. Furthermore, to give

a better characterization of the sensors, studies on

contact impedance variations over time should be

carried out. Electrodes that have shorter settling time

and that do not suffer from signal drifts are needed to

permit a faster, more reliable signal acquisition while

eliminating the undesired frequency components.

Due to the limitations of the proposed framework

and study design, conclusions regarding the relation

between signal quality and skin-electrode contact

properties are difﬁcult to formulate. Future studies

should include a larger number of participants, both

male and female, for a more thorough, unbiased

analysis. During some of the experimental sessions,

gel electrodes were disconnected or made a poor

contact with the scalp of the participant. Also, due

to the constraints imposed by the rigid headset used

for dry electrode positioning, proper contact for dry

electrodes was not always obtained. Variability in the

size and head shape of the participants combined with

the different hair types, made the contact between

the skin and the electrode pins difﬁcult. Results also

indicate that the reported outliers in signal quality

might be related to a bad contact of the electrodes

to the skin and not to the high skin-electrode contact

impedance magnitude.

Improvements to the proposed evaluation

framework should include a change in the stimulation

frequency of the SSVEP protocol. To avoid

interference from the strong low frequency

components, the alpha band frequency range

and the frequencies introduced by the walking

paradigms, a ﬂickering frequency higher than 13Hz is

recommended. Also, placing the recording electrodes

above the occipital lobe would permit the capture of

a stronger SSVEP response as this site is closer to the

visual cortex. A protocol for eliciting event-related

potentials (ERPs) should also be included in the

evaluation as ERPs are often used in BCIs and

psychological studies. Moreover, the ERPs have a

very low amplitudes and thus are very sensitive to

different sources of interference.

Overall, better EEG systems and electrode

designs are needed to permit the usage of dry

electrode technology in a wide range of applications

requiring high quality signals. The skin-electrode

contact impedance broadly characterizes the interface

between the electrode and the skin. To allow the

design of better performing electrodes, more work

needs to be carried out in identifying the exact contact

characteristics that have the largest impact on signal

quality. Some of the approaches that could assist

in this process involve studying the skin-electrode

interface by analyzing the real and imaginary parts of

the impedance signal or by creating models of this

interface.

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