Information Fusion,
Год журнала:
2023,
Номер
103, С. 102124 - 102124
Опубликована: Ноя. 4, 2023
The
importance
of
Fetal
Movement
(FM)
patterns
as
a
biomarker
for
fetal
health
has
been
extensively
argued
in
obstetrics.
However,
the
inability
current
FM
monitoring
methods,
such
ultrasonography,
to
be
used
outside
clinical
environments
made
it
challenging
understand
nature
and
evolution
FM.
A
small
body
work
introduced
wearable
sensor-based
monitors
address
this
gap.
Despite
promises
controlled
environments,
reliable
instrumentation
monitor
out-of-clinic
remains
unresolved,
particularly
due
challenges
separating
FMs
from
interfering
artifacts
arising
maternal
activities.
To
date,
efforts
have
focused
almost
exclusively
on
homogenous
(single)
sensing
information
fusion
modalities,
decoupled
acoustic
or
accelerometer
sensors.
related
signal
varying
power
frequency
bandwidths
that
homogeneous
sensor
arrays
may
not
capture
separate
efficiently.
In
investigation,
we
introduce
novel
with
an
embedded
heterogeneous
suite
combining
accelerometers,
sensors,
piezoelectric
diaphragms
designed
broad
range
artifact
features
enabling
more
efficient
isolation
both.
We
further
outline
data
architecture
data-dependent
thresholding
machine
learning
automatically
detect
real-world
(home)
environments.
performance
device
are
validated
using
33
hours
at-home
use
through
concurrent
recording
perception
detected
impressive
82%
maternally
sensed
overall
accuracy
90%
detecting
non-FM
events.
Reliability
detection
was
strongest
32
gestational
weeks
onwards,
which
overlaps
critical
window
stillbirth
prevention.
believe
multi-modal
approach
presented
research
will
major
milestone
development
low-cost
pervasive
unsupervised
Information Fusion,
Год журнала:
2023,
Номер
103, С. 102136 - 102136
Опубликована: Ноя. 10, 2023
Advancements
in
structural
health
monitoring
(SHM)
techniques
have
spiked
the
past
few
decades
due
to
rapid
evolution
of
novel
sensing
and
data
transfer
technologies.
This
development
has
facilitated
simultaneous
recording
a
wide
range
data,
which
could
contain
abundant
damage-related
features.
Concurrently,
age
omnipresent
started
with
massive
amounts
SHM
collected
from
large-size
heterogeneous
sensor
networks.
The
abundance
information
diverse
sources
needs
be
aggregated
enable
robust
decision-making
strategies.
Data
fusion
is
process
integrating
various
produce
more
useful,
accurate,
reliable
about
system
behavior.
paper
reviews
recent
developments
applied
systems.
theoretical
concepts,
applications,
benefits,
limitations
current
methods
challenges
are
presented,
future
trends
discussed.
Furthermore,
set
criteria
proposed
evaluate
contents
original
review
papers
this
field,
road
map
provided
discussing
possible
work.
Abstract
Layered
double
hydroxides
(LDHs)
have
been
widely
studied
for
biomedical
applications
due
to
their
excellent
properties,
such
as
good
biocompatibility,
degradability,
interlayer
ion
exchangeability,
high
loading
capacity,
pH‐responsive
release,
and
large
specific
surface
area.
Furthermore,
the
flexibility
in
structural
composition
ease
of
modification
LDHs
makes
it
possible
develop
specifically
functionalized
meet
needs
different
applications.
In
this
review,
recent
advances
applications,
which
include
LDH‐based
drug
delivery
systems,
cancer
diagnosis
therapy,
tissue
engineering,
coatings,
functional
membranes,
biosensors,
are
comprehensively
discussed.
From
these
various
research
fields,
can
be
seen
that
there
is
great
potential
possibility
use
However,
at
same
time,
must
recognized
actual
clinical
translation
still
very
limited.
Therefore,
current
limitations
related
on
discussed
by
combining
limited
examples
with
requirements
biomaterials.
Finally,
an
outlook
future
provided.
Nature Communications,
Год журнала:
2024,
Номер
15(1)
Опубликована: Фев. 26, 2024
Abstract
Most
wearable
robots
such
as
exoskeletons
and
prostheses
can
operate
with
dexterity,
while
wearers
do
not
perceive
them
part
of
their
bodies.
In
this
perspective,
we
contend
that
integrating
environmental,
physiological,
physical
information
through
multi-modal
fusion,
incorporating
human-in-the-loop
control,
utilizing
neuromuscular
interface,
employing
flexible
electronics,
acquiring
processing
human-robot
biomechatronic
chips,
should
all
be
leveraged
towards
building
the
next
generation
robots.
These
technologies
could
improve
embodiment
With
optimizations
in
mechanical
structure
clinical
training,
better
facilitate
human
motor
sensory
reconstruction
enhancement.
Information Fusion,
Год журнала:
2022,
Номер
91, С. 694 - 712
Опубликована: Ноя. 7, 2022
With
the
rapid
development
of
Mobile
Internet
and
Industrial
Things,
a
variety
applications
put
forward
an
urgent
demand
for
user
device
identity
recognition.
Digital
with
hidden
characteristics
is
essential
both
individual
users
physical
devices.
assistance
multimodalities
as
well
fusion
strategies,
recognition
can
be
more
reliable
robust.
In
this
survey,
we
turn
to
investigate
concepts
limitations
unimodal
recognition,
motivation,
advantages
multimodal
summarize
technologies
via
feature
level,
match
score
decision
rank
level
data
strategies.
Additionally,
also
discuss
security
concerns
future
research
orientations
learning-based
which
enables
researchers
achieve
better
understanding
current
status
field
select
directions.
This
survey
summarizes
expands
processing
methods
multi-source
multimodality
data,
provides
theoretical
support
their
in
complicated
scenarios.
addition,
it
proper
•
User
by
leveraging
physiological
behavioral
biometrics.
Device
fingerprint.
Multi-modality
strategies
combining
multi-level
semantic
information.
Security
work
towards
