Sensors,
Journal Year:
2024,
Volume and Issue:
25(1), P. 139 - 139
Published: Dec. 29, 2024
Artificial
Intelligence
(AI)
is
transforming
the
field
of
sports
science
by
providing
unprecedented
insights
and
tools
that
enhance
training,
performance,
health
management.
This
work
examines
how
AI
advancing
role
scientists,
particularly
in
team
environments,
improving
training
load
management,
player
well-being.
It
explores
key
dimensions
such
as
optimization,
injury
prevention
return-to-play,
talent
identification
scouting,
off-training
behavior,
sleep
quality,
menstrual
cycle
Practical
examples
illustrate
applications
have
significantly
advanced
each
area
they
support
effectiveness
scientists.
manuscript
also
underscores
importance
ensuring
technologies
are
context-specific
communicated
transparently.
Additionally,
it
calls
for
academic
institutions
to
update
their
curriculums
with
AI-focused
education,
preparing
future
professionals
fully
harness
its
potential.
Finally,
addresses
challenges,
unpredictable
nature
sports,
emphasizing
need
interdisciplinary
collaboration,
including
clear
communication
mutual
understanding
between
scientists
experts,
critical
balance
AI-driven
human
expertise.
Advances in healthcare information systems and administration book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 86 - 108
Published: Feb. 14, 2024
This
chapter
presents
a
bibliometric
analysis
of
extended
reality
technologies
(i.e.,
augmented,
virtual,
and
mixed
reality)
concerning
physical
fitness
by
analyzing
251
published
documents
from
Scopus-indexed
sources.
Results
the
indicated
that
medicine
computer
science
are
prominent
subject
areas,
International
Journal
Environmental
Research
Public
Health
Lecture
Notes
in
Computer
Science
leading
publishers
this
domain.
The
further
found
variability
terms
authorship
patterns
international
collaboration
58
documents.
In
addition
to
this,
there
has
been
steady
increase
publications
domain,
with
substantial
surge
2019
onwards.
United
States
China
contributors,
several
collaborative
networks
among
countries,
particularly
high-income,
western
nations.
Furthermore,
keyword
co-occurrences
is
focus
on
VR,
gamification,
health
issues
related
older
adults.
Retos,
Journal Year:
2024,
Volume and Issue:
58, P. 85 - 94
Published: June 22, 2024
This
study
explores
the
effectiveness
of
exercise
monitoring
systems
in
improving
athlete
performance
and
motivation
within
educational
settings.
Two
hypotheses
were
formulated
tested:
one
positing
that
utilization
would
reduce
muscle
injury
rates
among
athletes,
other
suggesting
it
increase
athletes'
levels.
The
experimental
design
involved
dividing
participants
into
control
groups,
with
former
utilizing
proposed
system
latter
employing
traditional
teaching
methods.
Assessments
conducted
post-session
to
measure
comprehension
levels,
evaluation
criteria
focusing
on
accurate
identification
course
components.
Contrary
expectations,
results
did
not
support
hypotheses,
indicating
no
significant
reduction
or
levels
athletes
exposed
system.
These
findings
underscore
need
for
a
nuanced
understanding
complex
factors
influencing
development
outcomes.
Future
research
should
employ
rigorous
methodologies
objective
outcome
measures
further
elucidate
role
optimize
their
integration
training
programs,
thus
contributing
advancements
contexts.
Keywords:
system,
real-time
feedback,
performance,
innovative
instructional
approaches,
motivation,
injury,
technology,
fitness
training.
Journal of Functional Morphology and Kinesiology,
Journal Year:
2024,
Volume and Issue:
9(3), P. 114 - 114
Published: June 28, 2024
The
aim
of
this
study
was
to
test
a
machine
learning
(ML)
model
predict
high-intensity
actions
and
body
impacts
during
youth
football
training.
Sixty
under-15,
-17,
-19
sub-elite
Portuguese
players
were
monitored
over
6-week
period.
External
training
load
data
collected
from
the
target
variables
accelerations
(ACCs),
decelerations
(DECs),
dynamic
stress
(DSL)
using
an
18
Hz
global
positioning
system
(GPS).
Additionally,
we
perceived
exertion
biological
characteristics
total
quality
recovery
(TQR),
rating
(RPE),
session
RPE
(sRPE),
chronological
age,
maturation
offset
(MO),
age
at
peak
height
velocity
(APHV).
ML
computed
by
feature
selection
process
with
linear
regression
forecast
bootstrap
method.
predictive
analysis
revealed
that
players'
MO
demonstrated
varying
degrees
effectiveness
in
predicting
their
DEC
ACC
across
different
ranges
IQR.
After
analysis,
following
performance
values
observed:
(x¯
Advances in psychology, mental health, and behavioral studies (APMHBS) book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 367 - 394
Published: Jan. 3, 2025
This
chapter
explores
the
transformative
impact
of
virtual
reality
(VR)
and
artificial
intelligence
(AI)
in
therapeutic
settings.
It
examines
how
VR's
immersive
environments
AI's
data-driven
insights
enhance
practices,
including
exposure
therapy,
cognitive
rehabilitation,
anxiety
management.
By
aligning
with
psychological
neurological
theories,
these
technologies
offer
innovative
solutions
for
improving
patient
outcomes.
The
also
addresses
challenges
such
as
high
costs,
data
privacy,
need
rigorous
research.
Future
directions
emphasize
importance
ongoing
development,
ethical
considerations,
empirical
validation.
Ultimately,
VR
AI
hold
potential
to
revolutionize
offering
more
effective,
personalized,
treatment
options.
Molecular & cellular biomechanics,
Journal Year:
2025,
Volume and Issue:
22(1), P. 670 - 670
Published: Jan. 6, 2025
This
work
explores
the
effective
application
of
deep
learning
for
recognizing
athletes’
movements,
aiming
to
enhance
precision
in
competitive
sports.
Traditional
motion
analysis
methods
primarily
rely
on
manual
observation,
which
can
introduce
subjective
bias
and
limit
accuracy.
To
address
these
limitations,
we
propose
an
automated
method
based
classifying
technical
movements
while
evaluating
their
performance.
A
hybrid
model,
combining
Convolutional
Neural
Networks
(CNN)
Long
Short-Term
Memory
(LSTM)
networks,
is
utilized
extract
key
frames
from
video
data.
The
CNN
responsible
feature
extraction,
capturing
intricate
details
movement,
LSTM
captures
temporal
sequence
characteristics,
providing
context
actions.
further
strengthen
our
approach,
delve
into
biological
mechanisms
underlying
athletic
movements.
Understanding
biomechanics
motion—such
as
joint
angles,
muscle
activation
patterns,
energy
expenditure—can
accuracy
models.
By
integrating
insights
improve
recognition
process,
allowing
a
more
nuanced
understanding
how
impact
Through
experiments,
demonstrate
that
model
achieves
high
across
multiple
benchmark
datasets
(UCF-101,
HMDB-51,
Kinetics-400,
Sports-1M),
with
particularly
93.5%
UCF-101
dataset.
These
results
indicate
proposed
both
accurate
reliable,
making
it
suitable
athlete
training
competition
analysis.
findings
this
research
have
significant
implications
sports
science,
evaluation,
injury
prevention.
coaches
athletes
precise
feedback
analysis,
facilitate
targeted
interventions
performance
reducing
risks.
aims
offer
powerful
tool
athletes,
coaches,
researchers,
contributing
advancement
through
deeper
movement
dynamics
underpinnings.
Concurrency and Computation Practice and Experience,
Journal Year:
2025,
Volume and Issue:
37(3)
Published: Jan. 14, 2025
ABSTRACT
With
the
rapid
development
of
Artificial
Intelligence
(AI)
technology,
athletics
field
is
undergoing
profound
changes.
This
transformation
reflected
not
only
in
ways
training
and
competition
but
also
overall
enhancement
athletes'
performance
efficiency
event
management.
The
introduction
AI
has
made
data
analysis
feasible,
enabling
coaches
athletes
to
gain
deeper
insights
make
more
informed
decisions.
paper
reviews
current
applications
domain
its
athlete
competitive
strategies,
focusing
on
practical
management,
analysis,
injury
detection,
personalized
training.
Furthermore,
systems
support
intelligent
by
integrating
historical
with
real‐time
data,
thereby
improving
tactical
decision‐making.
However,
despite
significant
achievements
applications,
a
series
challenges
remain,
including
lack
high‐quality
datasets,
insufficient
model
interpretability,
ethical
privacy
issues.
In
light
these
challenges,
we
propose
viewpoints
future
directions
aimed
at
promoting
industry.
Molecular & cellular biomechanics,
Journal Year:
2025,
Volume and Issue:
22(2), P. 764 - 764
Published: Jan. 21, 2025
Postural
mechanics
and
movement
control
play
fundamental
roles
in
artistic
creation,
particularly
painting,
where
precision
fluidity
of
motion
directly
influence
outcomes.
This
study
investigated
the
biomechanical
relationships
between
posture,
movement,
painting
practice
through
a
comprehensive
analysis
38
artists
(22
Female,
16
Male)
ranging
from
novice
to
expert-level
practitioners
traditional
Chinese
contemporary
techniques.
Using
an
integrated
measurement
approach
combining
Motion
Capture
System
(MCS)
(Vicon
System),
electromyography
(EMG),
force
plate
analysis,
we
examined
postural
dynamics,
patterns,
their
effects
on
across
varied
conditions.
Results
revealed
significant
correlations
stability
(r
=
0.82,
p
<
0.001),
with
experienced
demonstrating
superior
strategies
compared
novices.
Analysis
seated
versus
standing
positions
showed
distinct
advantages
metrics
(88.5
±
4.2
vs.
82.3
5.6
index,
0.01),
though
offered
more
excellent
range
(58.7
cm
7.2
42.3
brush
reach,
0.001).
Environmental
factors,
easel
configuration
lighting
conditions,
significantly
impacted
performance,
optimal
height
(90%–105%
eye
level)
correlating
enhanced
scores
(improvement
18.4
4.2%,
Tool
selection
demonstrated
that
medium-length
brushes
(20
cm–30
cm)
provided
comfort
(8.7
0.9
out
10)
(88.6
3.8
100)
scores.
Extended
sessions
progressive
changes
muscle
activation
expert
maintaining
consistent
patterns
despite
fatigue
(8.4
1.2%
18.7
3.2%
variability,
These
findings
provide
quantitative
evidence
for
importance
proper
creation
offer
practical
insights
optimizing
performance
improved
awareness
environmental
setup.
