Role of Robotics in the Assessment of Neurodegenerative Disorders
Krishnasamy Tamilselvam Yokhesh
IntechOpen eBooks,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 16, 2025
Neurodegenerative
disorders
are
characterized
by
the
degeneration
of
nerve
cells,
causing
debilitating
symptoms
that
negatively
impact
patient’s
quality
life.
Traditionally,
assessment
neurodegenerative
relies
on
clinical
evaluations,
which
subjective
and
inconsistent.
An
objective
evaluation
is
vital
to
provide
good
care
patients.
With
emergence
robotic
technology,
several
novel
robot
systems
have
been
developed
improve
treatment
techniques
for
neurogenerative
disorders.
Wearable
robots,
include
motion
sensors,
real-time
monitoring
upper-limb
gait
movements,
offers
a
comprehensive
set
information
detect
early
signs
motor
deterioration.
Similarly,
exoskeletons
more
prevalently
proposed
as
an
tool.
These
not
only
enhance
accuracy
assessments
but
also
reduce
burden
healthcare
professionals
automating
routine
tasks.
few
sets
in
recent
times.
This
chapter
aims
focus
discussing
assessment,
treatment,
rehabilitation
patients
diagnosed
with
Furthermore,
we
will
elaborate
existing
limitations
systems,
thereby
highlighting
scope
future
studies.
Язык: Английский
Sensorimotor Integration: A Review of Neural and Computational Models and the Impact of Parkinson’s Disease
IEEE Transactions on Cognitive and Developmental Systems,
Год журнала:
2024,
Номер
17(1), С. 3 - 21
Опубликована: Дек. 23, 2024
Язык: Английский
Hypo-connectivity of the primary somatosensory cortex in Parkinson’s disease: a resting-state functional MRI study
Frontiers in Neurology,
Год журнала:
2024,
Номер
15
Опубликована: Апрель 30, 2024
Background
Parkinson’s
disease
(PD)
is
characterized
by
a
range
of
motor
symptoms
as
well
documented
sensory
dysfunction.
This
dysfunction
can
present
itself
either
“pure”
disturbance
or
consequence
sensory-motor
integration
within
the
central
nervous
system.
study
aims
to
investigate
changes
in
functional
connectivity
primary
somatosensory
cortex
(S1)
and
its
clinical
significance
(PD),
an
area
that
has
received
limited
attention
previous
neuroimaging
studies.
Methods
included
thirty-three
patients
with
PD
thirty-four
healthy
controls
(HCs).
Clinical
evaluations
were
conducted
assess
manifestations,
severity,
capacity
all
patients.
Resting-state
MRI
(fMRI)
was
employed
evaluate
six
paired
S1
subregions
participants.
Seed-based
correlation
(SBC)
analysis
utilized
construct
matrix
among
generate
maps
between
remaining
brain
voxels.
Finally,
partial
least-squares
(PLS)
association
modified
characteristics
Results
In
matrix,
demonstrated
notable
decrease
across
various
comparison
HCs
(
p
<
0.001,
corrected
using
network-based
methods).
maps,
hypo-connectivity
primarily
observed
sensorimotor
network
common
patterns
for
false
discovery
rate)
default
mode
(DMN)
distinct
patterns.
Moreover,
this
identified
negative
scores
axial
postural
instability/gait
difficulty
(PIGD)
Nevertheless,
direct
relationship
assessment
scales
not
established.
Conclusion
offers
novel
insights
into
neurobiological
mechanisms
contribute
PD,
highlighting
significant
involvement
disturbances
Язык: Английский