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Electroencephalographic profiles for differentiation of disorders of consciousness.
[locked-in syndrome]
Electroencephalography
(
EEG
)
is
best
suited
for
long
-term
monitoring
of
brain
functions
in
patients
with
disorders
of
consciousness
(
DOC
)
.
Mathematical
tools
are
needed
to
facilitate
efficient
interpretation
of
long
-duration
sleep
-wake
EEG
recordings
.
Starting
with
matching
pursuit
(
MP
)
decomposition
,
we
automatically
detect
and
parametrize
sleep
spindles
,
slow
wave
activity
,
K-
complexes
and
alpha
,
beta
and
theta
waves
present
in
EEG
recordings
,
and
automatically
construct
profiles
of
their
time
evolution
,
relevant
to
the
assessment
of
residual
brain
function
in
patients
with
DOC
.
A
bove
proposed
EEG
profiles
were
computed
for
32
patients
diagnosed
as
minimally
conscious
state
(
MCS
,
20
patients
)
,
vegetative
state
/
unresponsive
wakefulness
syndrome
(
VS
/
UWS
,
11
patients
)
and
Locked-
in
Syndrome
(
LiS
,
1
patient
)
.
Their
interpretation
revealed
significant
correlations
between
patients
'
behavioral
diagnosis
and
:
(
a
)
occurrence
of
sleep
EEG
patterns
including
sleep
spindles
,
slow
wave
activity
and
light
/
deep
sleep
cycles
,
(
b
)
appearance
and
variability
across
time
of
alpha
,
beta
,
and
theta
rhythms
.
Discrimination
between
MCS
and
VS
/
UWS
based
upon
prominent
features
of
these
profiles
classified
correctly
87
%
of
cases
.
Proposed
EEG
profiles
offer
user-independent
,
repeatable
,
comprehensive
and
continuous
representation
of
relevant
EEG
characteristics
,
intended
as
an
aid
in
differentiation
between
VS
/
UWS
and
MCS
states
and
diagnostic
prognosis
.
To
enable
further
development
of
this
methodology
into
clinically
usable
tests
,
we
share
user-friendly
software
for
MP
decomposition
of
EEG
(
http
:
/
/
braintech
.
pl
/
svarog
)
and
scripts
used
for
creation
of
the
presented
profiles
(
attached
to
this
article
)
.
Diseases
Validation
Diseases presenting
"clinically usable tests"
symptom
locked-in syndrome
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