Smart and Sustainable Built Environment,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 24, 2024
Purpose
This
paper
aims
to
analyze
the
current
state
of
technological
advancements
research
in
addressing
diverse
risk
factors
involved
earthmoving
equipment
operations
through
Rasmussen's
(1997)
management
framework.
It
examines
how
existing
technologies
capture,
manage
and
disseminate
information
across
various
levels
safety
by
defining
their
core
functionalities.
The
highlights
gaps
solutions
regarding
flow
emphasizes
need
for
an
integrated
approach
enhance
holistic
capable
capturing
risks
different
management.
Design/methodology/approach
employs
a
multistep
approach.
Initially,
functionalities
were
identified
systematic
review
scholarly
works.
Subsequently,
social
network
analysis
(SNA)
Pareto
applied
evaluate
determine
importance
improving
them.
Findings
findings
highlight
multilevel
approaches
that
expand
address
all
combination
focuses
primarily
on
on-site
monitoring,
congested
work
sites,
site
layout/path
planning,
utility
problems,
training,
blind
spot
visibility.
Site
monitoring
warning
systems,
supported
sensors
computer
vision
(CV),
are
pivotal
identifying
enabling
data-driven
However,
workforce-level
cognitive
(W1-W6),
which
influence
behavior,
remain
underexplored
enhancing
functionality
anticipation
response
during
operation.
Prevention
is
function
solutions,
emphasizing
human
such
as
sources
hazards
operations.
Learning:
AI
IoT
systems
key
future
development,
when
grounded
ontology-based
knowledge
earthwork,
they
gain
structured
types,
interactions
earthwork
activities.
enhances
capabilities
these
capture
complex
between
hazard
(human
equipment),
supporting
comprehensive
Originality/value
elucidates
require
more
approach—grounded
understanding
technologies—to
effectively
Rasmussen
should
not
only
isolated
but
also
ensure
continuous
multiple
ACM Transactions on Computing for Healthcare,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 21, 2024
Mental
fatigue
is
a
crucial
aspect
that
has
gained
attention
across
various
disciplines
due
to
its
impact
on
overall
well-being.
While
previous
research
explored
the
use
of
wearable
devices
for
detecting
mental
fatigue,
limited
investigation
been
conducted
into
effectiveness
these
in
different
body
positions
or
multi-device
setups.
To
address
this,
our
study
utilizes
unique
public
dataset
containing
over
13
hours
sensor
data
collected
36
sessions,
with
four
(Earable,
Chestband,
Wristband,
and
Headband).
We
propose
several
machine
learning-based
approaches
assess
both
psychological
physiological
levels
multimodal
environment.
Specifically,
we
introduce
device
type-specific
(trained
tested
single
device)
multiple
devices)
inference
tasks.
Our
findings
show
models
perform
well,
AUC
scores
ranging
from
0.63
0.69
0.74
0.80
fatigue.
The
approach
shows
improved
performance
(AUC
0.74)
0.81
0.88).
Hence,
this
presents
in-depth
analysis
wearables,
demonstrating
potential
setups
are
prevalent
today’s
emerging
lifestyles.
Sensors,
Journal Year:
2023,
Volume and Issue:
23(23), P. 9522 - 9522
Published: Nov. 30, 2023
Despite
longstanding
traditional
construction
health
and
safety
management
(CHSM)
methods,
the
industry
continues
to
face
persistent
challenges
in
this
field.
Neuroscience
tools
offer
potential
advantages
addressing
these
issues
by
providing
objective
data
indicate
subjects’
cognition
behavior.
The
application
of
neuroscience
CHSM
has
received
much
attention
research
community,
but
comprehensive
statistics
on
is
lacking
provide
insights
for
later
scholars.
Therefore,
study
applied
bibliometric
analysis
examine
current
state
use
CHSM.
development
phases;
most
productive
journals,
regions,
institutions;
influential
scholars
articles;
author
collaboration;
reference
co-citation;
domains
were
identified.
It
revealed
four
domains:
monitoring
status
workers,
enhancing
hazard
recognition
ability,
reducing
work-related
musculoskeletal
disorders
integrating
with
artificial
intelligence
techniques
occupational
health,
where
magnetoencephalography
(EMG),
electroencephalography
(EEG),
eye-tracking,
electrodermal
activity
(EDA)
are
predominant
tools.
also
shows
a
growing
interest
address
issues.
In
addition,
future
studies
suggested
facilitate
applications
workplaces
narrowing
gaps
between
experimental
settings
real
situations,
quality
collected
performance
processing
algorithms,
overcoming
user
resistance
adoption.
Review of Scientific Instruments,
Journal Year:
2023,
Volume and Issue:
94(9)
Published: Sept. 1, 2023
Fatigue
has
become
an
important
health
problem
in
modern
life;
excessive
mental
fatigue
may
induce
various
cardiovascular
diseases.
Most
current
recognition
is
based
only
on
specific
scenarios
and
tasks.
To
improve
the
accuracy
of
daily
recognition,
this
paper
proposes
a
multimodal
grading
method
that
combines
three
signals
electrocardiogram
(ECG),
photoplethysmography
(PPG),
blood
pressure
(BP).
We
collected
ECG,
PPG,
BP
from
22
subjects
during
time
periods:
morning,
afternoon,
evening.
Based
these
signals,
56
characteristic
parameters
were
extracted
multiple
dimensions,
which
comprehensively
covered
physiological
information
different
states.
The
compared
with
feature
optimization
ability
recursive
elimination
(RFE),
maximal
coefficient,
joint
mutual
information,
optimum
matrix
selected
was
input
into
random
forest
(RF)
for
three-level
classification.
results
showed
classification
using
one
88.88%,
92.72%
combination
two
features,
94.87%
all
features.
This
study
indicates
fusion
traits
contains
more
comprehensive
better
identifies
level
fatigue,
RFE-RF
model
performs
best
identification.
variability
index
useful
Data in Brief,
Journal Year:
2023,
Volume and Issue:
52, P. 109896 - 109896
Published: Dec. 9, 2023
The
prevalence
of
mental
fatigue
is
a
noteworthy
phenomenon
that
can
affect
individuals
across
diverse
professions
and
working
routines.
This
paper
provides
comprehensive
dataset
physiological
signals
obtained
from
23
participants
during
their
professional
work
questionnaires
to
analyze
fatigue.
included
demographic
information
Chalder
Fatigue
Scale
scores
indicating
physical
Both
signal
measurements
the
were
performed
in
two
sessions,
morning
evening.
present
encompasses
signals,
including
electroencephalogram
(EEG),
blood
volume
pulse
(BVP),
electrodermal
activity
(EDA),
heart
rate
(HR),
skin
temperature
(TEMP),
3-axis
accelerometer
(ACC)
data.
NeuroSky
MindWave
EEG
device
was
used
for
brain
Empatica
E4
smart
wristband
other
signals.
Measurements
carried
out
on
four
different
occupational
groups,
such
as
academicians,
technicians,
computer
engineers,
kitchen
workers.
provision
metadata
supplements
dataset,
thereby
promoting
inquiries
about
neurophysiological
concomitants
fatigue,
autonomic
patterns,
repercussions
cognitive
burden
human
proficiency
actual
workplace
settings.
accessibility
aforementioned
serves
facilitate
progress
field
research
while
also
laying
groundwork
creation
customized
evaluation
techniques
interventions
domains.
Frontiers in Built Environment,
Journal Year:
2023,
Volume and Issue:
9
Published: Dec. 15, 2023
Introduction:
This
study
investigated
the
influence
of
indoor
lighting
environments
on
paper
reading
efficiency
and
brain
fatigue
to
explore
parameters
that
benefit
users
during
various
durations.
Methods:
The
was
conducted
in
Smart
Lighting
Lab,
where
12
participants
were
tested
under
different
illuminance
levels
correlated
color
temperatures
(CCT)
for
three
distinct
Reading
task
tests
objective
measures
activity
by
monitoring
participants’
electroencephalograms
(EEGs)
used
as
key
factors
assess
levels.
Results:
By
analyzing
subjective
results,
we
found
significantly
affected
changes
environment.
Also,
based
results
this
study,
propose
recommendations
tasks
For
a
15
min
task,
condition
500
lux-6,500
K
most
efficient
reading;
30
lux-4,000
be
effective;
750
best
environment
60
duration.
Discussion:
These
suggestions
can
serve
reference
designing
In
addition,
they
provide
guidance
researchers
reviewers
conducting
similar
studies.
Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(22), P. 10510 - 10510
Published: Nov. 14, 2024
The
detection
of
the
human
mental
fatigue
state
holds
immense
significance
due
to
its
direct
impact
on
work
efficiency,
specifically
in
system
operation
control.
Numerous
approaches
have
been
proposed
address
challenge
detection,
aiming
identify
signs
and
alert
individual.
This
paper
introduces
an
approach
assessment
based
application
machine
learning
techniques
video
a
working
operator.
For
validation
purposes,
was
applied
dataset,
“Human
Fatigue
Assessment
Based
Video
Data”
(HFAVD)
integrating
data
with
features
computed
by
using
our
computer
vision
deep
models.
incorporated
encompass
head
movements
represented
Euler
angles
(roll,
pitch,
yaw),
vital
(blood
pressure,
heart
rate,
oxygen
saturation,
respiratory
rate),
eye
mouth
states
(blinking
yawning).
integration
these
eliminates
need
for
manual
calculation
or
parameters,
it
obviates
requirement
sensors
external
devices,
which
are
commonly
employed
existing
datasets.
main
objective
is
advance
research
particularly
academic
settings.
this
reason,
we
conducted
series
experiments
utilizing
analyze
dataset
assess
predicted
results
reveal
that
random
forest
technique
consistently
achieved
highest
accuracy
F1-score
across
all
experiments,
predominantly
exceeding
90%.
These
findings
suggest
highly
promising
task
prove
strong
connection
association
among
used
annotate
videos
fatigue.
Smart and Sustainable Built Environment,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 24, 2024
Purpose
This
paper
aims
to
analyze
the
current
state
of
technological
advancements
research
in
addressing
diverse
risk
factors
involved
earthmoving
equipment
operations
through
Rasmussen's
(1997)
management
framework.
It
examines
how
existing
technologies
capture,
manage
and
disseminate
information
across
various
levels
safety
by
defining
their
core
functionalities.
The
highlights
gaps
solutions
regarding
flow
emphasizes
need
for
an
integrated
approach
enhance
holistic
capable
capturing
risks
different
management.
Design/methodology/approach
employs
a
multistep
approach.
Initially,
functionalities
were
identified
systematic
review
scholarly
works.
Subsequently,
social
network
analysis
(SNA)
Pareto
applied
evaluate
determine
importance
improving
them.
Findings
findings
highlight
multilevel
approaches
that
expand
address
all
combination
focuses
primarily
on
on-site
monitoring,
congested
work
sites,
site
layout/path
planning,
utility
problems,
training,
blind
spot
visibility.
Site
monitoring
warning
systems,
supported
sensors
computer
vision
(CV),
are
pivotal
identifying
enabling
data-driven
However,
workforce-level
cognitive
(W1-W6),
which
influence
behavior,
remain
underexplored
enhancing
functionality
anticipation
response
during
operation.
Prevention
is
function
solutions,
emphasizing
human
such
as
sources
hazards
operations.
Learning:
AI
IoT
systems
key
future
development,
when
grounded
ontology-based
knowledge
earthwork,
they
gain
structured
types,
interactions
earthwork
activities.
enhances
capabilities
these
capture
complex
between
hazard
(human
equipment),
supporting
comprehensive
Originality/value
elucidates
require
more
approach—grounded
understanding
technologies—to
effectively
Rasmussen
should
not
only
isolated
but
also
ensure
continuous
multiple
