Rare Diseases Symptoms Automatic Extraction
Home
A random Abstract
Our Project
Our Team
Evaluating true BCI communication rate through mutual information and language models.
[locked-in syndrome]
Brain
-computer
interface
(
BCI
)
systems
are
a
promising
means
for
restoring
communication
to
patients
suffering
from
"
locked-
in
"
syndrome
.
Research
to
improve
system
performance
primarily
focuses
on
means
to
overcome
the
low
signal
to
noise
ratio
of
electroencephalogric
(
EEG
)
recordings
.
However
,
the
literature
and
methods
are
difficult
to
compare
due
to
the
array
of
evaluation
metrics
and
assumptions
underlying
them
,
including
that
:
1
)
all
characters
are
equally
probable
,
2
)
character
selection
is
memoryless
,
and
3
)
errors
occur
completely
at
random
.
The
standardization
of
evaluation
metrics
that
more
accurately
reflect
the
amount
of
information
contained
in
BCI
language
output
is
critical
to
make
progress
.
We
present
a
mutual
information-based
metric
that
incorporates
prior
information
and
a
model
of
systematic
errors
.
The
parameters
of
a
system
used
in
one
study
were
re
-optimized
,
showing
that
the
metric
used
in
optimization
significantly
affects
the
parameter
values
chosen
and
the
resulting
system
performance
.
The
results
of
11
BCI
communication
studies
were
then
evaluated
using
different
metrics
,
including
those
previously
used
in
BCI
literature
and
the
newly
advocated
metric
.
Six
studies
'
results
varied
based
on
the
metric
used
for
evaluation
and
the
proposed
metric
produced
results
that
differed
from
those
originally
published
in
two
of
the
studies
.
Standardizing
metrics
to
accurately
reflect
the
rate
of
information
transmission
is
critical
to
properly
evaluate
and
compare
BCI
communication
systems
and
advance
the
field
in
an
unbiased
manner
.
