IEEE Journal of Biomedical and Health Informatics,
Journal Year:
2024,
Volume and Issue:
28(7), P. 3882 - 3894
Published: April 30, 2024
Biosignals
collected
by
wearable
devices,
such
as
electrocardiogram
and
photoplethysmogram,
exhibit
redundancy
global
temporal
dependencies,
posing
a
challenge
in
extracting
discriminative
features
for
blood
pressure
(BP)
estimation.
To
address
this
challenge,
we
propose
HGCTNet,
handcrafted
feature-guided
CNN
transformer
network
cuffless
BP
measurement
based
on
devices.
By
leveraging
convolutional
operations
self-attention
mechanisms,
design
CNN-Transformer
hybrid
architecture
to
learn
from
biosignals
that
capture
both
local
information
dependencies.
Then,
introduce
attention
module
utilizes
extracted
query
vectors
eliminate
redundant
within
the
learned
features.
Finally,
feature
fusion
integrates
features,
demographics
enhance
model
performance.
We
validate
our
approach
using
two
large
datasets:
CAS-BP
dataset
Aurora-BP
dataset.
Experimental
results
demonstrate
HGCTNet
achieves
an
estimation
error
of
0.9
$\pm$
6.5
mmHg
diastolic
(DBP)
0.7
8.3
systolic
(SBP)
On
dataset,
corresponding
errors
are
notation="LaTeX">$-$
0.4
7.0
DBP
8.6
SBP.
Compared
current
state-of-the-art
approaches,
reduces
mean
absolute
SBP
10.68%
9.84%
These
highlight
potential
improving
performance
measurements.
The
source
code
available
at
https://github.com/zdzdliu/HGCTNet.
Advanced Materials,
Journal Year:
2022,
Volume and Issue:
34(16)
Published: March 14, 2022
Piezoelectric
arterial
pulse
wave
dynamics
are
traditionally
considered
to
be
similar
those
of
typical
blood
pressure
waves.
However,
achieving
accurate
continuous
monitoring
based
on
waves
remains
challenging,
because
the
correlation
between
piezoelectric
and
their
related
is
unclear.
To
address
this,
first
elucidated
via
theoretical,
simulation,
experimental
analysis
these
dynamics.
Based
this
correlation,
authors
develop
a
wireless
wearable
system,
with
better
portability
than
conventional
systems
that
velocity
multiple
sensors.
They
explore
feasibility
without
motion
artifacts,
using
single
sensor.
These
findings
eliminate
controversy
over
response,
can
potentially
used
portable
device
for
early
prevention
daily
control
hypertension.
Journal of Hypertension,
Journal Year:
2022,
Volume and Issue:
40(8), P. 1449 - 1460
Published: June 16, 2022
Background:
Many
cuffless
blood
pressure
(BP)
measuring
devices
are
currently
on
the
market
claiming
that
they
provide
accurate
BP
measurements.
These
technologies
have
considerable
potential
to
improve
awareness,
treatment,
and
management
of
hypertension.
However,
recent
guidelines
by
European
Society
Hypertension
do
not
recommend
for
diagnosis
Objective:
This
statement
Working
Group
Monitoring
Cardiovascular
Variability
presents
types
technologies,
issues
in
their
validation,
recommendations
clinical
practice.
Statements:
Cuffless
monitors
constitute
a
wide
heterogeneous
group
novel
with
different
intended
uses.
specific
accuracy
issues,
which
render
established
validation
protocols
cuff
inadequate
validation.
In
2014,
Institute
Electrical
Electronics
Engineers
published
standard
devices,
International
Organization
Standardization
is
developing
another
standard.
The
should
address
related
need
individual
calibration,
stability
measurements
post
ability
track
changes,
implementation
machine
learning
technology.
Clinical
field
investigations
may
also
be
considered
regarding
readings
investigated.
Conclusion:
changing
fundamental
questions
accuracy,
performance,
carefully
addressed
before
can
recommended
use.
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: Aug. 17, 2023
Continuous
monitoring
of
arterial
blood
pressure
(BP)
outside
a
clinical
setting
is
crucial
for
preventing
and
diagnosing
hypertension
related
diseases.
However,
current
continuous
BP
instruments
suffer
from
either
bulky
systems
or
poor
user-device
interfacial
performance,
hampering
their
applications
in
monitoring.
Here,
we
report
thin,
soft,
miniaturized
system
(TSMS)
that
combines
conformal
piezoelectric
sensor
array,
an
active
adaptation
unit,
signal
processing
module,
advanced
machine
learning
method,
to
allow
real
wearable,
wireless
ambulatory
artery
BP.
By
optimizing
the
materials
selection,
control/sampling
strategy,
integration,
TSMS
exhibits
improved
performance
while
maintaining
Grade
A
level
measurement
accuracy.
Initial
trials
on
87
volunteers
tracking
two
individuals
prove
capability
as
reliable
product,
its
feasibility
practical
usability
precise
control
personalized
diagnosis
schemes
development.
Annual Review of Biomedical Engineering,
Journal Year:
2022,
Volume and Issue:
24(1), P. 203 - 230
Published: April 1, 2022
Cuffless
blood
pressure
(BP)
measurement
has
become
a
popular
field
due
to
clinical
need
and
technological
opportunity.
However,
no
method
been
broadly
accepted
hitherto.
The
objective
of
this
review
is
accelerate
progress
in
the
development
application
cuffless
BP
methods.
We
begin
by
describing
principles
conventional
measurement,
outstanding
hypertension/hypotension
problems
that
could
be
addressed
with
methods,
recent
advances,
including
smartphone
proliferation
wearable
sensing,
are
driving
field.
then
present
all
major
methods
under
investigation,
their
current
evidence.
Our
presentation
includes
calibrated
(i.e.,
pulse
transit
time,
wave
analysis,
facial
video
processing)
uncalibrated
oscillometry,
ultrasound,
volume
control).
can
offer
convenience
advantages,
whereas
do
not
require
periodic
cuff
device
usage
or
demographic
inputs.
conclude
summarizing
highlighting
potentially
useful
future
research
directions.
Sensors,
Journal Year:
2023,
Volume and Issue:
23(5), P. 2479 - 2479
Published: Feb. 23, 2023
Smart
wearable
systems
for
health
monitoring
are
highly
desired
in
personal
wisdom
medicine
and
telemedicine.
These
make
the
detecting,
monitoring,
recording
of
biosignals
portable,
long-term,
comfortable.
The
development
optimization
health-monitoring
have
focused
on
advanced
materials
system
integration,
number
high-performance
has
been
gradually
increasing
recent
years.
However,
there
still
many
challenges
these
fields,
such
as
balancing
trade-off
between
flexibility/stretchability,
sensing
performance,
robustness
systems.
For
this
reason,
more
evolution
is
required
to
promote
In
regard,
review
summarizes
some
representative
achievements
progress
monitoring.
Meanwhile,
a
strategy
overview
presented
about
selecting
materials,
integrating
systems,
biosignals.
next
generation
accurate,
continuous,
long-term
will
offer
opportunities
disease
diagnosis
treatment.
Journal of Hypertension,
Journal Year:
2023,
Volume and Issue:
41(12), P. 2074 - 2087
Published: June 12, 2023
There
is
intense
effort
to
develop
cuffless
blood
pressure
(BP)
measuring
devices,
and
several
are
already
on
the
market
claiming
that
they
provide
accurate
measurements.
These
devices
heterogeneous
in
measurement
principle,
intended
use,
functions,
calibration,
have
special
accuracy
issues
requiring
different
validation
than
classic
cuff
BP
monitors.
To
date,
there
no
generally
accepted
protocols
for
their
ensure
adequate
clinical
use.This
statement
by
European
Society
of
Hypertension
(ESH)
Working
Group
Monitoring
Cardiovascular
Variability
recommends
procedures
validating
intermittent
(providing
measurements
every
>30
sec
usually
30-60
min,
or
upon
user
initiation),
which
most
common.Six
tests
defined
evaluating
aspects
devices:
static
test
(absolute
accuracy);
device
position
(hydrostatic
effect
robustness);
treatment
(BP
decrease
awake/asleep
change
exercise
increase
recalibration
(cuff
calibration
stability
over
time).
Not
all
these
required
a
given
device.
The
necessary
depend
whether
requires
individual
measures
automatically
manually,
takes
more
one
position.The
complex
needs
be
tailored
according
functions
calibration.
ESH
recommendations
present
specific,
clinically
meaningful,
pragmatic
types
only
will
used
evaluation
management
hypertension.
npj Digital Medicine,
Journal Year:
2023,
Volume and Issue:
6(1)
Published: March 30, 2023
Smart
rings
provide
unique
opportunities
for
continuous
physiological
measurement.
They
are
easy
to
wear,
little
burden
in
comparison
other
smart
wearables,
suitable
nocturnal
settings,
and
can
be
sized
ideal
contact
between
the
sensors
skin
at
all
times.
Continuous
measuring
of
blood
pressure
(BP)
provides
essential
diagnostic
prognostic
value
cardiovascular
health
management.
However,
conventional
ambulatory
BP
measurement
devices
operate
using
an
inflating
cuff
that
is
bulky,
intrusive,
impractical
frequent
or
measurements.
We
introduce
ring-shaped
bioimpedance
leveraging
deep
tissue
sensing
ability
while
introducing
no
sensitivity
tones,
unlike
optical
modalities.
integrate
human
finger
finite
element
model
with
exhaustive
experimental
data
from
participants
derive
optimum
design
parameters
electrode
placement
sizes
yields
highest
arterial
volumetric
changes,
discrimination
against
varying
tones.
constructed
machine
learning
algorithms.
The
ring
used
estimate
showing
peak
correlations
0.81,
low
error
(systolic
BP:
0.11
±
5.27
mmHg,
diastolic
3.87
mmHg)
>2000
points
wide
ranges
(systolic:
89-213
mmHg
diastolic:
42-122
mmHg),
highlighting
significant
potential
use
accurate
estimation
BP.
Biomedical Signal Processing and Control,
Journal Year:
2021,
Volume and Issue:
68, P. 102813 - 102813
Published: June 1, 2021
The
use
of
machine
learning
techniques
in
medicine
has
increased
recent
years
due
to
a
rise
publicly
available
datasets.
These
have
been
applied
high
blood
pressure
studies
following
two
approaches:
hypertension
stage
classification
based
on
clinical
data
and
estimation
related
physiological
signals.
This
paper
presents
literature
review
such
studies.
We
aimed
identify
the
best
practices,
challenges,
opportunities
developing
models
detect
or
estimate
using
Hence,
we
identified
examined
techniques,
datasets,
predictors
used
previous
feature
selection
reduce
model
complexity
are
also
reviewed.
found
lack
combining
socio-demographic
with
signals,
despite
correlation
photoplethysmography
waveforms
variables
as
age,
gender,
body
mass
index,
heart
rate.
Therefore,
there
is
an
opportunity
increase
performance
by
both
types
for
detection
monitoring.