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[
1
4
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1
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[
1
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1
3
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2
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[
7
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Fig
u
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4
.
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en
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o
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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
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SS
N:
2502
-
4
7
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u
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2
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−
Featu
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:
Featu
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th
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m
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(
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,
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Fig
u
r
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6
.
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
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4
7
5
2
I
n
d
o
n
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J
E
lec
E
n
g
&
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p
Sci,
Vo
l.
23
,
No
.
2
,
Au
g
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s
t
20
21
:
1
1
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1184
−
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t f
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e
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s
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in
th
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in
d
o
f
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tu
d
y
[
2
3
]
,
[
2
4
]
.
2
.
3
.
Cla
s
s
if
ier
T
h
e
class
if
icatio
n
is
th
e
f
in
al
s
tag
e
o
f
p
atter
n
r
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o
g
n
itio
n
.
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h
e
class
if
ier
m
u
s
t
b
e
tr
ain
ed
with
a
s
et
o
f
tr
ain
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n
g
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tu
r
es
an
d
test
it
with
test
in
g
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tu
r
es
th
en
m
ak
e
a
co
m
p
ar
is
o
n
b
etwe
en
th
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a
ctu
al
an
d
p
r
e
d
icted
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es
to
m
ak
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ju
d
g
m
en
t
o
n
th
e
s
y
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tem
r
esp
o
n
s
e.
T
h
e
class
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ier
h
as
u
s
ed
in
th
is
s
tu
d
y
is
th
e
SV
M
class
if
ier
.
T
h
e
s
u
p
p
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t
v
ec
to
r
m
ac
h
in
e
ca
n
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lin
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n
-
lin
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r
class
if
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n
th
at
h
as
b
ee
n
u
s
ed
to
class
if
y
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o
n
-
lin
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r
ca
teg
o
r
ies.
T
h
is
class
if
ier
im
p
lem
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ts
c
lass
if
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n
b
y
p
r
ed
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g
th
e
b
est
h
y
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-
p
la
n
e,
wh
ich
s
ep
ar
ates
th
e
class
d
at
a
f
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o
m
o
th
er
class
es.
A
b
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y
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p
la
n
ca
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e
f
o
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n
d
b
y
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in
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n
g
a
g
r
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ter
m
ar
g
in
b
etwe
en
th
e
two
class
es.
T
h
e
m
ax
im
al
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th
o
f
th
e
p
lan
e
th
at
p
ar
allels to
h
y
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e
r
-
p
l
an
ca
n
d
ef
in
e
as th
e
lar
g
est m
ar
g
in
[
2
5
]
,
[
2
6
]
.
T
h
e
lin
ea
r
SVM
h
as d
ep
en
d
e
n
t o
n
th
is
s
tu
d
y
.
2
.
4
.
O
f
f
lin
e
t
est
I
n
o
f
f
lin
e
test
,
ea
c
h
s
u
b
ject
is
to
ld
t
o
p
e
r
f
o
r
m
s
ix
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et
o
f
m
o
v
em
en
ts
an
d
ea
c
h
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et
o
f
m
o
v
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en
ts
is
co
n
s
is
t
o
f
s
ev
en
class
o
f
m
o
v
em
en
ts
th
at
d
escr
ib
e
i
n
th
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Fi
g
u
r
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3
.
E
v
er
y
m
o
v
em
en
t
tak
e
s
3
s
ec
o
n
d
s
s
o
t
h
at
th
e
s
et
tak
es 2
1
s
ec
o
n
d
s
.
Fo
u
r
s
ets o
f
m
o
v
em
en
t
h
av
e
b
ee
n
u
s
ed
to
tr
ain
th
e
SVM
class
if
ier
,
an
d
th
e
o
th
er
two
s
ets
h
av
e
b
ee
n
u
s
ed
to
tes
t
th
e
class
if
ier
.
T
h
e
o
f
f
lin
e
test
h
as
u
s
ed
to
ev
alu
ate
th
e
s
ig
n
als
an
d
s
h
o
w
th
e
b
est
p
o
s
itio
n
f
o
r
th
e
s
en
s
o
r
s
o
n
th
e
h
an
d
.
T
h
e
im
p
o
r
tan
ce
o
f
t
h
e
o
f
f
lin
e
test
h
as
ev
alu
ate
d
th
e
s
tu
d
y
alg
o
r
ith
m
a
n
d
h
o
w
to
m
ak
e
th
e
b
est ac
cu
r
ac
y
[
2
7
]
.
2
.
4
.
1
.
O
nli
ne
t
est
I
n
th
e
o
n
lin
e
test
,
ea
ch
s
u
b
ject
co
n
tr
o
ls
th
e
p
r
o
s
th
etic
h
an
d
i
n
a
r
ea
l
-
tim
e
s
tate
with
s
p
ec
if
ied
class
es
d
escr
ib
ed
in
Fig
u
r
e
2
.
As
m
en
tio
n
ed
in
t
h
e
o
f
f
lin
e
test
,
f
o
u
r
s
ets
h
av
e
also
u
s
ed
to
tr
ai
n
th
e
class
if
ier
th
en
th
e
tr
ain
ed
class
if
ier
is
u
s
ed
to
c
o
n
tr
o
l
th
e
p
r
o
s
th
etic
h
an
d
.
T
h
en
ea
ch
s
u
b
ject
p
er
f
o
r
m
s
th
e
s
p
ec
if
ied
g
estu
r
e,
wh
ich
will d
ir
ec
tly
co
n
tr
o
l th
e
p
r
o
s
th
etic
h
an
d
to
ca
lcu
late
th
e
ac
cu
r
ac
y
[
2
8
]
.
3.
P
RO
ST
H
E
T
I
C
H
A
ND
T
h
e
c
h
a
l
l
e
n
g
e
o
f
t
h
e
p
r
e
s
e
n
t
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h
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ity
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r
aq
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n
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n
s
titu
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th
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ass
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wh
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elp
e
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ad
v
a
n
ce
th
is
wo
r
k
.
RE
F
E
R
E
NC
E
S
[1
]
A.
Clo
u
ti
e
r
a
n
d
J.
Ya
n
g
,
“
Co
n
tr
o
l
Of
Ha
n
d
P
ro
st
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e
se
s
-
A
Li
tera
tu
re
Re
v
iew
,
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M
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3
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ter
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sig
n
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mp
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ter
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d
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1
1
1
5
/DET
C
2
0
1
3
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3
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4
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.
[2
]
M
.
R.
M
o
h
a
m
a
d
Ism
a
il
,
C
.
K
.
La
m
,
K
.
S
u
n
d
a
ra
j,
a
n
d
M
.
H
.
F
.
Ra
h
ima
n
,
“
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n
d
m
o
ti
o
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p
a
tt
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o
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n
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l
y
sis
o
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fo
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rm
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u
sc
le
u
sin
g
M
M
G
sig
n
a
ls,”
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ll
e
ti
n
o
f
E
lec
trica
l
En
g
i
n
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rin
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n
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s
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o
.
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p
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0
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0
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5
9
1
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i.
v
8
i
2
.
1
4
1
5
.
[3
]
J
.
To
o
,
A
.
R
.
A
b
d
u
ll
a
h
,
T
.
N
.
S
.
T
.
Zaw
a
wi,
N
.
M
.
S
a
a
d
,
a
n
d
H
.
M
u
sa
.,
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Clas
sifica
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o
f
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ig
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l
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se
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n
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d
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re
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y
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o
m
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in
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e
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tu
re
s,”
I
n
ter
n
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ti
o
n
a
l
J
o
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rn
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l
o
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ma
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ter
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l.
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o
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1
,
p
p
.
1
-
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0
1
7
.
[
4
]
D
.
T
k
a
c
h
,
H
.
H
u
a
n
g
,
a
n
d
T
.
A
.
K
u
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k
e
n
,
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n
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n
,
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o
u
r
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7
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1
.
[5
]
M
.
M
o
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a
m
m
a
d
i,
F
.
Al
-
Az
a
b
,
B
.
Ra
a
h
e
m
i,
G
.
Rich
a
rd
s,
a
n
d
N
.
Ja
wo
rsk
a
,
“
Da
ta
m
in
in
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EE
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sig
n
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ls
in
d
e
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r
th
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m
s,
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n
d
t
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,
”
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C
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.
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n
fo
rm
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7
-
6
.
[
6
]
Y
.
Y
.
F
a
n
g
,
N
.
H
e
t
t
i
a
r
a
c
h
c
h
i
,
D
.
Z
h
o
u
,
a
n
d
H
.
Liu
,
“
M
u
l
t
i
-
m
o
d
a
l
s
e
n
s
i
n
g
t
e
c
h
n
i
q
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e
s
f
o
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i
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t
e
r
f
a
c
i
n
g
h
a
n
d
p
r
o
s
t
h
e
s
e
s
:
A
r
e
v
i
e
w
,
”
I
E
E
E
S
e
n
s
.
J
.
,
v
o
l
.
1
5
n
o
.
11,
pp.
6065
-
6
0
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6
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2
0
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5
,
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S
E
N
.
2
0
1
5
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2
4
5
0
2
1
1
.
[7
]
A
.
Tes
ta,
M
.
Cin
q
u
e
,
A
.
Co
ro
n
a
to
,
G
.
De
P
ietro
,
a
n
d
J
.
C
.
Au
g
u
sto
,
“
He
u
risti
c
stra
teg
ies
fo
r
a
ss
e
ss
in
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wire
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se
n
so
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n
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sili
e
n
c
y
:
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n
e
v
e
n
t
-
b
a
se
d
f
o
rm
a
l
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p
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ro
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c
h
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o
u
rn
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l
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ristic
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2
1
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o
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p
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4
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9
2
5
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-
x
.
[8
]
D
.
Esp
o
sit
o
,
E
.
A
n
d
re
o
z
z
i,
A
.
F
r
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ti
n
i,
G
.
D.
G
a
rg
iu
lo
,
a
n
d
S
.
S
a
v
in
o
,
“
A
p
iez
o
re
sistiv
e
se
n
so
r
t
o
m
e
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su
re
m
u
sc
l
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co
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trac
ti
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a
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d
m
e
c
h
a
n
o
m
y
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ra
p
h
y
,
”
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e
n
so
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wit
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d
,
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l.
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8
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o
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p
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3
3
9
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0
8
2
5
5
3
.
[
9
]
R
.
d
e
la
Ro
sa
,
A
.
Alo
n
so
,
A
.
Ca
rre
ra
,
R
.
J.
Du
rá
n
,
a
n
d
P
.
F
e
rn
á
n
d
e
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,
“
M
a
n
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m
a
c
h
in
e
in
terfa
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e
sy
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m
fo
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n
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ro
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sc
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lar
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d
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se
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E
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d
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M
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ls,”
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3
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[1
0
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.
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.
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,
N
.
A
.
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m
z
a
id
,
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.
M
.
Z
u
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ig
a
,
a
n
d
A
.
K
.
A
.
Wa
h
a
b
,
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e
c
h
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n
o
m
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ra
p
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n
d
M
u
sc
le
F
u
n
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ti
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n
As
se
ss
m
e
n
t:
A
Re
v
iew
o
f
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rre
n
t
S
tate
a
n
d
P
ro
sp
e
c
ts,”
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ica
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B
io
me
c
h
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n
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l.
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o
.
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4
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[
1
1
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C
.
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e
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a
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T
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,
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[1
2
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.
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u
o
,
X
.
S
h
e
n
g
,
H
.
Li
u
,
a
n
d
X
.
Zh
u
,
“
M
e
c
h
a
n
o
m
y
o
g
ra
p
h
y
a
ss
isted
m
y
o
e
letric
se
n
sin
g
fo
r
u
p
p
e
r
-
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x
trem
it
y
p
ro
sth
e
se
s:
A
h
y
b
ri
d
a
p
p
ro
a
c
h
,
”
IEE
E
S
e
n
s
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l
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l.
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6
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[
1
3
]
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.
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e
i
,
S
.
M
a
,
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X
.
L
i
,
“
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M
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m
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l
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[1
4
]
Li
Z
h
a
n
g
,
Wei
d
a
Z
h
o
u
,
a
n
d
Li
c
h
e
n
g
Jia
o
,
“
Wav
e
let
su
p
p
o
rt
v
e
c
to
r
m
a
c
h
in
e
,”
I
EE
E
T
ra
n
sa
c
ti
o
n
s
o
n
S
y
ste
ms
,
v
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l.
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o
.
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M
CB.2
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3
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8
1
1
1
1
3
.
[1
5
]
A.
Wo
łcz
o
ws
k
i,
a
n
d
R
.
Z
d
u
n
e
k
,
“
El
e
c
tro
m
y
o
g
ra
p
h
y
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n
d
m
e
c
h
a
n
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m
y
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g
ra
p
h
y
sig
n
a
l
re
c
o
g
n
it
io
n
:
Ex
p
e
rime
n
tal
a
n
a
ly
sis
u
sin
g
m
u
lt
i
-
wa
y
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rra
y
d
e
c
o
m
p
o
siti
o
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m
e
th
o
d
s
,
”
Bi
o
c
y
b
e
rn
.
Bi
o
me
d
.
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n
g
,
v
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l.
3
7
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o
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/
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b
b
e
.
2
0
1
6
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0
9
.
0
0
4
.
[1
6
]
N.
S
i
d
d
i
q
u
i
a
n
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.
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6
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7
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8
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9
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