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Chapter 29
Mobile Electroencephalography
Olave E. Krigolson, Mathew Rocha Hammerstrom, and Katherine Boere
Abstract Electroencephalography (EEG) research has traditionally been associated
a participant being seated at a table, with many electrodes affixed to a “swim-
with
ming cap”, which in turn is connected to an amplifier connected to one or more
computers. While this type of experimental setup affords the ability to ask an array of
research questions, it also greatly restricts ecological validity among other factors.
The advent of mobile EEG—EEG systems that are lightweight, easy to put on, and
wireless—allows a researcher to take EEG research out of the laboratory and into the
“real world”. In this chapter, we define what mobile EEG is and provide a brief
historical context of the development of mobile EEG. We then look at the range of
mobile EEG systems available to researchers, the technical considerations that need
to be considered when using these systems, and provide thoughts on the validation of
said systems. Finally, we end with an application section in which we describe a
range of mobile EEG “use cases” to give the reader examples of how mobile EEG
can be used.
Keywords EEG · ERP · Mobile
technology · Ecological validity · Neuroscience ·
Cognitive neuroscience
29.1 What Is Mobile EEG?
Traditionally, the coll ection of electroencephalographi c (EEG) data has been associated with desk-mounted, wired, large array systems (32+ channels) that are
inherently “not mobile” (Fig. 29.1). While this sort of experimental setup was
O. E. Krigolson (*)
Theoretical and Applied Neuroscience Laboratory, School of Exercise Science, University of
Victoria, Victoria, BC, Canada
e-mail: krigolson@uvic.ca
M. R. Hammerstrom · K. Boere
Department
Victoria, BC, Canada
e-mail:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026
T.
Warbrick (ed.), The EEG Handbook,
https://doi.org/10.1007/978-3-032-20450-9_29
of Exercise Science, Physical and Health Education, The University of Victoria,
mathewhammerstrom@uvic.ca; katherineboere@uvic.ca
403
404 O. E. Krigolson et al.
Fig. 29.1 A “traditional”
EEG
system, the Brain
Products actiChamp (Brain
Products GmbH, Gilching,
Germany)
deemed necessary to collect EEG data, there are obvious problems that stem from the
methodology in this format. First, the technical requirements of lab-based EEG
systems restrict ecological validity—only a small portion of the daily tasks that we
engage in take place sitting in front of a computer in isolation. And we would
assume, even fewer wearing a swimming-style cap with many electrodes streaming
ir t
from said cap connected to an amplifier and a computer. As such, it is fa
whether
the
cognitive,
motor,
and perceptual phenomena that are studied in this
o question
manner with EEG parallel the neural processes that subserve us in the real world.
Second, another obvious and related problem that stems from the use of traditional
EEG systems is that the equipment itself restricts the brain processes that can be
studied. For example, we know that being outside impacts neural processing (e.g.,
Boere et al.,
ter.
compu
2023a, b), y
In a similar manner, what about movement? A vast portion of the human
it is very hard to be in nature when one is wired to a
et,
brain is dedicated to moving our bodies from one location to another, yet traditional
EEG data collection by its very nature makes movement problematic. With these two
issues in mind—ecological validity and the restrictions in what can be studied due to
the nature of the methodology - over the past 15 years or so researchers have begun
to look
for “mobile EEG” solutions (Fig.
29.2).
First, it is probably important to define what is meant by mobile EEG (mEEG).
One has to consider whether the cap is wired to an amplifier, whether the movement
of the participant is restricted by proximity to the amplifier, and other factors such as
these. Indeed, the concept of mEEG is a true spectrum that on one end has a
traditional EEG amplifier with wired electrodes and a cap carried with or by the
participant and on the other end a Bluetooth headband-style system running off of a
mobile device such as a phone or a tablet. Here, we will attempt to be inclusive of all
29 Mobile Electroencephalography 405
Fig. 29.2 A “mobile” EEG
system,
the Brain Products
X.on (Brain Products
GmbH, Gilching, Germany)
mEEG solutions. What truly matters, in a sense, is that it is feasible given the
research question and capacity to conduct mEEG research.
It is hard to pinpoint the exact start of “mobile EEG” (mEEG) research. In 1993,
Sirevaag and colleagues collected EEG data while pilots were flying rotary-wing
aircraft. Going back further, one would even have to consider the seminal work done
by Berger in 1924 to be, in a sense, “mobile”—at least in the sense that his system
could be moved between rooms (MRI scanner, for example, cannot do this). With
that said, credit must be given to the work by Debener et al. (
2012)
1
, who had
participants perform an auditory oddball task while seated indoors but importantly
also while walking outside. mEEG data was collected from a modified Emotiv EEG
headset, a standard EEG cap connected to a laptop running OpenVibe software that
was carried within a backpack, which in the walking outside condition made this
study truly mobile. The data from this study clearly demonstrated evoked auditory
components of the human event-related brain potential (ERPs) thus highlighting that
it was possible to make these kinds of measurements outside of the laboratory. In a
similar manner, Scalon and colleagues in a series of studies (e.g.,
that auditory ERPs could be collected using a similar setup while participants
strated
1
It is important to note that other researchers and several commercial companies had collected EEG
data prior to the Debener study. For example, Emotiv Inc. launched the EPOC EEG headset
commercially and Lin et al. (
technology.
EEG
2009) were arguably the first researchers to demonstrate mobile
2017) demon-
406 O. E. Krigolson et al.
Fig. 29.3 EEG being
recorded
while riding a bike
were riding a bicycle (Fig. 29.3). In their work, EEG data was collected from a cap
with electrodes using a Brain Products V-Amp system (Brain Products GmbH,
Gilching, Germany) connected to a Windows laptop carried in a backpack. Similar
to the work done by Debener and colleagues while walking, Scalon et al. were able
to capture auditory ERP components while participants were riding a bicycle. In
other work using the Muse Mobile EEG headband, Kovacevic et al. (20 15
neurof
eedback data from 523 participants in a single night, and Hashemi et al.
(
2016) presented an EEG study with 6029 participants performing a meditation
se, research that demonstrates the ability of mEEG to capture larger data sets
exerci
) collected
than possible in a traditional laboratory environment.
Perhaps the most important question that has to be asked with regard to mEEG is
why use it? While we have hinted at the reasons above, we will now clearly state
them. First and foremost is of course the opportunity to get outside of the laboratory
and study cognitive phenomena in the real world. Indeed, the Scanlon et al. (
2017)
study highlights this as we think it is quite obvious that riding a bicycle outside is
considerably different from riding a stationary bike inside from a perceptual-motor
perspective. As such, perhaps the strongest reason to use mEEG in research is to
increase ecological validity, a construct that is paid homage to in Research Methods
classes across the globe, but is rarely addressed adequately in EEG studies in
Psychology and Neuroscience. The second key advantage to mEEG is ease of
use/setup time. In work done by our research group using the Muse mEEG system,
we had an average setup time of under 60 s (Krigolson et al.,
2021).
Of course, the
29 Mobile Electroencephalography 407
setup time for mEEG systems is wholly dependent on the mEEG system in question,
which is noted below when various systems are reviewed. But overall, there is little
to no doubt that ease of use/setup time is a massive advantage when using mEEG
relative to a traditional computer-based cap—amplifier EEG system. Finally, mEEG
is low cost by its very nature, especially when one considers the available commercial devices. Lowering the cost of EEG data capture leads to a natural i
ncrease in
sample size which is of growing importance in a research field that has been
criticized for underpowered research leading to non-replicable findings (Ioannidis,
2005).
29.2 Range of mEEG Systems
It is impossible to list here all of the mEEG systems that are currently available,
especially within the commercial space. In an attempt to classify current systems, we
will broadly group them into what we will call commercial and research systems.
Before this however, it is worth noting four key features that differ between systems.
One, the number and placement of electrodes—for mobile systems this spans from a
single recording electrode to 32+ recording electrodes. Two, the data quality of the
individual systems. Three, the manner in which data is transmitted (Bluetooth,
Wireless, Wired). Four, ease of setup of the system. When considering the use of a
mEEG system, it is important to examine each of these four features.
Commercial Systems Without question, the Muse EEG headband is the most
popular and the most distributed mEEG system in the world with over 500,000
units currently in the market. The Muse system has four electrodes located at AF7,
AF8, TP9, TP10, and also comes with an accelerometer, gyroscope, and a pulse
oximeter (www.choosemuse.com; Fig. 29.4).
Further, the latest version of Muse, Athena, also comes with functional nearinfrared spectroscopy sensors. Importantly, work by our research group and others
has demonstrated that the EEG data quality of the Muse is sufficient for conducting
peer-reviewed research studies (Fickling et al.,
2020; Krigolson et al., 2017, 2021 :
see below for more detail). It is important to note that there are numerous other
mEEG systems capable of collecting research-grade data—for instance, other
research groups have demonstrated similar findings with systems such as the
OpenBCI Cyton (Qiu et al.,
Fig. 29.4 The Muse S
Athena. A combined EEG
and fNIRS system
2019), the Neurosky Mindflex (Katona et al., 2014),
408 O. E. Krigolson et al.
and the Emotiv Epoc+ (Kotowski et al., 2018; Mercado-Aguirre et al., 2019). A full
review of all of the commercially available mEEG systems is beyond this chapter,
but others such as Bateson et al. (
do so in review papers. With that said, it is worth noting that new commercial
to
mEEG systems are released on a regular basis making it almost impossible to stay
current with the latest technology.
Research Systems As with commercial mEEG systems, there are non-commercial
“research” mEEG systems available for research as well. Again, there are too many
systems to list here so we will endeavor to highlight some prominent systems to
highlight key differences in mEEG technology. Some research-grade mEEG systems
provide full head coverage and a large number of electrodes (20+). For instanc e, the
CGX Quick 20 and Quick 32 have 20 or 32 electrodes respectively and transmit data
via Bluetooth to a recording computer or tablet. Other research-grade mEEG systems
that try to achieve full head coverage rely on traditional EEG caps connected to an
amplifier, but the amplifier is not directly wired to a computer (e.g., the Brain
Products LiveAmp). Other research-grade mEEG systems use a reduced electrode
array but still provide high-quality EEG data from the available electrodes. An
excellent example of this is the CGX Patch system that only has two electrodes
and is worn on the forehead only (see Boere et al.,
Brain Products X.on (Brain Products GmbH, Gilching, Germany) has provided
the
researchers with a research-grade mEEG system with seven electrodes that provides
semi-full head coverage. While the X.on has yet to be fully validated—specifically
there are no published papers with the device—the evidence that is available
suggests that the X.on is an excellent compr omise between data quality, head
coverage, and mobility (see
results)
. Other companies in the mEEG research space with excellent headsets
include the APEX system by TMSI, the Bittium BrainStatus system, the Smarting
systems by mBraintrain, the Enobio system by Neuroelectrics, and a series of
systems with varying configurations by Bitbrain, among others.
2017) and Sawangjai et al. (2020) have attempted
2023a, b). Recently, the release of
https://www.peereeg.com/results.html for preliminary
29.3 Technical Considerations
When considering the use of a mEEG for research, there are several factors that
differentiate these systems from more traditional lab-based EEG systems that need to
be considered and evaluated.
Wired Versu
electrodes will be wired to the amplifier or not. The advantage of a wired system is
that data quality is typically better with a wired system, and one does not have to
worry about data loss due to Bluetooth/wireless dropout. However, the obvious
constraint is that the participant is wired to the amplifier. Some researchers have
created a compromise wherein the participant carries the amplifier with them in a
pack or in some form of mounting device. Again, the restraint here is obvious—the
s Wireless First and foremost, one must consider whether the EEG