IP Journal of Surgery and Allied Sciences,
Год журнала:
2024,
Номер
6(1), С. 1 - 4
Опубликована: Апрель 10, 2024
The
integration
of
technology
in
physiotherapy
practices
holds
immense
promise
for
advancing
patient
care
and
outcomes.
Yet,
the
swift
evolution
technological
solutions
necessitates
a
cautious
discerning
approach
from
physiotherapists.
This
article
explores
complexities
surrounding
adoption
physiotherapy,
emphasizing
thorough
evaluation,
critical
analysis,
context-driven
implementation.
By
acknowledging
limitations
constraints
inherent
various
advancements,
physiotherapists
can
effectively
harness
their
potential
while
prioritizing
patient-centered
evidence-based
practice.
Such
an
ensures
that
serves
as
tool
to
augment
clinical
decision-making
therapeutic
interventions,
rather
than
overshadowing
fundamental
principles
personalized
holistic
rehabilitation.
As
continues
reshape
landscape
balanced
strategy
values
both
innovation
well-being
remains
paramount
optimizing
outcomes
fostering
sustainable
healthcare
practices.
Diagnostics,
Год журнала:
2024,
Номер
14(13), С. 1333 - 1333
Опубликована: Июнь 23, 2024
This
study
delves
into
the
transformative
potential
of
integrating
augmented
reality
(AR)
within
imaging
technologies,
shedding
light
on
this
evolving
landscape.
Through
a
comprehensive
narrative
review,
research
uncovers
wealth
literature
exploring
intersection
between
AR
and
medical
imaging,
highlighting
its
growing
prominence
in
healthcare.
AR's
integration
offers
host
opportunities
to
enhance
surgical
precision,
bolster
patient
engagement,
customize
interventions.
Moreover,
when
combined
with
technologies
like
virtual
(VR),
artificial
intelligence
(AI),
robotics,
opens
up
new
avenues
for
innovation
clinical
practice,
education,
training.
However,
amidst
these
promising
prospects
lie
numerous
unanswered
questions
areas
ripe
exploration.
emphasizes
need
rigorous
elucidate
efficacy
AR-integrated
interventions,
optimize
workflows,
address
technological
challenges.
As
healthcare
landscape
continues
evolve,
sustained
efforts
are
crucial
fully
realizing
impact
imaging.
Systematic
reviews
also
overlook
regulatory
developmental
factors,
particularly
regard
devices.
These
include
compliance
standards,
safety
regulations,
risk
management,
validation,
processes.
Addressing
aspects
will
provide
understanding
challenges
settings,
informing
stakeholders
about
considerations
successful
implementation.
navigating
approval
process
requires
substantial
financial
resources
expertise,
presenting
barriers
entry
smaller
innovators.
Collaboration
across
disciplines
concerted
overcome
be
essential
frontier
harnessing
revolutionize
delivery.
Brain Disorders,
Год журнала:
2023,
Номер
11, С. 100097 - 100097
Опубликована: Сен. 1, 2023
Background:
Hereditary
Spastic
Paraparesis
(HSP),
also
known
as
Strumpell-Lorrain
disease,
is
a
neurodegenerative
disorder
characterized
by
progressive
muscle
weakness,
lower
limb
spasticity,
and
abnormal
gait.
It
genetically
inherited
condition
affecting
the
spinal
cord.
Currently,
there
lack
of
scientific
literature
on
evaluation
space-time
parameters
plantar
pressures
in
individuals
with
HSP.
Therefore,
objective
this
study
to
assess
spatial-temporal
using
motion
sensors
baropodometric
platform.
Case
presentation:
A
50-year-old
female
patient
body
mass
index
(BMI)
22.28
presented
our
hospital
12-year
history
disease.
She
exhibited
typical
symptoms
including
spastic
paraparesis
limbs,
leading
difficulty
walking.
The
initial
symptom
walking
was
diagnosed
when
she
38
years
old.
Apart
from
impairments
associated
spasticity
ataxia,
demonstrated
weakness
without
any
cognitive
deficits.
Conclusions:
This
analysis
elucidates
challenges
faced
disease
walking,
particularly
during
swing
phase,
resulting
reliance
monopodal
support.
Additionally,
experiences
dorsiflexion
ankle
due
gastrocnemius
muscle,
an
increased
load
forefoot.
These
findings
contribute
better
understanding
specific
gait
abnormalities
biomechanical
Multimedia Tools and Applications,
Год журнала:
2024,
Номер
unknown
Опубликована: Апрель 12, 2024
Abstract
Physical
rehabilitation
is
crucial
in
healthcare,
facilitating
recovery
from
injuries
or
illnesses
and
improving
overall
health.
However,
a
notable
global
challenge
stems
the
shortage
of
professional
physiotherapists,
particularly
acute
some
developing
countries,
where
ratio
can
be
as
low
one
physiotherapist
per
100,000
individuals.
To
address
these
challenges
elevate
patient
care,
field
physical
progressively
integrating
Computer
Vision
Human
Activity
Recognition
(HAR)
techniques.
Numerous
research
efforts
aim
to
explore
methodologies
that
assist
exercises
evaluate
movements,
which
incorrect
potentially
worsen
conditions.
This
study
investigates
applying
various
deep-learning
models
for
classifying
using
benchmark
KIMORE
UI-PRMD
datasets.
Employing
Bi-LSTM,
LSTM,
CNN,
CNN-LSTM,
alongside
Random
Search
architectural
design
Hyper-parameter
tuning,
our
investigation
reveals
(CNN)
model
top
performer.
After
cross-validation,
technique
achieves
remarkable
mean
testing
accuracy
rates
93.08%
on
dataset
99.7%
dataset.
marks
slight
improvement
0.75%
0.1%,
respectively,
compared
previous
In
addition,
expanding
beyond
exercise
classification,
this
explores
dataset’s
utility
disease
identification,
consistently
demonstrates
an
outstanding
89.87%,
indicating
its
promising
role
both
identification
within
context
rehabilitation.
Artificial
intelligence
(AI)
has
revolutionized
telerehabilitation
by
integrating
machine
learning
(ML),
big
data
analytics,
and
real-time
feedback
to
create
adaptive,
patient-centered
care.
AI-driven
systems
enhance
analyzing
patient
personalize
therapy,
monitor
progress,
suggest
adjustments,
eliminating
the
need
for
constant
clinician
oversight.
The
benefits
of
AI-powered
include
increased
accessibility,
especially
remote
or
mobility-limited
patients,
greater
convenience,
allowing
patients
perform
therapies
at
home.
However,
challenges
persist,
such
as
privacy
risks,
digital
divide,
algorithmic
bias.
Robust
encryption
protocols,
equitable
access
technology,
diverse
training
datasets
are
critical
addressing
these
issues.
Ethical
considerations
also
arise,
emphasizing
human
oversight
maintaining
therapeutic
relationship.
AI
aids
clinicians
automating
administrative
tasks
facilitating
interdisciplinary
collaboration.
Innovations
like
5G
networks,
Internet
Medical
Things
(IoMT),
robotics
further
telerehabilitation’s
potential.
By
transforming
rehabilitation
into
a
dynamic,
engaging,
personalized
process,
together
represent
paradigm
shift
in
healthcare,
promising
improved
outcomes
broader
worldwide.
JMIR mhealth and uhealth,
Год журнала:
2024,
Номер
12, С. e55003 - e55003
Опубликована: Янв. 24, 2024
Background
Mobile
health
interventions
delivered
through
mobile
apps
are
increasingly
used
in
physiotherapy
care.
This
may
be
because
of
the
potential
to
facilitate
changes
behavior,
which
is
central
aims
care
by
physiotherapists.
A
benefit
using
their
ability
incorporate
behavior
change
techniques
(BCTs)
that
can
optimize
effectiveness
physiotherapeutic
interventions.
Research
continues
suggest
despite
importance,
strategies
often
missing
patient
management.
Evaluating
physiotherapists
use
drive
inform
clinical
practice
and
potentially
improve
outcomes.
Examining
quality
exploring
key
features
support
important
aspects
such
an
evaluation.
Objective
The
primary
aim
this
study
was
describe
range
app
stores
intended
for
patients
secondary
were
assess
quality,
BCTs,
potential.
Methods
systematic
review
undertaken.
Apple
App
Store
Google
Play
searched
a
2-step
search
strategy,
terms
relevant
discipline.
Strict
inclusion
exclusion
criteria
applied:
had
self-contained
(or
stand-alone)
without
requirement
conjunction
with
partner
wearable
device
or
another
plugin.
Included
coded
BCTs
Behavior
Change
Technique
Taxonomy
version
1.
assessed
Rating
Scale,
Scale
app’s
behavior.
Results
In
total,
1240
screened,
35
included.
Of
these
apps,
22
(63%)
available
on
both
platforms.
24
(69%)
general
focus
(eg,
not
condition-specific),
remaining
11
(31%)
being
more
specific
knee
rehabilitation
pelvic
floor
training).
mean
score
(Mobile
Scale)
3.7
(SD
0.4)
5
(range
2.8-4.5).
number
identified
per
8.5
3.6).
most
frequently
included
instruction
how
perform
(n=32),
action
planning
(n=30),
self-monitoring
(n=28).
(App
3.1)
21
3-15).
Conclusions
received
from
physiotherapist
variable
quality.
Although
they
contain
some
varied
widely
across
apps.
International
Registered
Report
Identifier
(IRRID)
RR2-10.2196/29047
Journal of Clinical Medicine,
Год журнала:
2025,
Номер
14(2), С. 525 - 525
Опубликована: Янв. 15, 2025
Background/Objective:
Knee
osteoarthritis
(OA)
is
a
common
and
debilitating
condition
affecting
older
adults,
often
progressing
to
advanced
stages
requiring
total
joint
replacement.
Exercise
therapy
widely
recognized
as
the
first-line
approach
for
prevention
initial
management
of
OA.
This
systematic
review
assessed
effectiveness
home-based
exercises
(HBEs)
compared
supervised
in
alleviating
pain
reducing
disability
among
patients
with
knee
Methods:
A
search
PubMed,
Cochrane
Library,
ScienceDirect
identified
randomized
controlled
trials
(RCTs)
published
between
January
2001
October
2024.
Methodological
quality
was
evaluated
using
Physiotherapy
Evidence
Database
(PEDro)
scale,
meta-analysis
conducted
quantify
efficacy
these
interventions.
Results:
Ten
RCTs
involving
917
were
included,
ranging
moderate
high
methodological
(PEDro
score:
6.3
±
1.2).
Intervention
durations
ranged
from
4
12
weeks.
Both
HBEs
found
be
effective,
but
demonstrated
statistically
significant
improvements
(SMD
=
−0.45
[95%
CI
−0.79;
−0.11],
p
0.015)
−0.28
−0.42;
−0.14],
<
0.001)
HBEs.
Conclusions:
Despite
superiority
over
HBEs,
considering
cost-effectiveness
ease
implementation
we
developed
recommendations
create
hybrid
rehabilitation
program
that
combines
both
approaches
maximize
clinical
outcomes.
Knee
osteoarthritis
(KOA)
is
a
progressive
degenerative
joint
disorder
that
significantly
impacts
mobility,
pain
levels,
and
overall
quality
of
life.
Conventional
rehabilitation
methods,
while
effective,
often
suffer
from
limitations
related
to
patient
adherence,
accessibility,
cost.
This
systematic
review
examines
the
role
virtual
reality
(VR),
augmented
(AR),
sensor-based
technologies
in
KOA
rehabilitation,
evaluating
their
effectiveness
reduction,
functional
improvement,
engagement.
A
comprehensive
literature
search
identified
four
randomized
controlled
trials
(RCTs)
comprising
405
participants,
with
an
average
Physiotherapy
Evidence
Database
(PEDro)
score
6/10,
indicating
moderate
high
methodological
quality.
Findings
suggest
VR
AR
interventions
enhance
adherence
engagement,
systems
provide
real-time
biofeedback,
enabling
personalized
therapeutic
adjustments.
These
demonstrated
significant
improvements
management,
muscle
strength,
mobility.
However,
challenges
such
as
costs,
limited
absence
standardized
treatment
protocols
remain
barriers
widespread
clinical
adoption.
Further
research
should
focus
on
long-term
efficacy,
cost-effectiveness,
integration
these
innovations
into
routine
practice.