Journal of Clinical Medicine,
Journal Year:
2024,
Volume and Issue:
13(19), P. 5792 - 5792
Published: Sept. 28, 2024
Background:
Parkinson’s
disease
(PD)
is
a
neurodegenerative
disorder
with
high
prevalence
in
men
and
characterized
by
symptoms
such
as
tremors
gait
difficulties.
This
study
aimed
to
determine
muscle
activation
patients
PD
considering
sex
differences.
Methods:
pilot
used
analytical,
quantitative,
observational,
case-control
methods.
Surface
electromyography
was
assess
activity
during
variant
of
the
Illinois
agility
test.
The
population
comprised
an
experimental
group
(N
=
30)
control
healthy
individuals
without
10).
Results:
test
revealed
significant
differences
completion
times
between
groups.
took
longer
overall
(p
0.004),
especially
for
standing
up
<
0.001)
sitting
down
0.002),
than
group.
In
group,
influenced
gastrocnemius
activation,
women
showing
higher
(rs
−0.87).
Women
also
had
greater
rectus
femoris
sitting,
on
right
side
when
−0.66)
left
exhibited
biceps
0.87).
However,
did
not
affect
activation.
Conclusions:
Patients
showed
lower
while
up,
down,
walking.
Journal of Sensor and Actuator Networks,
Journal Year:
2025,
Volume and Issue:
14(2), P. 23 - 23
Published: Feb. 20, 2025
(1)
Background:
Wearable
sensors
have
emerged
as
a
promising
technology
in
the
management
of
Parkinson’s
disease
(PD).
These
can
provide
continuous
and
real-time
monitoring
various
motor
non-motor
symptoms
PD,
allowing
for
early
detection
intervention.
In
this
paper,
I
review
current
research
on
application
wearable
focusing
gait,
tremor,
bradykinesia,
dyskinesia
monitoring.(2)
Methods:
involved
literature
search
that
spanned
2000–2024
period
included
following
keywords:
“wearable
sensors”,
“Parkinson’s
Disease”,
“Inertial
“accelerometers’’,
‘’gyroscopes’’,
‘’magnetometers”,
“Smartphones”,
“Smart
homes”.
(3)
Results:
Despite
favorable
outcomes
from
development
inertial
sensors,
like
gyroscopes
accelerometers
smartphones,
is
still
restricted
because
there
are
no
standards,
harmonization,
or
consensus
both
clinical
analytical
validation.
As
result,
several
trials
were
created
to
compare
effectiveness
with
conventional
evaluation
methods
order
track
course
enhance
quality
life
results.
(4)
Conclusions:
hold
great
promise
PD
likely
play
significant
role
future
healthcare
systems.
Medicina,
Journal Year:
2025,
Volume and Issue:
61(3), P. 524 - 524
Published: March 17, 2025
Background
and
Objectives:
Virtual
reality
(VR)-based
interventions
provide
immersive
interactive
environments
that
can
enhance
motor
learning
deliver
real-time
feedback,
offering
potential
advantages
over
conventional
therapies.
This
systematic
review
evaluated
the
impact
of
non-immersive
VR
exergaming
versus
therapy
on
balance
in
Parkinson’s
disease
(PD)
through
a
detailed
analysis
randomized
controlled
trials
(RCTs).
Materials
Methods:
A
comprehensive
search
was
conducted
across
PubMed,
Lilacs,
IBECS,
CENTRAL,
Web
Science
(WOS),
EBSCOHost,
SciELO
databases.
Article
selection
duplicate
removal
were
managed
using
Rayyan
QCRI.
The
quality
evidence
assessed
GRADE
system.
Results:
From
an
initial
screening
100
studies,
58
underwent
title
abstract
screening.
After
full-text
evaluation,
11
RCTs
met
inclusion
criteria,
involving
518
participants
with
PD
(average
age:
67.3
years;
67.95%
men).
outcomes
primarily
measured
Berg
scale
(BBS),
employed
most
studies
(n
=
9).
pooled
demonstrated
significant
improvement
scores
for
experimental
groups
compared
to
controls,
standardized
mean
difference
(SMD)
0.58
[95%
CI:
0.07,
1.09,
p
0.03].
However,
heterogeneity
substantial
(I2
77%).
six-minute
walking
test
(6
MWT),
as
another
outcome
four
articles,
revealed
32.99
m
−8.02,
74.00],
but
effect
not
statistically
(p
0.11).
this
moderate
41%),
indicating
some
variability
studies.
Alternative
tools,
such
Tinetti
Performance-Oriented
Mobility
Assessment
(POMA)
scale,
UPDRS
III,
sensory
organization
(SOT),
also
where
possible.
Conclusions:
VR-based
offer
promise
improving
disease,
enhancing
rehabilitation
engagement.
Their
integration
into
clinical
practice
could
complement
therapy.
further
research
is
needed
optimize
protocols,
standardize
parameters,
maximize
their
mobility,
independence,
life.
Sensors,
Journal Year:
2024,
Volume and Issue:
24(15), P. 4983 - 4983
Published: Aug. 1, 2024
Quantitative
mobility
analysis
using
wearable
sensors,
while
promising
as
a
diagnostic
tool
for
Parkinson's
disease
(PD),
is
not
commonly
applied
in
clinical
settings.
Major
obstacles
include
uncertainty
regarding
the
best
protocol
instrumented
testing
and
subsequent
data
processing,
well
added
workload
complexity
of
this
multi-step
process.
To
simplify
sensor-based
diagnosing
PD,
we
analyzed
from
262
PD
participants
50
controls
performing
several
motor
tasks
wearing
sensor
on
their
lower
back
containing
triaxial
accelerometer
gyroscope.
Using
ensembles
heterogeneous
machine
learning
models
incorporating
range
classifiers
trained
set
features,
show
that
our
effectively
differentiate
between
with
controls,
both
mixed-stage
(92.6%
accuracy)
group
selected
mild
only
(89.4%
accuracy).
Omitting
algorithmic
segmentation
complex
decreased
accuracy
models,
did
inclusion
kinesiological
features.
Feature
importance
revealed
Timed
Up
Go
(TUG)
to
contribute
highest-yield
predictive
minor
decreases
based
cognitive
TUG
single
task.
Our
approach
facilitates
major
simplification
without
compromising
performance.
Research Square (Research Square),
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 21, 2025
Abstract
Background
Classifying
and
predicting
Parkinson's
disease
(PD)
is
challenging
because
of
its
diverse
subtypes
based
on
severity
levels.
Currently,
identifying
objective
biomarkers
associated
with
that
can
distinguish
PD
in
clinical
trials
necessary.
This
study
aims
to
address
the
applicability
heterogeneity
using
classification
digital
biomarker
development
by
combining
multimodal
data
machine
learning
(ML)
approaches.
Methods
We
analyzed
datasets
combine
characteristics,
physical
function
lifestyle
data,
gait
parameters
motion
analysis
systems,
wearable
sensors
collected
from
persons
(n
=
102)
perform
clustering
for
subtype
classification.
Results
identified
three
subtypes,
each
exhibiting
different
patterns
severity,
increasing
as
it
progressed
clusters
1
3.
found
significant
mutual
information
between
all/single
modalities
unified
rating
scale
scores,
potential
high
feature
importance
ML.
Among
all
modalities,
principal
components
derived
were
most
indicators
severity.
A
model
utilizing
first
component
left
right
ankle
achieved
perfect
an
area
under
curve
1.0,
accurately
distinguishing
clinically
severe
mild
PD.
These
findings
suggest
features
both
ankles
reflect
asymmetry
factors
which
contributes
performance.
Conclusions
Digital
obtained
attached
bilaterally
body
segments
demonstrate
classifying
tracking
progression.
Our
emphasized
value
sensor-based
management,
suggested
integration
into
personalized
monitoring
systems
therapeutic
interventions
Sensors,
Journal Year:
2024,
Volume and Issue:
24(13), P. 4172 - 4172
Published: June 27, 2024
Manual
wheelchair
users
(MWUs)
are
prone
to
a
sedentary
life
that
can
negatively
affect
their
physical
and
cardiovascular
health,
making
regular
assessment
important
identify
appropriate
interventions
lifestyle
modifications.
One
mean
of
assessing
MWUs’
health
is
the
6
min
push
test
(6MPT),
where
user
propels
themselves
as
far
they
in
six
minutes.
However,
reliance
on
observer
input
introduces
subjectivity,
while
limited
quantitative
data
inhibit
comprehensive
assessment.
Incorporating
sensors
into
6MPT
address
these
limitations.
Here,
ten
MWUs
performed
with
additional
sensors:
two
inertial
measurement
units
(IMUs)—one
one
wrist
together
heart
rate
wristwatch.
The
conventional
measurements
distance
laps
were
recorded
by
observer,
IMU
used
calculate
laps,
distance,
speed,
cadence.
results
demonstrated
provide
metrics
traditional
strong
significant
correlations
between
calculated
lap
counts
(r
=
0.947,
p
<
0.001)
distances
0.970,
0.001).
Moreover,
during
final
minute
was
significantly
correlated
0.762,
0.017).
Enhanced
objective,
quantitative,
for
clinicians
effectively
inform
rehabilitation.
Sensors,
Journal Year:
2024,
Volume and Issue:
24(22), P. 7284 - 7284
Published: Nov. 14, 2024
Reduced
walking
endurance
is
common
in
people
with
multiple
sclerosis
(PwMS),
leading
to
reduced
social
participation
and
increased
fall
risk.
This
highlights
the
importance
of
identifying
which
gait
aspects
should
be
mostly
targeted
by
rehabilitation
maintain/increase
this
population.
A
total
56
PwMS
24
healthy
subjects
(HSs)
executed
6
min
walk
test
(6
MWT),
a
clinical
measure
endurance,
wearing
three
inertial
sensors
(IMUs)
on
their
shanks
lower
back.
Five
IMU-based
digital
metrics
descriptive
different
domains,
i.e.,
double
support
duration,
trunk
sway,
regularity,
symmetry,
local
dynamic
instability,
were
computed.
All
demonstrated
moderate-high
ability
discriminate
between
HSs
(AUC:
0.79-0.91)
able
detect
differences
at
minimal
(PwMS
Life,
Journal Year:
2024,
Volume and Issue:
14(11), P. 1514 - 1514
Published: Nov. 20, 2024
Patients
with
COVID-19
suffering
in
the
acute
phase
from
both
sequelae
of
disease
and
prolonged
immobilization
require
a
rehabilitation
for
functional
recovery
comprehensive
evaluation.
This
study
proposes
using
6-Minute
Walk
Test
(6MWT)
as
global
assessment
tool
to
quantify
outcomes
post-COVID
patients.
Additionally,
investigating
effect
High-Intensity
Laser
Therapy
(HILT)
on
patients
musculoskeletal
comorbidities
was
another
key
research
question.
Two
programs
were
retrospectively
analyzed
follows:
one
consisting
kinesiotherapy
combined
other
alone.
Functional
evaluation
6MWT
conducted
before
after
10
daily
therapeutic
sessions
33
ambulatory
divided
into
2
groups
(18
treated
HILT
vs.
15
only).
The
successfully
completed
by
32
out
(96.96%),
performance
improvements
ranging
3%
60%
among
Statistical
differences
also
observed
between
groups,
suggesting
that
is
sensitive,
objective,
valuable
rehabilitation,
supporting
potential
benefits
enhancing
recovery.
