The
aim
of
the
study
was
to
validate
a
methodology
for
professional
pilots'
neurophysiological
assessment
improve
training
program
tailoring
and
management.
In
particular,
focused
on
quantifying
(i)
mental
workload,
(ii)
stress
level
(iii)
cooperation
degree
between
two
members
crews.
Two
groups
pilots
were
involved
in
experiments:
Experienced
Unexperienced.
Additionally,
Instructor
responsible
provide
subjective
evaluation
about
states
cooperation.
During
entire
flight
simulations,
brain
activity
acquired
through
Electroencephalography
(EEG).
results
demonstrated
that
it
is
possible
quantify
operators'
while
dealing
with
simulations
under
realistic
settings.
Pilots'
workload
behavioral
levels
resulted
be
positively
significantly
correlated
corresponding
measurements
(all
R
>
0.6,
all
p
<
0.05),
observed
higher
(p
0.05)
than
Although
are
preliminary,
they
show
how
capability
tasks
will
instructors
additional
objective
information.
this
information
would
allow
sessions
based
crew's
behavior.
Journal of Neural Engineering,
Journal Year:
2024,
Volume and Issue:
21(5), P. 056023 - 056023
Published: Sept. 19, 2024
In
the
context
of
electroencephalographic
(EEG)
signal
processing,
artifacts
generated
by
ocular
movements,
such
as
blinks,
are
significant
confounding
factors.
These
overwhelm
informative
EEG
features
and
may
occur
too
frequently
to
simply
remove
affected
epochs
without
losing
valuable
data.
Correcting
these
remains
a
challenge,
particularly
in
out-of-lab
online
applications
using
wearable
systems
(i.e.
with
low
number
channels,
any
additional
channels
track
EOG).
Behaviour and Information Technology,
Journal Year:
2022,
Volume and Issue:
42(10), P. 1617 - 1639
Published: June 26, 2022
Real-time
travel
information
design
with
inadequate
consideration
of
human
factors
can
lead
to
driver
distraction
and
diminish
road
safety.
This
study
measures
drivers'
brain
electrical
activity
patterns
evaluate
multiple
aspects
cognition
psychology
under
real-time
provision
using
insights
from
the
neuroscience
domain
on
localisation
functions.
The
84
participants
are
collected
an
electroencephalogram
(EEG)
in
interactive
driving
simulator
environment.
impacts
auditory
characteristics
(amount,
sufficiency,
content)
different
time
stages
interaction
(before,
during,
after)
frequency
band
powers
EEG
signals
regions
analyzed
linear
mixed
models.
Study
results
illustrate
that
drivers
exert
more
cognitive
effort
perceive/process
routes
complex
environments.
Insufficient
may
evoke
increased
attention
internal
processing
memory
characterised
by
higher
uncertainty,
while
route
recommendation
switch
such
increase
stress
anxiety.
findings
aid
providers,
both
private
public,
as
well
auto
manufacturers
incorporate
designing
safer
their
delivery
systems.
Applied Sciences,
Journal Year:
2023,
Volume and Issue:
13(23), P. 12800 - 12800
Published: Nov. 29, 2023
In
the
field
of
passive
Brain–computer
Interfaces
(BCI),
need
to
develop
systems
that
require
rapid
setup,
suitable
for
use
outside
laboratories
is
a
fundamental
challenge,
especially
now,
market
flooded
with
novel
EEG
headsets
good
quality.
However,
lack
control
in
operational
conditions
can
compromise
performance
machine
learning
model
behind
BCI
system.
First,
this
study
focuses
on
evaluating
loss
system,
induced
by
different
positioning
headset
(and
course
sensors),
so
generating
variation
features
used
calibrate
algorithm.
This
phenomenon
called
covariate
shift.
Detecting
shift
occurrences
advance
allows
preventive
measures,
such
as
informing
user
adjust
position
or
applying
specific
corrections
new
coming
data.
We
an
unsupervised
Machine
Learning
model,
Isolation
Forest,
detect
occurrence
tested
method
two
datasets,
one
controlled
setting
(9
participants),
and
other
more
realistic
(10
participants).
dataset,
we
simulated
movement
cap
using
channel
reference
configurations.
For
each
test
configuration,
selected
set
electrodes
near
electrodes.
Regarding
aimed
simulate
laboratory,
mimicking
removal
repositioning
non-expert
user.
both
recorded
multiple
sessions
configuration
while
executing
Workload
tasks.
The
results
obtained
Forest
allowed
identification
data,
even
15-s
recording
sample.
Moreover,
showed
strong
significant
negative
correlation
between
percentage
detected
method,
accuracy
system
(p-value
<
0.01).
approach
opens
perspectives
developing
robust
flexible
systems,
potential
move
these
technologies
towards
out-of-the-lab
use,
without
supervision
The
aim
of
the
study
was
to
validate
a
methodology
for
professional
pilots'
neurophysiological
assessment
improve
training
program
tailoring
and
management.
In
particular,
focused
on
quantifying
(i)
mental
workload,
(ii)
stress
level
(iii)
cooperation
degree
between
two
members
crews.
Two
groups
pilots
were
involved
in
experiments:
Experienced
Unexperienced.
Additionally,
Instructor
responsible
provide
subjective
evaluation
about
states
cooperation.
During
entire
flight
simulations,
brain
activity
acquired
through
Electroencephalography
(EEG).
results
demonstrated
that
it
is
possible
quantify
operators'
while
dealing
with
simulations
under
realistic
settings.
Pilots'
workload
behavioral
levels
resulted
be
positively
significantly
correlated
corresponding
measurements
(all
R
>
0.6,
all
p
<
0.05),
observed
higher
(p
0.05)
than
Although
are
preliminary,
they
show
how
capability
tasks
will
instructors
additional
objective
information.
this
information
would
allow
sessions
based
crew's
behavior.
