Sensors,
Journal Year:
2025,
Volume and Issue:
25(7), P. 1994 - 1994
Published: March 22, 2025
Stroke
is
the
fifth
leading
cause
of
death
in
Taiwan.
In
process
stroke
treatment,
rehabilitation
for
gait
recovery
one
most
critical
aspects
treatment.
The
Gait
Assessment
and
Intervention
Tool
(G.A.I.T.)
currently
used
clinical
practice
to
assess
level;
however,
G.A.I.T.
heavily
depends
on
physician
training
judgment.
With
advancement
technology,
today's
small,
lightweight
inertial
measurement
unit
(IMU)
wearable
sensors
are
rapidly
revolutionizing
assessment
may
be
incorporated
into
routine
practice.
this
paper,
we
developed
a
data
acquisition
analysis
system
based
IMU
devices,
proposed
simple
yet
accurate
calibration
reduce
drifting
errors,
designed
machine
learning
algorithm
obtain
real-time
coordinates
from
data,
computed
parameters,
derived
formula
scores
with
significant
correlation
physician's
observational
scores.
Journal of Functional Morphology and Kinesiology,
Journal Year:
2025,
Volume and Issue:
10(1), P. 73 - 73
Published: Feb. 22, 2025
Background/Objectives:
Falls
among
the
older
adult
population
represent
a
significant
public
health
concern,
often
leading
to
diminished
quality
of
life
and
serious
injuries
that
escalate
healthcare
costs,
they
may
even
prove
fatal.
Accurate
fall
risk
prediction
is
therefore
crucial
for
implementing
timely
preventive
measures.
However,
date,
there
no
definitive
metric
identify
individuals
with
high
experiencing
fall.
To
address
this,
present
study
proposes
novel
approach
transforms
biomechanical
time-series
data,
derived
from
gait
analysis,
into
visual
representations
facilitate
application
deep
learning
(DL)
methods
assessment.
Methods:
By
leveraging
convolutional
neural
networks
(CNNs)
Siamese
(SNNs),
proposed
framework
effectively
addresses
challenges
limited
datasets
delivers
robust
predictive
capabilities.
Results:
Through
extraction
distinctive
gait-related
features
generation
class-discriminative
activation
maps
using
Grad-CAM,
random
forest
(RF)
machine
(ML)
model
not
only
achieves
commendable
accuracy
(83.29%)
but
also
enhances
explainability.
Conclusions:
Ultimately,
this
underscores
potential
advanced
computational
tools
algorithms
improve
prediction,
reduce
burdens,
promote
greater
independence
well-being
adults.
Athena health & research journal.,
Journal Year:
2025,
Volume and Issue:
1(3)
Published: March 7, 2025
Introduction:
The
Gait
Assessment
and
Intervention
Tool
(GAIT)
is
an
observational
gait
scale
designed
to
identify
evaluate
pattern
alterations
in
individuals
with
Stroke.
Objective:
To
translate,
culturally
adapt,
validate
the
European
Portuguese
version
of
GAIT,
ensuring
its
applicability
clinical
practice
research.
Material
Methods:
study
was
conducted
two
phases:
(1)
Translation
cultural
adaptation,
following
international
guidelines,
including
translation,
back-translation,
review
by
a
panel
11
experts
pre-testing;
(2)
Content
validation,
assessed
nine
using
Validity
Index
(CVI).
Results:
final
GAIT
achieved
100%
agreement
among
pre-test
phase.
In
content
30
out
31
items
were
rated
as
"very
relevant"
or
"quite
(I-CVI
≥
0.87),
resulting
S-CVI
0.996,
indicating
excellent
validity.
Discussion:
demonstrated
conceptual
equivalence
original
strong
These
findings
suggest
that
reliable
valuable
tool
for
post-stroke
assessment,
supporting
identification
specific
impairments
implementation
targeted
interventions.
Conclusion:
high
validity
scores
expert
support
use
Future
studies
should
inter-
intra-rater
reliability
explore
integration
digital
technologies
analysis.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: March 19, 2025
Gait
impairment,
which
is
commonly
observed
in
stroke
survivors,
underscores
the
imperative
of
rehabilitating
walking
function.
Wearable
inertial
measurement
units
(IMUs)
can
capture
gait
parameters
patients,
becoming
a
promising
tool
for
objective
and
quantifiable
assessment.
Optimal
sensor
placement
assessment
that
involves
optimal
combinations
features
(kinematics)
required
to
improve
accuracy
while
reducing
number
sensors
achieve
convenient
IMU
scheme
both
clinical
home
assessment;
however,
previous
studies
lack
comprehensive
discussions
on
features.
To
obtain
an
assessment,
this
study
investigated
impact
based
data
scores
16
patients.
Stepwise
regression
was
performed
select
kinematics
most
correlated
with
(lower
limb
part
Fugl-Meyer
assessment).
Sensors
at
different
locations
were
combined
into
28
groups
their
compared.
First,
reduced
does
not
significantly
Second,
selected
by
stepwise
are
found
all
from
hip
bilateral
thighs.
Last,
three-sensor
scheme–sensors
thighs
suggested,
achieved
high
adjusted
R2
=
0.999,
MAE
0.07,
RMSE
0.08.
Further,
prediction
error
zero
if
predicted
lower
scales
rounded
nearest
integer.
These
findings
offer
solution
quantitatively
assessing
Therefore,
IMU-based
provides
complementary
rehabilitation
Sensors,
Journal Year:
2025,
Volume and Issue:
25(7), P. 1994 - 1994
Published: March 22, 2025
Stroke
is
the
fifth
leading
cause
of
death
in
Taiwan.
In
process
stroke
treatment,
rehabilitation
for
gait
recovery
one
most
critical
aspects
treatment.
The
Gait
Assessment
and
Intervention
Tool
(G.A.I.T.)
currently
used
clinical
practice
to
assess
level;
however,
G.A.I.T.
heavily
depends
on
physician
training
judgment.
With
advancement
technology,
today's
small,
lightweight
inertial
measurement
unit
(IMU)
wearable
sensors
are
rapidly
revolutionizing
assessment
may
be
incorporated
into
routine
practice.
this
paper,
we
developed
a
data
acquisition
analysis
system
based
IMU
devices,
proposed
simple
yet
accurate
calibration
reduce
drifting
errors,
designed
machine
learning
algorithm
obtain
real-time
coordinates
from
data,
computed
parameters,
derived
formula
scores
with
significant
correlation
physician's
observational
scores.
