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K
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MS
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s
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4
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5
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lin
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cle
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tifa
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wa
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d
er
in
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,
o
r
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ar
tif
ac
ts
[1
]
,
[
2]
.
B
esid
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th
at,
f
o
r
an
E
C
G
s
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n
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o
f
5
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f
r
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u
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f
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m
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to
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ar
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p
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m
ay
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s
u
p
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f
r
o
m
4
7
Hz
to
5
3
Hz
.
[
3
]
Fo
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th
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E
C
G
s
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th
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f
r
eq
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ca
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m
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[
4
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.
Me
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[2
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,
[
5]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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J
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Sci,
Vo
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3
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J
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2
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in
a
ce
r
tain
f
r
eq
u
en
cy
r
an
g
e
w
ith
in
th
e
b
an
d
s
to
p
f
ilter
(
b
an
d
-
r
ejec
t
f
ilter
)
.
I
t
h
as
two
b
an
d
s
an
d
a
s
to
p
b
an
d
in
it.
I
f
th
e
s
to
p
b
an
d
is
v
er
y
n
ar
r
o
w,
it
is
ca
lled
a
n
o
tch
f
ilter
.
T
h
e
tr
an
s
f
er
f
u
n
ctio
n
o
f
th
e
n
o
tch
is
s
h
o
wn
in
(
1
)
.
(
)
=
(
1
−
−
1
+
−
2
)
/
(
1
−
−
1
+
2
−
2
)
(
1
)
W
h
er
e
a
=
2
co
s
ω
,
an
d
r
<
|
1
|
.
T
h
e
p
ar
am
eter
r
d
eter
m
in
es
th
e
p
o
le
d
is
tan
ce
f
r
o
m
th
e
u
n
it
cir
cle
an
d
th
e
n
o
r
m
alize
d
b
a
n
d
wid
th
,
w
h
er
e
r
is
r
ev
er
s
ely
p
r
o
p
o
r
tio
n
al
to
th
e
r
ec
ip
r
o
ca
l
b
a
n
d
wid
th
o
f
th
e
n
o
tch
f
ilter
.
I
n
ad
d
itio
n
to
t
h
e
E
C
G
s
y
s
tem
,
n
o
tch
f
ilter
s
a
r
e
u
s
ed
in
v
ar
io
u
s
f
ield
s
in
clu
d
in
g
esti
m
atio
n
s
y
s
tem
s
[
1
0
]
,
[
1
1
]
.
Ad
ap
tiv
e
n
o
is
e
ca
n
ce
llatio
n
(
ANC)
i
s
an
alter
n
ate
ca
lcu
lati
o
n
m
eth
o
d
o
lo
g
y
f
o
r
n
o
is
e
o
r
i
n
ter
f
er
en
ce
in
a
c
o
r
r
u
p
ted
s
ig
n
al.
T
h
e
m
a
in
p
u
r
p
o
s
e
o
f
n
o
is
e
ca
n
ce
llatio
n
is
to
ass
ess
th
e
n
o
is
e
a
n
d
r
ed
u
ce
it
f
r
o
m
t
h
e
co
m
b
in
atio
n
o
f
th
e
o
r
ig
in
al
i
n
p
u
t
s
ig
n
al
an
d
t
h
e
n
o
is
e
s
ig
n
al
s
o
th
at
a
n
o
is
e
-
f
r
ee
s
ig
n
al
is
o
b
tain
ed
.
I
n
ad
ap
tiv
e
n
o
is
e
ca
n
ce
llatio
n
,
a
d
d
itio
n
al
n
o
is
e
is
g
iv
e
n
to
m
ea
s
u
r
e
th
e
d
am
ag
e
d
in
p
u
t
s
ig
n
al.
T
h
e
r
ef
e
r
en
ce
in
p
u
t
is
ad
ap
tiv
e
f
ilter
in
g
an
d
s
u
b
tr
ac
tio
n
f
r
o
m
t
h
e
m
ain
in
p
u
t
s
ig
n
al
to
o
b
tain
an
esti
m
ate
d
s
ig
n
al.
I
n
th
is
m
eth
o
d
,
th
e
d
esire
d
s
ig
n
al
(
wh
ich
is
d
am
ag
ed
b
y
an
ad
d
itio
n
al
n
o
is
e)
ca
n
b
e
r
ec
o
v
er
ed
u
s
in
g
a
ce
r
tain
alg
o
r
ith
m
.
[
1
2
]
,
[
1
3
]
Var
io
u
s
k
in
d
s
o
f
ad
a
p
tiv
e
alg
o
r
ith
m
s
a
r
e
u
s
ed
f
o
r
n
o
is
e
ca
n
ce
l
in
g
lik
e
least
m
ea
n
s
q
u
ar
e
(
L
MS)
,
n
o
r
m
alize
d
L
MS
(
NL
MS)
,
r
ec
u
r
s
iv
e
least
s
q
u
ar
e
(
R
L
S),
in
clu
d
in
g
in
te
r
f
er
en
ce
ca
n
ce
llatio
n
alg
o
r
ith
m
o
f
m
u
lti
-
s
tag
e
p
ar
tial
p
ar
allel
[
1
4
]
,
[
1
5
]
.
T
h
e
L
M
S
alg
o
r
ith
m
p
r
o
v
i
d
es
g
o
o
d
n
u
m
er
ical
s
tab
ilit
y
an
d
h
as
f
ew
h
ar
d
war
e
r
eq
u
ir
e
m
e
n
ts
,
h
o
wev
er
,
t
h
e
wea
k
n
ess
o
f
th
is
alg
o
r
ith
m
is
in
ter
m
s
o
f
co
n
v
e
r
g
en
ce
.
Me
an
wh
ile,
o
n
e
o
f
th
e
NL
MS
alg
o
r
ith
m
s
is
th
e
m
o
s
t
wid
el
y
u
s
ed
al
g
o
r
ith
m
s
in
tech
n
ical
f
ield
s
.
An
u
p
d
ate
d
v
er
s
io
n
o
f
th
e
r
eg
u
lar
L
MS
al
g
o
r
ith
m
is
th
e
NL
MS
alg
o
r
ith
m
.
Usi
n
g
th
e
f
o
llo
win
g
b
y
w
ay
o
f
th
e
th
eo
r
em
,
u
p
d
atin
g
th
e
co
ef
f
icien
ts
o
f
th
e
ad
ap
tiv
e
f
ilter
with
th
e
NL
MS
alg
o
r
ith
m
[
1
2
]
,
[
1
6
]
:
̅
(
+
1
)
=
̅
(
)
+
µ
(
)
̅
(
)
‖
̅
(
)
‖
2
(
2
)
T
h
at
m
ay
h
a
v
e
b
ee
n
wr
itten
as,
̅
(
+
1
)
=
̅
(
)
+
µ
(
)
(
)
̅
(
)
(
3
)
w
h
er
e
µ
(
)
=
µ
‖
̅
(
)
‖
2
(
4
)
I
n
th
e
ea
r
lier
eq
u
iv
alen
ce
,
th
e
alg
o
r
ith
m
o
f
NL
MS
is
s
im
i
la
r
to
th
e
r
eg
u
lar
L
MS
alg
o
r
ith
m
,
ex
ce
p
t
th
at
th
er
e
is
a
tim
e
-
v
ar
y
in
g
NL
MS
alg
o
r
ith
m
s
tep
s
ize
o
f
μ
(
n
)
.
T
h
e
s
tep
s
ize
μ
(
n
)
d
eter
m
in
es
th
e
s
p
ee
d
an
d
s
tab
ilit
y
o
f
th
e
ad
ap
tatio
n
.
T
h
e
ad
a
p
tiv
e
f
ilter
'
s
co
n
v
er
g
e
n
ce
s
p
ee
d
ca
n
b
e
e
n
h
an
ce
d
b
y
th
is
p
h
ase
s
ca
le.
C
o
m
p
ar
ed
to
th
e
alg
o
r
ith
m
f
o
r
L
MS,
th
e
alg
o
r
ith
m
o
f
NL
MS
is
a
th
eo
r
etica
lly
f
aster
c
o
n
v
er
g
in
g
alg
o
r
ith
m
,
wh
ich
ca
n
c
o
m
e
at
a
h
ig
h
er
r
esid
u
al
er
r
o
r
p
r
ice.
T
h
e
k
ey
d
o
wn
s
id
e
o
f
th
e
p
u
r
e
L
MS
alg
o
r
ith
m
is
th
at
it
is
v
u
ln
er
ab
le
to
its
I
n
p
u
t
x
x
s
ca
lin
g
(
n
)
.
T
h
is
m
ak
es
it
v
er
y
d
if
f
icu
lt
to
s
elec
t
a
μ
lear
n
in
g
r
ate
th
at
m
ain
tain
s
alg
o
r
ith
m
co
n
s
is
ten
cy
.
T
h
e
N
L
MS
is
a
m
o
d
if
ied
o
f
th
e
L
M
S
alg
o
r
ith
m
th
at
f
ix
es
th
is
tr
ic
k
y
b
y
n
o
r
m
alizin
g
th
e
in
p
u
t
p
o
wer
[
1
2
,
17]
.
Flo
wch
ar
t o
f
a
d
ap
tiv
e
f
ilter
in
g
alg
o
r
ith
m
as sh
o
wn
in
Fig
u
r
e
1
.
Hea
r
t
r
ate
f
r
eq
u
e
n
cy
is
v
er
y
r
elev
an
t
d
ata
f
o
r
h
ea
lth
s
tatu
s
.
I
n
ce
r
tain
m
e
d
ical
o
r
s
p
o
r
ts
u
s
es,
s
u
ch
as
s
tr
ess
ch
ec
k
s
o
r
life
ca
r
e
co
n
d
itio
n
esti
m
atio
n
,
th
e
f
r
eq
u
en
cy
ca
lcu
latio
n
is
u
s
ed
.
C
alcu
latin
g
it
f
r
o
m
t
h
e
s
ig
n
al
o
f
E
C
G
is
o
n
e
o
f
th
e
p
o
ten
tial
m
eth
o
d
s
o
f
ac
ce
s
s
in
g
h
ea
r
t
r
ate
f
r
eq
u
e
n
cy
.
T
h
e
elec
tr
o
ca
r
d
io
g
r
am
(
E
C
G)
r
ep
r
esen
ts
th
e
h
u
m
an
h
ea
r
t'
s
elec
tr
ical
f
u
n
ctio
n
.
T
h
e
E
C
G
co
n
s
is
t
s
o
f
f
iv
e
wav
es
-
P,
Q,
R
,
S,
an
d
T
.
T
h
is
s
ig
n
al
co
u
ld
b
e
ass
ess
ed
b
y
t
h
e
u
s
u
al
p
r
esen
ce
o
f
elec
tr
o
d
es
in
t
h
e
h
u
m
an
b
o
d
y
.
W
ith
am
p
lifie
r
s
an
d
an
alo
g
-
d
i
g
ital
co
n
v
er
ter
s
,
s
ig
n
als
f
r
o
m
th
ese
elec
tr
o
d
es
ar
e
ca
r
r
ied
in
to
b
asic
elec
tr
ic
al
cir
cu
its
.
Ma
n
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
A
n
a
p
p
r
o
a
ch
o
f a
d
a
p
tive
n
o
tch
filt
erin
g
d
esig
n
fo
r
elec
tr
o
ca
r
d
io
g
r
a
m
n
o
is
e
ca
n
ce
lla
tio
n
(
R
a
h
ma
d
Hid
a
ya
t
)
1305
m
eth
o
d
s
an
d
alg
o
r
ith
m
s
ca
n
d
etec
t
th
e
h
ea
r
t
r
ate
f
r
eq
u
en
cy
f
r
o
m
th
e
E
C
G
s
ig
n
al.
Ma
n
y
h
ea
r
t
r
ate
d
etec
tio
n
alg
o
r
ith
m
s
ar
e
b
ased
o
n
th
e
d
etec
tio
n
o
f
QR
S
co
m
p
lex
es,
a
n
d
h
ea
r
t
r
ate
is
m
ea
s
u
r
ed
as
t
h
e
in
ter
v
al
b
etwe
en
co
m
p
lex
es
o
f
QR
S.
Fo
r
ex
am
p
le,
th
e
co
m
p
lex
ity
o
f
QR
S
ca
n
b
e
d
ef
i
n
ed
u
s
in
g
ar
tifi
cial
n
eu
r
al
n
etwo
r
k
alg
o
r
ith
m
s
,
g
en
etic
alg
o
r
ith
m
s
,
wav
elet
tr
an
s
f
o
r
m
s
,
o
r
f
ilt
er
b
an
k
s
[
1
8
]
T
h
e
r
esu
lts
o
f
t
h
e
E
C
G
s
cr
ee
n
in
g
p
r
o
v
id
e
th
e
p
o
s
s
ib
ilit
y
o
f
an
al
y
zin
g
h
ea
r
t d
is
ea
s
e.
E
C
G
s
ig
n
al
as sh
o
wn
in
Fig
u
r
e
2
.
Fig
u
r
e
1
.
Flo
wch
ar
t
o
f
a
d
ap
tiv
e
f
ilter
in
g
alg
o
r
ith
m
Fig
u
r
e
2
.
E
C
G
s
ig
n
al
[
2
]
I
n
th
e
wo
r
k
o
f
[
1
9
]
,
a
d
ig
ital
FIR
f
ilter
is
d
ev
elo
p
e
d
a
n
d
a
p
p
lied
with
v
ar
io
u
s
win
d
o
win
g
tech
n
iq
u
es
s
u
ch
as
Ham
m
in
g
,
Kaiser
,
an
d
C
h
eb
y
s
h
ev
to
elim
in
ate
5
0
Hz
p
o
wer
lin
e
n
o
is
e
in
th
e
s
i
g
n
al
o
f
E
C
G.
T
h
e
ass
es
s
m
en
t in
th
e
MA
T
L
AB
s
ettin
g
was c
o
m
p
leted
.
C
o
m
p
a
r
in
g
th
e
wav
ef
o
r
m
s
o
f
th
e
in
iti
al
an
d
f
ilter
ed
E
C
G
s
ig
n
als
,
f
o
r
all
FIR
f
ilter
s
,
t
h
e
r
esu
lts
o
b
tain
ed
a
r
e
co
m
p
ar
ed
with
.
T
h
e
o
n
e
wh
o
u
s
es
th
e
C
h
eb
y
s
h
ev
win
d
o
w
is
th
e
f
ilter
th
at
p
r
o
v
id
es
th
e
b
est
r
esu
lts
.
Dete
ctio
n
,
esti
m
atio
n
,
an
d
f
ilter
in
g
o
f
t
h
e
d
es
ir
ed
s
ig
n
al
ag
ain
s
t
n
o
is
e
ar
e
s
o
m
e
o
f
th
e
m
o
s
t
c
o
m
m
o
n
m
et
h
o
d
s
.
T
h
e
tim
e
-
d
o
m
ain
an
aly
s
is
also
r
eq
u
ir
es
a
co
m
p
ar
is
o
n
o
f
two
di
s
tin
ct
s
ig
n
als
in
wh
ich
a
s
t
o
ch
asti
c
s
ig
n
al
is
u
s
u
ally
m
o
r
e
ad
v
an
tag
e
o
u
s
ly
an
aly
ze
d
i
n
th
e
tim
e
d
o
m
ain
.
T
h
r
o
u
g
h
ce
r
tain
im
p
lem
e
n
tatio
n
s
o
f
s
ig
n
al
p
r
o
ce
s
s
in
g
,
th
er
e
is
th
e
b
r
ea
k
d
o
wn
o
f
t
h
e
o
r
i
g
in
al
s
ig
n
al
in
to
th
e
f
u
n
d
am
e
n
tal
s
ig
n
al.
T
h
e
n
o
tch
ad
ap
tiv
e
f
ilt
er
ca
n
e
x
tr
ac
t
th
e
n
o
is
e
f
r
o
m
t
h
e
tar
g
et
s
ig
n
al.
An
o
th
er
way
t
o
r
ed
u
ce
n
o
is
e
ca
n
also
b
e
d
o
n
e
with
an
o
th
er
f
ilter
ca
lled
th
e
Kalm
an
f
ilter
[
2
0
]
.
Ma
n
e
a
n
d
Ag
ash
e
[
2
1
]
,
th
e
p
r
o
p
o
s
ed
n
o
tch
ad
a
p
tiv
e
f
ilter
is
co
n
n
ec
ted
in
p
ar
allel
to
ex
tr
ac
t
th
e
m
ajo
r
f
r
eq
u
e
n
cy
o
f
th
e
n
o
is
e
-
co
n
tam
in
ated
s
ig
n
al.
E
ac
h
f
ilt
er
is
ca
p
ab
le
o
f
d
ec
o
m
p
o
s
in
g
th
e
'
n
'
s
in
u
s
o
id
s
wh
ich
ar
e
h
ar
m
o
n
io
u
s
ly
r
elate
d
to
th
eir
co
n
s
titu
en
t c
o
m
p
o
n
en
t
s
.
Ver
m
a
an
d
Sin
g
h
[
2
2
]
p
r
o
p
o
s
ed
a
h
ig
h
-
p
er
f
o
r
m
a
n
ce
tu
n
e
ab
le
ad
ap
tiv
e
n
o
tc
h
f
ilter
alg
o
r
ith
m
f
o
r
esti
m
atin
g
th
e
ac
cu
r
ac
y
o
f
E
C
G
s
ig
n
als.
Usi
n
g
th
e
p
r
o
p
o
s
ed
n
o
tch
ad
ap
tiv
e
f
ilter
with
FIR
tu
n
ab
le
n
o
tch
f
r
eq
u
e
n
cies,
an
in
ter
f
er
en
ce
o
f
elec
tr
ical
wir
e
an
d
th
e
n
o
is
e
o
f
m
u
s
cle
co
n
tr
ac
tio
n
is
g
r
ea
tly
s
u
p
p
r
ess
ed
.
T
h
e
co
n
s
er
v
atio
n
o
f
s
elec
tiv
ity
an
d
atten
u
atio
n
at
n
o
tch
f
r
e
q
u
en
cies
is
a
n
es
s
en
tial
f
ea
tu
r
e
o
f
th
e
s
u
g
g
ested
f
ilter
s
ch
em
e.
T
h
e
f
ilter
s
ar
e
o
p
tim
ized
an
d
th
eir
co
ef
f
icien
ts
ar
e
ca
lcu
lated
s
u
ch
th
at
n
o
is
e
in
t
h
e
s
ig
n
al
o
f
E
C
G
i
s
m
in
im
ized
with
in
t
h
e
s
p
ec
if
i
ed
f
r
e
q
u
en
c
y
r
a
n
g
e.
T
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
esti
m
ates
th
e
f
r
eq
u
en
cy
o
f
th
e
u
n
wan
ted
s
ig
n
al
an
d
u
p
d
ate
s
th
e
f
ilter
c
o
n
s
is
ten
t
with
th
e
f
ilter
co
ef
f
icien
t
f
o
r
o
p
t
im
al
p
er
f
o
r
m
an
ce
.
Desig
n
in
g
an
E
C
G
m
ac
h
in
e
u
s
in
g
AT
m
eg
a
m
icr
o
c
o
n
tr
o
ller
tech
n
o
lo
g
y
h
as
b
ee
n
ca
r
r
ied
o
u
t
in
a
s
tu
d
y
[
2
3
]
wh
er
e
th
e
er
r
o
r
r
ate
is
s
till
b
elo
w
th
e
m
ax
im
u
m
allo
wab
le
th
r
esh
o
ld
.
C
o
m
p
u
ter
s
im
u
latio
n
s
b
ased
o
n
d
ig
ital
eq
u
iv
ale
n
ts
ar
e
a
f
ea
s
ib
le
an
d
r
ea
l
an
s
wer
f
o
r
th
e
a
cq
u
is
itio
n
an
d
e
x
tr
ac
tio
n
o
f
h
u
m
a
n
b
io
-
s
ig
n
als
wh
ich
ar
e
v
er
y
s
en
s
itiv
e
to
i
n
ter
f
er
e
n
ce
.
B
u
t
t
h
ese
d
ig
ital
f
ilter
s
a
r
e
m
o
s
tly
v
er
if
ied
o
n
s
to
r
ed
d
atab
ases
s
o
th
er
e
is
a
n
ee
d
to
im
p
r
o
v
e
th
e
ac
q
u
ir
ed
s
y
s
tem
in
r
ea
l
-
tim
e.
R
esear
ch
[
2
4
]
d
ea
ls
with
th
e
d
esig
n
an
d
s
im
u
latio
n
o
f
I
I
R
n
o
tch
f
ilter
s
f
o
r
im
p
lem
e
n
tatio
n
o
n
r
ea
l
-
tim
e,
n
o
n
-
in
v
as
iv
e
ac
q
u
ir
e
d
ca
r
o
tid
p
u
l
s
e
wav
es
with
Simu
lin
k
a
n
d
th
e
FDA
T
o
o
l.
T
o
a
n
aly
ze
a
n
E
C
G
s
ig
n
al
with
d
if
f
er
en
t
f
r
eq
u
en
cy
co
m
p
o
n
en
ts
,
a
wav
elet
-
d
ec
o
m
p
o
s
itio
n
-
f
ilter
r
ec
o
n
s
tr
u
ctio
n
(
W
DFR
)
alg
o
r
ith
m
is
em
p
lo
y
ed
in
[
2
5
]
.
T
h
e
alg
o
r
it
h
m
was
ap
p
lied
f
o
r
elim
in
atin
g
n
o
is
e
an
d
ar
tifa
ct
co
m
p
o
n
e
n
ts
in
E
C
G
s
ig
n
als.
T
h
e
NL
MS
alg
o
r
ith
m
h
as
b
ee
n
s
im
u
lated
in
[
2
0
]
th
at
NL
MS
h
as
ad
v
an
tag
es
in
ter
m
s
o
f
m
ea
n
s
q
u
ar
e
er
r
o
r
(
MSE
)
co
m
p
ar
ed
t
o
th
e
L
M
S
an
d
R
L
S
alg
o
r
ith
m
s
[
2
6
]
.
F
o
r
s
im
u
latio
n
p
u
r
p
o
s
es,
ad
d
iti
v
e
wh
ite
Gau
s
s
ian
n
o
is
e
is
ad
d
e
d
to
th
e
in
f
o
r
m
at
io
n
s
ig
n
al
g
en
er
ated
r
an
d
o
m
l
y
an
d
ef
f
icien
tly
r
ed
u
ce
s
n
o
is
e
with
m
in
im
u
m
o
r
n
o
e
r
r
o
r
s
,
an
d
th
e
NL
MS
alg
o
r
ith
m
is
u
s
ed
to
r
ea
c
h
t
h
e
d
e
s
ir
ed
r
esu
lt
as
is
d
o
n
e
in
[
2
7
]
an
d
[
1
2
]
.
Als
o
,
th
e
n
o
is
e
ca
n
ce
llatio
n
e
f
f
icien
cy
o
f
th
e
NL
MS
was
co
n
s
is
ten
tly
h
ig
h
er
c
o
m
p
ar
e
d
to
th
e
E
C
G
s
ig
n
al
ANC
L
MS
alg
o
r
ith
m
.
[
3
]
NL
MS
was
als
o
u
s
ed
in
r
esear
ch
[
2
8
]
as
a
c
o
n
tin
u
atio
n
o
f
th
e
ad
a
p
tiv
e
li
n
e
en
h
a
n
ce
r
(
AL
E
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
22
,
No
.
3
,
J
u
n
e
2
0
2
1
:
1
3
0
3
-
1
3
1
1
1306
f
ilter
s
f
o
r
th
e
ad
ap
tiv
e
n
o
is
e
ca
n
ce
llatio
n
s
ch
em
e.
T
o
a
v
o
i
d
m
an
u
al
ca
lcu
latio
n
o
f
PQR
ST
p
ea
k
am
p
litu
d
e
v
alu
es,
th
e
s
o
f
twar
e
d
esig
n
ed
in
[
2
9
]
h
as
b
ee
n
a
b
le
to
r
ep
r
e
s
en
t
th
e
PQR
ST
an
d
ca
r
d
io
g
r
am
p
ea
k
am
p
litu
d
e
v
alu
es
f
o
r
ea
c
h
cy
cle
o
n
ea
c
h
elec
tr
o
ca
r
d
io
g
r
am
lead
.
T
h
e
r
esu
lts
o
f
th
e
co
n
tin
u
o
u
s
s
ig
n
al
elec
tr
o
ca
r
d
io
g
r
am
(
E
C
G)
ex
am
in
atio
n
wer
e
s
am
p
led
at
a
ce
r
tain
f
r
eq
u
en
cy
t
o
o
b
tain
d
is
cr
ete
d
ata
wh
ich
is
t
h
e
am
p
litu
d
e
as
a
f
u
n
ctio
n
o
f
i
n
teg
er
(
N
)
.
Ad
ap
t
iv
e
f
ilter
esti
m
atio
n
o
f
an
AN
C
ca
n
b
e
d
o
n
e
u
s
in
g
MA
T
L
AB
an
d
/o
r
Simu
lin
k
.
Fo
r
th
is
r
ea
s
o
n
,
th
e
MA
T
L
A
B
s
o
f
twar
e
wa
s
u
s
ed
in
th
e
s
t
u
d
y
o
f
[
3
0
]
to
ef
f
icien
tly
d
ete
ct
an
y
ab
n
o
r
m
alities
ex
is
tin
g
in
th
e
E
C
G
s
ig
n
al.
T
h
e
d
etec
tio
n
o
f
s
u
ch
ab
n
o
r
m
alities
r
ef
er
s
to
th
e
P,
Q,
R
,
an
d
S
p
ea
k
s
o
f
th
e
E
C
G
s
ig
n
al.
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
s
im
u
latio
n
p
ar
am
ete
r
s
o
f
th
is
s
tu
d
y
,
b
o
th
f
o
r
th
e
n
o
tch
f
ilter
d
esig
n
an
d
f
o
r
th
e
s
im
u
l
in
k
b
lo
ck
,
ar
e
lis
ted
in
T
ab
le
1
.
T
h
e
alg
o
r
ith
m
th
at
we
u
s
e
is
s
h
o
wn
in
Fig
u
r
e
3
.
W
h
ile
th
e
n
o
tch
s
im
u
lati
on
co
n
f
ig
u
r
atio
n
ar
e
s
h
o
wn
in
Fig
u
r
e
4
.
T
h
e
s
im
u
latio
n
is
also
co
m
p
lem
en
ted
b
y
u
s
in
g
t
h
e
M
AT
L
AB
s
cr
ip
t w
ith
3
2
f
ilter
tap
s
.
T
ab
le
1
.
T
h
e
s
im
u
latio
n
p
a
r
a
m
eter
s
F
i
l
t
e
r
D
e
s
i
g
n
(
F
D
A
To
o
l
)
S
i
mu
l
i
n
k
F
i
l
t
e
r
d
e
si
g
n
e
d
:
F
r
e
q
u
e
n
c
y
:
Ty
p
e
:
S
t
r
u
c
t
u
r
e
:
O
r
d
e
r
:
BW
3dB
:
A
pa
s
s
:
S
a
mp
l
i
n
g
f
r
e
q
u
e
n
c
y
:
N
o
t
c
h
4
7
H
z
I
I
R
D
i
r
e
c
t
f
o
r
m I
I
S
e
c
o
n
d
o
r
d
e
r
8
0
H
z
1
d
B
3
6
0
H
z
S
i
n
e
w
a
v
e
:
a
mp
l
i
t
u
d
e
:
f
r
e
q
u
e
n
c
y
:
p
h
a
se
o
f
f
se
t
:
samp
l
e
mo
d
e
:
samp
l
e
p
e
r
f
r
a
me
:
N
o
i
se
s
o
u
r
c
e
:
t
y
p
e
:
mea
n
:
v
a
r
i
a
n
c
e
:
t
h
e
i
n
i
t
i
a
l
se
e
d
:
samp
l
e
mo
d
e
:
S
N
LM
S
f
i
l
t
e
r
:
a
l
g
o
r
i
t
h
m:
f
i
l
t
e
r
l
e
n
g
t
h
:
S
a
mp
l
e
t
i
m
e
:
S
o
l
v
e
r
s
i
m
u
l
a
t
i
o
n
:
D
u
r
a
t
i
o
n
:
1
v
o
l
t
5
0
H
z
0
r
a
d
d
i
s
c
r
e
t
e
1
G
a
u
ss
i
a
n
(
Zi
g
g
u
r
a
t
)
0
1
[
2
3
3
4
1
]
d
i
s
c
r
e
t
e
N
o
r
mal
i
z
e
d
L
M
S
32
1
/
3
6
0
s
f
i
x
e
d
-
st
e
p
w
i
t
h
d
i
scre
t
e
(
n
o
c
o
n
t
i
n
u
o
u
s s
t
a
t
e
s)
6
0
0
s
e
c
o
n
d
s
Fig
u
r
e
3
.
NL
MS
alg
o
r
ith
m
f
lo
wch
ar
t [
3
]
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
A
n
a
p
p
r
o
a
ch
o
f a
d
a
p
tive
n
o
tch
filt
erin
g
d
esig
n
fo
r
elec
tr
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o
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u
r
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4
.
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h
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s
im
u
lin
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3.
RE
SU
L
T
S
A
ND
D
IS
CU
SS
I
O
N
3
.
1
.
F
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r
des
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n r
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lt
Acc
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ilter
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ilib
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r
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cir
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n
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f
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p
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u
r
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elate
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ely
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r
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5
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r
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5
.
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tc
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ely
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r
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r
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h
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th
e
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o
is
e
f
ilter
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n
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ig
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t
s
im
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=3
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CO
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ith
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im
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t
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alize
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n
s
q
u
ar
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(
NL
MS)
ad
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tiv
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ilter
.
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o
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ate
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is
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r
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th
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n
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in
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is
ch
o
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en
.
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o
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,
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ts
o
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ize
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co
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e
n
ce
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ate
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d
s
tab
ilit
y
f
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a
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e
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n
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d
.
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h
e
r
esu
lts
s
h
o
wed
th
at
th
e
f
ilter
d
esig
n
ed
was
ab
le
to
ad
ap
t to
c
h
an
g
es in
f
r
eq
u
en
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an
d
r
esp
o
n
s
e
ac
co
r
d
in
g
l
y
.
RE
F
E
R
E
NC
E
S
[1
]
S
.
El
o
u
a
h
a
m
,
A.
Dlio
u
,
M
.
Laa
b
o
u
b
i,
R
.
Latif,
N.
El
k
a
m
o
u
n
,
a
n
d
H.
Zo
u
g
a
g
h
,
"
F
il
terin
g
a
n
d
a
n
a
l
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z
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l
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n
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a
b
n
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rm
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lec
tro
m
y
o
g
ra
m
sig
n
a
l
s,"
In
d
o
n
e
s.
J
.
E
lec
tr.
En
g
.
C
o
m
p
u
t.
S
c
i.
,
v
o
l.
2
0
,
n
o
.
1
,
p
p
.
1
7
6
-
1
8
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,
2
0
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d
o
i:
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0
.
1
1
5
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/i
jee
c
s.v
2
0
.
i
1
.
p
p
1
7
6
-
1
8
4
.
[2
]
M
.
G
a
c
h
a
k
e
,
G
.
G
a
wa
n
d
e
,
a
n
d
K.
Kh
a
n
c
h
a
n
d
a
n
i,
"
P
e
rfo
rm
a
n
c
e
Co
m
p
a
riso
n
o
f
Va
rio
u
s
Di
g
it
a
l
F
il
ters
f
o
r
El
imin
a
ti
o
n
o
f
P
o
we
r
Li
n
e
In
terfe
re
n
c
e
fro
m
ECG
S
ig
n
a
l,
"
In
t.
J
.
C
u
rr
.
En
g
.
T
e
c
h
n
o
l.
,
v
o
l.
4
,
n
o
.
3
,
p
p
.
1
2
5
5
-
1
2
5
9
,
2
0
1
4
.
[3
]
H.
K
.
G
u
p
ta,
R.
Vijay
,
a
n
d
N.
Gu
p
ta,
"
De
sig
n
in
g
a
n
d
Im
p
lem
e
n
tatio
n
o
f
Al
g
o
ri
th
m
s
o
n
M
AT
LA
B
fo
r
Ad
a
p
ti
v
e
No
ise
Ca
n
c
e
ll
a
ti
o
n
fro
m
ECG
S
i
g
n
a
l,
"
In
t
.
J
.
C
o
mp
u
t.
Ap
p
l.
,
v
o
l.
7
1
,
n
o
.
5
,
p
p
.
1
-
8
,
2
0
1
3
,
d
o
i
:
1
0
.
5
1
2
0
/1
2
3
5
1
-
8
6
5
2
.
[4
]
C
.
B.
M
b
a
c
h
u
a
n
d
K.
J.
Offo
r,
"
Re
d
u
c
ti
o
n
o
f
P
o
we
rli
n
e
N
o
ise
i
n
Ecg
S
i
g
n
a
l
Us
in
g
F
ir
Dig
i
tal
F
il
t
e
r
Im
p
lem
e
n
ted
Wi
th
Ha
m
m
in
g
Wi
n
d
o
w,
"
I
n
t.
J
.
S
c
i.
E
n
v
iro
n
.
T
e
c
h
n
o
l.
,
v
o
l.
2
,
n
o
.
6
,
p
p
.
1
3
8
0
-
1
3
8
7
,
2
0
1
3
.
[5
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3
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.
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7
]
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.
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. M. M.
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.
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