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[
1
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[
2
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Mo
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3
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.
R
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cl
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
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8
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8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
9
2
9
-
6
9
4
3
6930
p
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to
th
e
lu
n
g
s
.
T
h
e
r
esp
ir
ato
r
y
s
ig
n
al’
s
am
p
litu
d
e
r
is
es
b
ec
au
s
e
o
f
th
is
.
A
s
th
e
d
iap
h
r
ag
m
r
elax
es
an
d
th
e
ch
est co
n
tr
ac
ts
,
th
e
air
is
f
o
r
ce
d
o
u
t o
f
th
e
lu
n
g
s
d
u
r
i
n
g
ex
h
alatio
n
.
T
h
e
r
esp
ir
ato
r
y
s
ig
n
al’
s
am
p
litu
d
e
d
ec
r
ea
s
es a
s
a
r
esu
lt.
Nu
m
er
o
u
s
asp
ec
ts
o
f
r
esp
ir
atio
n
,
in
clu
d
in
g
th
e
r
esp
ir
at
o
r
y
r
ate,
th
e
d
ep
th
o
f
ea
c
h
b
r
ea
t
h
,
an
d
th
e
v
a
r
iab
ilit
y
o
f
t
h
e
s
ig
n
al
o
v
er
tim
e,
ca
n
b
e
s
tu
d
ied
u
s
in
g
th
e
r
esp
ir
ato
r
y
s
ig
n
al.
Diag
n
o
s
in
g
r
esp
ir
at
o
r
y
d
is
o
r
d
er
s
an
d
g
ain
in
g
in
s
ig
h
t i
n
to
h
o
w
th
e
r
esp
ir
ato
r
y
s
y
s
tem
wo
r
k
s
b
y
an
aly
zin
g
th
ese
f
e
atu
r
es is
p
o
s
s
ib
le.
Fig
u
r
e
1
.
R
esp
ir
atio
n
s
ig
n
al
An
in
d
icato
r
o
f
v
e
n
tilatio
n
,
o
r
th
e
f
lo
w
o
f
air
in
to
an
d
o
u
t
o
f
th
e
lu
n
g
s
,
th
e
r
esp
ir
atio
n
r
ate,
o
f
te
n
k
n
o
wn
as
th
e
n
u
m
b
e
r
o
f
b
r
e
ath
s
p
er
m
in
u
te,
is
a
clin
ical
m
ea
s
u
r
e.
As
th
e
b
o
d
y
tr
ies
to
k
ee
p
th
e
tis
s
u
es’
o
x
y
g
e
n
s
u
p
p
l
y
g
o
in
g
,
a
s
h
if
t
i
n
r
esp
ir
atio
n
r
ate
is
f
r
eq
u
en
tl
y
th
e
f
ir
s
t
in
d
icatio
n
o
f
d
eter
i
o
r
atio
n
[
4
]
,
[
5
]
.
Fo
r
p
u
lm
o
n
a
r
y
d
is
o
r
d
e
r
s
,
r
esp
ir
atio
n
r
ates
an
d
p
atter
n
s
m
ay
b
e
u
s
ed
to
d
iag
n
o
s
e
an
d
tr
ac
k
a
p
er
s
o
n
'
s
h
ea
lth
co
n
ce
r
n
s
.
W
h
ile
th
e
av
er
a
g
e
r
esti
n
g
r
esp
ir
atio
n
r
ate
v
ar
ies
f
r
o
m
p
e
r
s
o
n
to
p
er
s
o
n
,
it
g
en
er
ally
r
an
g
es
f
r
o
m
1
2
to
2
0
b
p
m
(
b
r
ea
th
s
p
er
m
in
u
te)
.
B
esid
es,
th
er
e
ar
e
th
r
ee
ty
p
es
o
f
ab
n
o
r
m
al
r
esp
ir
ato
r
y
r
ates
wh
ich
ar
e
tach
y
p
n
ea
(
h
ig
h
r
esp
ir
ato
r
y
r
a
te)
,
b
r
ad
y
p
n
e
a
(
lo
w
r
esp
ir
ato
r
y
r
ate)
,
a
n
d
a
p
n
ea
(
ce
s
s
atio
n
o
f
r
esp
ir
atio
n
)
[
6
]
.
T
h
e
p
r
im
a
r
y
r
esp
ir
ato
r
y
m
u
s
cl
e’
s
d
iap
h
r
a
g
m
f
latten
s
a
n
d
c
o
n
tr
ac
ts
ty
p
ically
d
u
r
in
g
in
s
p
ir
a
tio
n
,
p
u
llin
g
o
n
th
e
b
elly
an
d
p
u
s
h
in
g
th
e
lo
wer
r
i
b
s
f
o
r
war
d
a
n
d
o
u
twar
d
[
7
]
.
F
o
r
th
o
u
s
an
d
s
o
f
y
ea
r
s
,
E
aster
n
civ
ilizatio
n
s
h
a
v
e
m
an
ag
ed
o
n
e’
s
b
r
ea
t
h
to
im
p
r
o
v
e
o
r
r
esto
r
e
o
n
e’
s
h
ea
lth
.
Fo
r
in
s
tan
ce
,
y
o
g
ic
r
esp
ir
atio
n
(
p
r
a
n
ay
am
a)
is
a
well
-
k
n
o
wn
,
ag
e
-
o
ld
r
e
g
u
late
d
r
esp
ir
atio
n
tech
n
i
q
u
e
f
r
e
q
u
e
n
tly
u
s
ed
with
y
o
g
a
o
r
m
ed
ita
tio
n
b
ec
au
s
e
o
f
it
is
p
u
r
p
o
r
ted
s
p
ir
itu
al
a
n
d
h
ea
lth
-
im
p
r
o
v
in
g
b
e
n
ef
its
.
Pra
n
ay
am
a
is
a
ty
p
e
o
f
y
o
g
a
th
at
f
o
cu
s
es
o
n
co
n
tr
o
llin
g
o
n
e’
s
b
r
ea
th
.
T
h
er
e
ar
e
s
ev
e
r
a
l
f
o
r
m
s
o
f
p
r
an
ay
am
a
,
ea
ch
with
its
o
wn
s
et
o
f
ad
v
an
tag
es.
I
m
p
r
o
v
ed
r
esp
ir
ato
r
y
f
u
n
ctio
n
,
less
s
tr
ess
an
d
an
x
iety
,
in
cr
ea
s
ed
en
er
g
y
lev
els,
im
p
r
o
v
ed
f
o
cu
s
an
d
atten
tio
n
,
en
h
an
ce
d
r
elax
atio
n
,
an
d
in
c
r
ea
s
ed
s
elf
-
awa
r
en
ess
ar
e
s
o
m
e
o
f
th
e
b
e
n
ef
its
o
f
p
r
a
n
a
y
am
a.
A
p
er
s
o
n
’
s
r
esp
ir
ato
r
y
r
ate
is
r
eg
u
lated
b
y
a
v
ar
iety
o
f
f
ac
to
r
s
,
in
clu
d
in
g
ag
e,
ex
er
cise
lev
el,
an
d
b
o
d
y
tem
p
er
atu
r
e.
Alth
o
u
g
h
th
e
t
y
p
ical
r
esp
ir
atio
n
r
ate
v
ar
ies
s
ig
n
if
ican
tly
ac
r
o
s
s
in
d
iv
id
u
als,
d
o
cto
r
s
an
d
n
u
r
s
es
r
eg
ar
d
a
ce
r
tain
r
a
n
g
e
to
b
e
n
o
r
m
al.
T
ab
le
1
p
r
esen
ts
th
e
ty
p
e
o
f
r
esp
ir
atio
n
r
ate
co
n
d
itio
n
ac
co
r
d
in
g
to
ag
e
f
r
o
m
n
ewb
o
r
n
to
a
d
u
lt.
Ho
wev
er
,
tach
y
p
n
ea
is
th
e
ea
r
lies
t
o
b
s
er
v
ab
le
clin
ical
s
y
m
p
to
m
an
d
th
e
p
atien
t’
s
m
ea
n
s
o
f
co
m
p
en
s
atin
g
f
o
r
th
e
r
estricte
d
lu
n
g
ca
p
ac
ity
ca
u
s
ed
b
y
r
es
tr
ictiv
e
lu
n
g
d
is
ea
s
e.
T
h
e
ac
ti
v
atio
n
o
f
au
x
iliar
y
m
u
s
cles
r
esu
lts
in
f
u
r
th
er
co
m
p
en
s
atio
n
.
Patien
ts
with
r
estricte
d
illn
ess
m
ay
o
cc
asio
n
ally
tak
e
lar
g
er
-
th
an
-
tid
al
s
ig
h
s
to
attr
ac
t
co
llap
s
in
g
u
n
its
.
I
n
f
ec
te
d
lu
n
g
s
’
co
m
p
en
s
ato
r
y
m
ec
h
a
n
is
m
s
also
wo
r
k
to
im
p
r
o
v
e
g
as
ex
ch
a
n
g
e
[
8
]
.
T
h
u
s
,
ea
ch
p
atter
n
is
clin
ically
e
s
s
en
tial
an
d
v
alu
ab
le
in
ev
alu
atin
g
p
atien
ts
[
9
]
.
I
n
m
ed
icin
e,
r
esp
ir
atio
n
m
ea
s
u
r
e
m
en
t
is
a
cr
u
cial
m
ar
k
er
f
o
r
t
h
e
ea
r
ly
id
en
tific
atio
n
o
f
m
aj
o
r
h
u
m
a
n
d
is
o
r
d
er
s
.
R
ep
o
r
ted
ly
,
d
ata
o
n
r
esp
ir
atio
n
ca
n
b
e
u
s
ed
t
o
p
r
e
d
ict
p
n
e
u
m
o
n
ia,
ca
r
d
io
p
u
lm
o
n
a
r
y
ar
r
est,
an
d
c
h
r
o
n
ic
h
ea
r
t
f
ailu
r
e.
Ho
we
v
er
,
it
h
as
b
ee
n
d
is
co
v
er
ed
th
at
th
e
b
r
ea
t
h
r
ate
(
B
R
)
ca
n
d
is
tin
g
u
is
h
b
etwe
en
s
tab
le
an
d
u
n
s
tab
le
in
d
iv
id
u
als
m
o
r
e
ef
f
ec
tiv
ely
th
an
th
e
h
ea
r
t
r
ate
(
HR
)
.
Mo
n
ito
r
in
g
th
e
r
esp
ir
ato
r
y
s
ig
n
al
m
ay
b
e
u
s
ed
to
id
en
tify
an
d
tr
ea
t
r
esp
ir
ato
r
y
p
r
o
b
lem
s
,
in
clu
d
in
g
ch
r
o
n
ic
o
b
s
tr
u
ctiv
e
p
u
lm
o
n
ar
y
d
is
ea
s
e,
o
n
e
o
f
th
e
m
o
s
t
p
r
ev
alen
t lo
n
g
-
ter
m
co
n
d
itio
n
s
,
an
d
to
f
o
r
ec
ast ca
r
d
iac
ar
r
est an
d
d
iag
n
o
s
e
h
y
p
o
x
e
m
ia
o
r
h
y
p
er
ca
r
b
ia.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
S
ystema
tic
r
ev
iew
:
S
ta
te
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of
-
th
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6931
T
ab
le
1
.
T
y
p
e
o
f
r
esp
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atio
n
r
a
te
co
n
d
itio
n
Ty
p
e
o
f
r
e
s
p
i
r
a
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i
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i
t
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r
e
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e
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mi
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u
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e
G
e
n
d
e
r
A
g
e
(
y
e
a
r
)
M
a
l
e
F
e
mal
e
N
e
w
b
o
r
n
(
B
i
r
t
h
-
1
y)
I
n
f
a
n
t
(1
-
3
y)
To
d
d
l
e
r
(3
-
6
y)
C
h
i
l
d
(6
y
a
n
d
o
l
d
e
r
)
A
d
u
l
t
30
y
a
n
d
a
b
o
v
e
N
o
r
mal
r
e
s
p
i
r
a
t
i
o
n
12
-
16
14
-
18
30
-
50
20
-
40
20
-
30
18
-
24
12
-
16
R
e
s
p
i
r
a
t
o
r
y
r
a
t
e
r
e
mai
n
s
c
o
n
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t
a
n
t
A
b
n
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r
ma
l
r
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sp
i
r
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o
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T
a
c
h
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a
(
h
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g
h
r
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sp
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r
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r
y
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t
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3
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>
2
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Bra
d
y
p
n
e
a
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l
o
w
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e
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p
i
r
a
t
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r
y
r
a
t
e
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-
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1
6
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-
10
Ap
n
e
a
(
c
e
ssa
t
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o
n
o
f
r
e
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i
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t
i
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>
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0
Du
e
to
m
an
y
ca
s
es
o
f
ab
n
o
r
m
al
r
esp
ir
atio
n
o
cc
u
r
r
i
n
g
,
m
a
n
y
r
esear
ch
er
s
s
tu
d
y
th
e
u
s
e
o
f
t
ec
h
n
o
lo
g
y
in
m
an
a
g
in
g
r
esp
ir
ato
r
y
d
is
ea
s
es.
Gen
er
ally
,
r
esp
ir
at
o
r
y
s
y
s
tem
tech
n
o
lo
g
y
h
as
two
d
if
f
er
en
t
ty
p
es
o
f
ap
p
r
o
ac
h
:
co
n
tact
an
d
n
o
n
-
c
o
n
tact
r
esp
ir
ato
r
y
d
is
ea
s
es.
Ge
n
er
ally
,
r
esp
ir
ato
r
y
s
y
s
tem
tech
n
o
lo
g
y
h
as
two
ty
p
es
o
f
ap
p
r
o
ac
h
es:
co
n
tac
t
an
d
n
o
n
-
co
n
tact
r
esp
ir
atio
n
m
ea
s
u
r
em
en
t.
C
o
n
v
en
tio
n
ally
,
co
n
tact
-
b
ase
d
m
ea
s
u
r
em
en
t
h
as
b
ee
n
u
s
ed
wid
ely
,
s
u
ch
as
wea
r
ab
le
s
en
s
o
r
s
wh
ich
ca
n
b
e
in
s
talled
with
in
clo
th
in
g
[
1
0
]
,
b
elts
[
1
1
]
,
[
1
2
]
,
d
ir
ec
tly
atta
ch
ed
to
th
e
s
k
in
[
1
3
]
,
[
1
4
]
,
o
r
u
s
ed
in
o
th
er
way
s
as
wea
r
ab
le
s
en
s
o
r
s
f
o
r
r
esp
ir
ato
r
y
m
o
n
ito
r
in
g
.
T
h
e
r
e
ar
e
m
an
y
d
if
f
er
e
n
t
ap
p
r
o
ac
h
es
to
cr
ea
tin
g
wea
r
ab
le
tech
n
o
lo
g
y
,
a
n
d
s
o
m
e
o
f
th
em
ar
e
co
v
e
r
ed
in
d
iv
id
u
ally
in
th
e
f
o
llo
win
g
s
ec
tio
n
s
ac
co
r
d
in
g
t
o
th
e
p
r
im
ar
y
s
en
s
o
r
t
y
p
e.
T
h
e
s
en
s
o
r
,
o
r
th
e
m
ea
s
u
r
ed
co
m
p
o
n
en
t,
m
u
s
t
b
e
in
co
n
tact
with
th
e
s
u
b
ject's
b
o
d
y
wh
en
u
s
in
g
co
n
tact
-
b
ased
m
ea
s
u
r
em
en
t
p
r
o
ce
d
u
r
es
[
1
5
]
.
T
ab
le
2
s
h
o
ws
th
e
ad
v
an
tag
e
an
d
lim
itatio
n
s
o
f
th
e
m
eth
o
d
o
f
r
esp
ir
atio
n
m
ea
s
u
r
em
en
t
wea
r
ab
le
co
n
tact
b
ased
.
T
ab
le
2
.
T
h
e
ad
v
a
n
tag
e
an
d
li
m
itatio
n
o
f
wea
r
a
b
le
co
n
tact
-
b
ased
r
esp
ir
atio
n
m
ea
s
u
r
em
e
n
t
Ty
p
e
o
f
c
o
n
t
a
c
t
-
b
a
s
e
d
A
d
v
a
n
t
a
g
e
s
Li
mi
t
a
t
i
o
n
s
EM
F
i
t
Le
ss
i
n
v
a
s
i
v
e
,
a
n
d
i
t
w
a
s
e
f
f
e
c
t
i
v
e
i
n
d
e
t
e
c
t
i
n
g
r
e
sp
i
r
a
t
o
r
y
r
a
t
e
Th
e
se
n
s
o
r
w
a
s
o
n
l
y
e
f
f
e
c
t
i
v
e
f
o
r
p
a
t
i
e
n
t
s wh
o
w
e
r
e
s
t
a
t
i
o
n
a
r
y
o
r
o
n
l
y
mo
d
e
r
a
t
e
l
y
a
c
t
i
v
e
s
i
n
c
e
b
o
d
y
mo
t
i
o
n
s
i
n
f
l
u
e
n
c
e
t
h
e
a
c
c
u
r
a
c
y
o
f
t
h
e
m
e
a
s
u
r
e
m
e
n
t
[
1
2
]
.
S
p
i
r
o
me
t
r
y
C
a
n
b
e
u
se
d
t
o
scr
e
e
n
f
o
r
r
e
s
p
i
r
a
t
o
r
y
d
i
s
e
a
se
i
n
so
me
h
i
g
h
-
r
i
s
k
s
c
e
n
a
r
i
o
s.
I
t
h
e
l
p
f
u
l
i
n
sep
a
r
a
t
i
n
g
c
a
r
d
i
a
c
d
i
s
e
a
se
f
r
o
m r
e
sp
i
r
a
t
o
r
y
d
i
s
e
a
se
[
1
6
]
.
Th
e
r
e
s
u
l
t
w
i
l
l
b
e
p
o
o
r
,
a
n
d
t
h
e
i
n
t
e
r
p
r
e
t
a
t
i
o
n
w
i
l
l
b
e
t
o
u
g
h
w
h
e
n
p
a
t
i
e
n
t
n
o
t
f
o
l
l
o
w
t
h
e
i
n
s
t
r
u
c
t
i
o
n
w
h
i
l
e
u
si
n
g
t
h
e
sp
i
r
o
me
t
r
y
.
S
martp
h
o
n
e
’
s
mi
c
r
o
p
h
o
n
e
F
o
r
n
a
sa
l
r
e
s
p
i
r
a
t
i
o
n
n
o
i
s
e
s re
c
o
r
d
e
d
b
y
a
smar
t
p
h
o
n
e
's m
i
c
r
o
p
h
o
n
e
,
t
h
e
a
c
c
u
r
a
t
e
r
e
sp
i
r
a
t
i
o
n
r
a
t
e
c
a
n
b
e
c
a
l
c
u
l
a
t
e
d
a
s
t
h
e
e
st
i
mat
i
o
n
e
r
r
o
r
s
[
1
7
]
,
[
1
8
]
.
A
s b
a
c
k
g
r
o
u
n
d
n
o
i
se
g
e
t
s
l
o
u
d
e
r
,
a
c
c
u
r
a
c
y
b
e
g
a
n
t
o
d
e
c
r
e
a
se
p
r
o
g
r
e
ss
i
v
e
l
y
t
h
e
f
u
r
t
h
e
r
u
sers w
e
r
e
f
r
o
m
t
h
e
s
o
u
r
c
e
o
f
t
h
e
r
e
sp
i
r
a
t
i
o
n
s
o
u
n
d
.
I
mp
e
d
a
n
c
e
p
n
e
u
mo
g
r
a
p
h
y
A
c
c
u
r
a
t
e
a
ss
e
ssm
e
n
t
o
f
se
v
e
r
a
l
r
e
s
p
i
r
a
t
o
r
y
p
a
r
a
m
e
t
e
r
s.
Th
i
s
p
o
r
t
a
b
l
e
,
a
f
f
o
r
d
a
b
l
e
d
e
v
i
c
e
c
o
u
l
d
h
e
l
p
w
i
t
h
h
e
a
l
t
h
c
a
r
e
[
1
9
]
.
A
n
a
l
y
s
e
s a
r
e
d
i
f
f
i
c
u
l
t
t
o
c
o
m
p
l
e
t
e
a
n
d
r
e
q
u
i
r
e
s
p
e
c
i
a
l
i
z
e
d
e
q
u
i
p
me
n
t
.
Du
e
to
t
h
e
in
c
o
n
v
e
n
ien
t
li
m
itatio
n
o
f
co
n
tact
-
b
ased
,
m
o
r
e
r
esear
ch
i
n
tr
o
d
u
ce
s
n
o
n
-
co
n
tact
r
esp
ir
atio
n
m
ea
s
u
r
em
en
t.
T
h
e
n
o
n
-
co
n
tact
m
ea
s
u
r
em
e
n
t
o
f
r
esp
ir
ato
r
y
m
o
tio
n
is
an
i
n
n
o
v
ativ
e
m
et
h
o
d
o
f
ev
alu
atin
g
r
esp
ir
ato
r
y
f
u
n
ctio
n
.
B
r
ief
ly
,
n
o
n
-
co
n
tact
m
ea
s
u
r
em
en
ts
ar
e
m
o
r
e
co
m
f
o
r
ta
b
le
f
o
r
th
e
p
atien
t,
esp
ec
ially
wh
en
p
e
r
f
o
r
m
in
g
co
n
tact
m
ea
s
u
r
em
e
n
ts
is
p
ar
ticu
lar
ly
ch
allen
g
i
n
g
r
eg
ar
d
i
n
g
th
e
s
p
ec
ialized
eq
u
ip
m
en
t
a
n
d
co
m
p
licated
s
etu
p
p
r
o
ce
s
s
[
2
0
]
.
T
h
er
e
f
o
r
e,
s
ev
er
al
tech
n
iq
u
es
th
at
d
o
n
o
t
r
eq
u
ir
e
to
u
c
h
s
en
s
o
r
s
to
b
e
co
n
n
ec
ted
to
th
e
p
atien
t
h
a
v
e
b
ee
n
d
ev
el
o
p
ed
to
r
ed
u
ce
p
atien
t
p
ain
an
d
in
c
r
ea
s
e
th
e
ac
ce
s
s
ib
ilit
y
o
f
r
esp
ir
ato
r
y
d
ata,
in
clu
d
in
g
th
er
m
al
im
ag
i
n
g
,
m
icr
o
wav
e
-
b
ased
,
a
n
d
r
ad
a
r
-
b
ased
tech
n
iq
u
es.
Fo
r
in
s
tan
ce
,
th
ese
ar
e
a
f
ew
ex
am
p
les
th
at
ar
e
f
r
eq
u
en
tly
u
s
ed
in
a
clin
ical
s
ettin
g
wh
ic
h
ar
e
d
o
p
p
ler
r
a
d
ar
[
2
1
]
,
d
ep
th
s
en
s
o
r
s
[
2
2
]
,
laser
v
ib
r
o
m
et
r
y
[
2
3
]
,
an
d
R
GB
ca
m
er
as
[
2
4
]
,
[
2
5
]
.
Ho
wev
e
r
,
t
h
e
p
r
ac
tical
u
s
e
o
f
th
ese
tech
n
iq
u
es
is
co
n
s
tr
ain
ed
b
y
th
e
r
eq
u
ir
em
en
t
f
o
r
r
ath
er
lar
g
e
p
er
io
d
s
an
d
ass
u
m
p
tio
n
s
r
eg
ar
d
in
g
th
e
r
eg
u
lar
ity
o
f
r
esp
ir
atio
n
r
ate
[
2
6
]
.
T
a
b
le
3
d
is
p
lay
s
th
e
a
d
v
an
tag
e
an
d
lim
itatio
n
o
f
t
h
e
t
y
p
e
o
f
n
o
n
-
co
n
tact
m
eth
o
d
r
e
v
iewe
d
.
No
n
-
co
n
tact
tech
n
iq
u
es
f
o
r
m
ea
s
u
r
in
g
r
esp
ir
atio
n
h
av
e
d
r
a
wn
m
o
r
e
atten
tio
n
in
r
ec
en
t
y
ea
r
s
.
T
h
u
s
,
th
e
cr
ea
tio
n
o
f
n
ew
tech
n
o
l
o
g
ies
an
d
th
e
r
is
in
g
d
em
an
d
f
o
r
n
o
n
-
in
v
asiv
e
an
d
r
em
o
te
m
o
n
ito
r
in
g
s
o
lu
tio
n
s
in
h
ea
lth
ca
r
e
an
d
welln
ess
ap
p
licatio
n
s
.
C
o
m
p
ar
ed
t
o
co
n
tact
m
eth
o
d
s
,
n
o
n
-
c
o
n
tact
tech
n
iq
u
es
f
o
r
m
ea
s
u
r
in
g
r
esp
ir
atio
n
h
av
e
a
f
ew
b
en
e
f
its
.
T
h
ey
ar
e
n
o
n
-
in
v
asiv
e,
wh
i
ch
m
ea
n
s
th
e
u
s
er
ca
n
u
s
e
th
e
m
m
o
r
e
ea
s
ily
an
d
co
m
f
o
r
ta
b
ly
b
ec
a
u
s
e
n
o
s
en
s
o
r
s
o
r
elec
tr
o
d
es n
ee
d
to
b
e
a
f
f
i
x
ed
to
th
e
b
o
d
y
.
T
h
e
y
also
elim
in
ate
th
e
p
o
ten
tial
f
o
r
s
k
in
in
f
ec
tio
n
s
o
r
r
ash
es th
at
co
n
tact
s
en
s
o
r
s
m
ay
b
r
i
n
g
o
n
.
No
n
-
c
o
n
tact
tech
n
i
q
u
es c
an
also
b
e
u
s
ed
wh
e
n
it
is
im
p
r
ac
tical
to
u
s
e
co
n
tact
tech
n
iq
u
es,
s
u
c
h
as
wh
en
th
e
u
s
er
is
s
leep
in
g
o
r
m
o
v
i
n
g
a
r
o
u
n
d
.
I
n
t
h
e
cu
r
r
en
t
co
r
o
n
a
v
ir
u
s
d
is
ea
s
e
2
0
1
9
(
C
OVI
D
-
19)
p
a
n
d
em
ic
co
n
tex
t,
wh
er
e
th
er
e
is
an
in
cr
ea
s
in
g
n
ee
d
f
o
r
telem
ed
icin
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
9
2
9
-
6
9
4
3
6932
s
o
lu
tio
n
s
,
th
ey
ca
n
also
b
e
u
s
ed
f
o
r
r
em
o
te
m
o
n
ito
r
in
g
.
T
h
e
ab
ilit
y
to
an
aly
ze
non
-
co
n
ta
ct
s
ig
n
als,
s
u
ch
as
th
o
s
e
o
b
tain
ed
f
r
o
m
ca
m
er
a
s
o
r
m
icr
o
p
h
o
n
es,
an
d
e
x
tr
a
ct
v
alu
ab
le
d
ata
ab
o
u
t
r
esp
ir
atio
n
,
s
u
ch
as
th
e
r
esp
ir
ato
r
y
r
ate,
d
e
p
th
,
an
d
v
a
r
iab
ilit
y
,
h
as
b
ee
n
m
a
d
e
p
o
s
s
ib
le
b
y
ad
v
a
n
ce
s
in
c
o
m
p
u
te
r
v
is
io
n
an
d
m
ac
h
in
e
lear
n
in
g
.
As
a
r
esu
lt,
n
ew
o
p
p
o
r
tu
n
ities
f
o
r
tr
ac
k
in
g
c
h
an
g
es
in
r
esp
ir
atio
n
p
atter
n
s
o
v
er
ti
m
e
an
d
m
o
n
ito
r
in
g
an
d
d
iag
n
o
s
in
g
r
esp
ir
ato
r
y
d
i
s
o
r
d
er
s
u
s
in
g
n
o
n
-
co
n
tact
tec
h
n
iq
u
es
h
av
e
co
m
e
to
lig
h
t.
I
n
th
e
clim
ax
,
th
e
ad
v
an
tag
es
o
f
n
o
n
-
c
o
n
tact
m
e
th
o
d
s
f
o
r
m
ea
s
u
r
i
n
g
r
esp
ir
atio
n
o
v
er
co
n
tact
m
eth
o
d
s
,
th
e
d
ev
elo
p
m
en
t
o
f
n
ew
tech
n
o
lo
g
ies,
an
d
th
e
r
is
in
g
n
ee
d
f
o
r
n
o
n
-
in
v
asiv
e
an
d
r
em
o
te
m
o
n
ito
r
in
g
s
o
lu
tio
n
s
in
h
ea
lth
ca
r
e
an
d
welln
ess
ap
p
licatio
n
s
all
co
n
tr
ib
u
te
to
th
e
g
r
o
win
g
in
ter
est in
th
ese
m
eth
o
d
s
.
T
ab
le
3
.
T
h
e
ad
v
a
n
tag
e
an
d
li
m
itatio
n
s
o
f
n
o
n
-
co
n
tact
r
esp
ir
atio
n
m
ea
s
u
r
em
e
n
t
Ty
p
e
o
f
n
o
n
-
c
o
n
t
a
c
t
me
t
h
o
d
A
d
v
a
n
t
a
g
e
s
Li
mi
t
a
t
i
o
n
s
R
G
B
v
i
d
e
o
c
a
mer
a
s
y
st
e
m
[
2
4
]
,
[
2
7
]
,
[
2
8
]
A
si
m
p
l
e
c
a
mera
u
s
i
n
g
st
a
n
d
a
r
d
-
r
e
so
l
u
t
i
o
n
i
ma
g
e
s
c
a
n
b
e
u
s
e
d
.
S
o
me
m
e
t
h
o
d
s
a
r
e
e
a
sy
t
o
u
s
e
a
n
d
c
o
u
l
d
b
e
u
se
d
i
n
t
h
e
w
a
r
d
o
r
h
o
me
e
n
v
i
r
o
n
me
n
t
.
B
o
d
y
m
o
v
e
me
n
t
c
a
n
sh
i
f
t
t
h
e
f
a
c
e
f
r
o
m t
h
e
c
a
mer
a
’
s ra
n
g
e
o
f
v
i
e
w
f
o
r
l
o
n
g
-
t
e
r
m
(
l
i
k
e
n
i
g
h
t
t
i
me)
su
r
v
e
i
l
l
a
n
c
e
.
A
f
e
e
d
b
a
c
k
s
y
st
e
m w
o
u
l
d
b
e
r
e
q
u
i
r
e
d
.
T
h
e
mo
n
i
t
o
r
i
n
g
c
a
n
n
o
t
c
o
n
t
i
n
u
e
i
f
h
a
n
d
s
,
b
l
a
n
k
e
t
s,
o
r
a
n
y
h
i
d
e
t
h
e
f
a
c
e
.
D
o
p
p
l
e
r
r
a
d
a
r
[
2
1
]
I
t
c
a
n
b
e
u
se
d
a
t
l
o
n
g
d
i
s
t
a
n
c
e
s.
P
o
ssi
b
i
l
i
t
y
o
f
w
i
r
e
l
e
ss
t
r
a
n
sf
e
r
o
f
r
e
sp
i
r
a
t
o
r
y
r
a
t
e
d
a
t
a
t
o
t
h
e
c
e
n
t
r
a
l
u
n
i
t
.
M
o
v
e
me
n
t
c
r
e
a
t
e
s
a
r
t
e
f
a
c
t
s w
h
i
c
h
a
l
t
e
r
t
h
e
r
e
sp
i
r
a
t
o
r
y
r
a
t
e
si
g
n
a
l
.
C
u
r
r
e
n
t
l
y
e
x
p
e
n
si
v
e
a
n
d
c
h
a
l
l
e
n
g
i
n
g
t
o
se
t
u
p
.
La
ser
v
i
b
r
o
me
t
r
y
[
2
9
]
Th
e
p
o
s
t
-
p
r
o
c
e
ss
i
n
g
i
s
p
r
i
m
a
r
y
a
n
d
u
s
e
s rea
l
-
t
i
me
o
u
t
p
u
t
.
H
o
w
e
v
e
r
,
i
t
i
s
a
si
g
n
i
f
i
c
a
n
t
s
t
a
n
d
-
o
f
f
d
i
st
a
n
c
e
n
o
n
-
c
o
n
t
a
c
t
d
i
sp
l
a
c
e
m
e
n
t
m
e
a
s
u
r
e
m
e
n
t
a
s w
e
l
l
.
Le
ss
a
c
c
e
ssi
b
i
l
i
t
y
U
l
t
r
a
-
w
i
d
e
b
a
n
d
[
3
0
]
,
[
3
1
]
Th
e
u
l
t
r
a
-
w
i
d
e
b
a
n
d
(
U
W
B
)
r
a
d
a
r
se
n
so
r
d
e
m
o
n
s
t
r
a
t
e
d
v
e
r
y
a
c
c
u
r
a
t
e
r
e
s
p
i
r
a
t
i
o
n
mea
s
u
r
e
m
e
n
t
.
Th
e
a
c
c
u
r
a
c
y
c
o
u
l
d
s
u
f
f
e
r
f
r
o
m
o
b
s
t
a
c
l
e
s
b
e
t
w
e
e
n
t
h
e
h
u
m
a
n
b
o
d
y
a
n
d
t
h
e
se
n
s
o
r
.
Th
e
r
m
a
l
i
m
a
g
i
n
g
[
3
2
]
C
o
m
p
a
r
e
d
t
o
o
t
h
e
r
t
e
c
h
n
i
q
u
e
s
f
o
r
m
e
a
su
r
i
n
g
r
e
s
p
i
r
a
t
o
r
y
r
a
t
e
,
i
t
c
o
u
l
d
b
e
mo
r
e
i
mp
a
r
t
i
a
l
a
n
d
r
e
l
i
a
b
l
e
[
3
3
]
S
u
c
c
e
ssi
v
e
e
v
a
l
u
a
t
i
o
n
s
o
f
t
h
e
o
b
j
e
c
t
's
d
i
s
t
a
n
c
e
f
r
o
m t
h
e
c
a
mera
,
i
t
s
v
a
r
i
a
t
i
o
n
s
i
n
m
o
v
e
me
n
t
,
t
e
m
p
e
r
a
t
u
r
e
,
a
n
d
h
u
mi
d
i
t
y
,
a
s we
l
l
a
s
t
h
e
c
r
e
a
t
i
o
n
o
f
a
c
o
st
l
y
mo
n
i
t
o
r
.
B
r
ea
th
in
g
s
ig
n
als
ar
e
a
f
o
r
m
o
f
p
h
y
s
io
lo
g
ical
s
ig
n
al
u
s
ed
to
ev
alu
ate
r
esp
ir
ato
r
y
h
ea
lth
.
I
t
ca
n
b
e
u
s
ed
to
d
iag
n
o
s
e
r
esp
ir
ato
r
y
d
is
o
r
d
er
s
,
f
o
llo
w
ch
a
n
g
es
in
r
esp
ir
ato
r
y
h
ea
lth
o
v
er
tim
e,
a
n
d
m
o
n
ito
r
p
atien
ts
with
r
esp
ir
ato
r
y
illn
ess
es.
T
h
e
d
ata
r
ev
iew
in
t
h
is
r
esear
ch
p
ap
er
is
b
ased
o
n
b
o
th
co
n
tact
an
d
non
-
c
o
n
tact
-
b
ased
m
et
h
o
d
s
.
D
ata
class
if
icatio
n
is
th
e
p
r
o
ce
s
s
o
f
lab
ellin
g
a
d
ata
p
o
in
t.
T
h
e
d
ata
class
if
icatio
n
also
ca
n
b
e
u
s
ed
to
class
if
y
r
esp
ir
ato
r
y
s
ig
n
als
as
n
o
r
m
al
o
r
ab
n
o
r
m
al
in
th
e
co
n
tex
t
o
f
b
r
ea
th
in
g
s
ig
n
als.
T
h
er
e
ar
e
two
ap
p
r
o
ac
h
es
to
r
esp
ir
atio
n
class
if
icatio
n
:
m
ac
h
in
e
lear
n
in
g
a
n
d
d
ee
p
lear
n
in
g
.
Kn
o
win
g
th
e
d
if
f
er
en
ce
s
b
etwe
en
m
ac
h
in
e
an
d
d
ee
p
lear
n
in
g
is
b
etter
b
ef
o
r
e
class
if
icatio
n
.
T
ab
le
4
ex
p
o
s
es th
e
d
if
f
er
en
ce
s
b
etwe
en
m
ac
h
in
e
lear
n
in
g
an
d
d
ee
p
lear
n
in
g
in
g
en
er
al.
Dee
p
lear
n
in
g
a
n
d
m
ac
h
i
n
e
l
ea
r
n
in
g
ar
e
t
h
e
two
s
u
g
g
ested
m
eth
o
d
s
f
o
r
r
esp
ir
at
o
r
y
class
if
icatio
n
,
an
d
b
o
th
ar
e
ca
teg
o
r
ies o
f
a
r
tific
ial
in
tellig
en
ce
.
Fig
u
r
e
2
s
h
o
ws
th
e
cr
itical
d
if
f
er
en
ce
b
etwe
en
a
r
tific
ial
in
te
llig
en
ce
(
AI
)
an
d
m
ac
h
in
e
lea
r
n
in
g
.
I
n
a
n
u
ts
h
ell,
m
ac
h
i
n
e
lear
n
in
g
is
AI
th
at
ca
n
a
u
to
m
atica
lly
a
d
a
p
t
with
litt
le
h
u
m
an
h
elp
.
He
n
ce
,
th
e
r
e
ar
e
f
o
u
r
ca
teg
o
r
ies
o
f
m
ac
h
in
e
lear
n
i
n
g
alg
o
r
ith
m
s
:
s
u
p
er
v
is
ed
,
s
em
i
-
s
u
p
er
v
is
ed
,
u
n
s
u
p
er
v
is
ed
an
d
r
ein
f
o
r
ce
m
en
t
lear
n
in
g
.
I
n
s
u
p
e
r
v
is
ed
lear
n
in
g
,
th
e
c
o
m
p
u
ter
u
s
es
g
u
id
an
ce
to
i
n
f
er
a
f
u
n
ctio
n
f
r
o
m
th
e
d
ata,
an
d
it
is
d
iv
id
ed
in
to
th
r
ee
m
ain
ty
p
es
:
class
if
icatio
n
,
r
eg
r
ess
io
n
an
d
f
o
r
ec
asti
n
g
.
T
h
e
ty
p
ical
alg
o
r
ith
m
is
k
-
n
ea
r
est
n
eig
h
b
o
r
(
KNN)
,
n
aiv
e
B
ay
e
s
(
NB
)
,
d
ec
is
io
n
tr
ee
s
(
DT
)
,
lin
ea
r
r
eg
r
ess
io
n
(
L
R
)
,
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
i
n
es
(
SVM)
an
d
n
e
u
r
al
n
etwo
r
k
s
.
B
esid
es,
s
em
i
-
s
u
p
er
v
is
ed
lear
n
in
g
u
s
es
lab
elled
a
n
d
u
n
lab
el
ed
d
ata
co
m
p
ar
ab
le
to
s
u
p
er
v
is
ed
lear
n
in
g
.
Un
la
b
eled
d
ata
h
as
n
o
m
ea
n
i
n
g
f
u
l
tag
s
,
wh
er
ea
s
lab
elled
d
ata
h
as
th
em
,
s
o
th
e
alg
o
r
ith
m
ca
n
in
ter
p
r
et
th
em
.
Ma
ch
in
e
lear
n
in
g
s
y
s
tem
s
c
an
lear
n
to
ca
teg
o
r
ize
u
n
lab
e
led
d
ata
u
s
in
g
th
is
co
m
b
in
atio
n
.
W
h
er
ea
s
in
u
n
s
u
p
er
v
is
ed
lear
n
in
g
,
th
e
co
m
p
u
ter
f
in
d
s
a
p
atter
n
o
n
its
o
wn
.
C
lu
s
ter
in
g
an
d
ass
o
ciatio
n
r
u
le
lear
n
in
g
alg
o
r
ith
m
s
ar
e
th
e
two
p
r
im
ar
y
ca
t
eg
o
r
ies
o
f
u
n
s
u
p
er
v
is
ed
lear
n
i
n
g
alg
o
r
ith
m
s
.
T
h
e
ty
p
ical
alg
o
r
ith
m
u
s
ed
is
k
-
m
ea
n
s
clu
s
ter
in
g
an
d
ass
o
ciatio
n
r
u
les.
Oth
er
th
an
t
h
at,
th
e
R
ein
f
o
r
ce
m
e
n
t
L
ea
r
n
in
g
ap
p
r
o
ac
h
u
s
es o
b
s
er
v
atio
n
s
f
r
o
m
in
ter
ac
tin
g
with
th
e
en
v
ir
o
n
m
en
t to
ad
o
p
t
b
e
h
a
v
io
r
s
th
at
m
ax
im
ize
th
e
r
ewa
r
d
o
r
m
i
n
im
ize
th
e
r
is
k
.
T
h
e
ag
en
t,
a
r
ein
f
o
r
ce
m
e
n
t
lear
n
in
g
alg
o
r
ith
m
,
iter
ativ
ely
co
n
tin
u
ally
lear
n
s
f
r
o
m
th
e
en
v
ir
o
n
m
en
t.
T
h
e
ag
en
t
g
r
ad
u
ally
g
ain
s
k
n
o
wled
g
e
f
r
o
m
en
co
u
n
ter
s
with
th
e
en
v
ir
o
n
m
en
t
u
n
til
it
h
as
in
v
esti
g
ated
ev
er
y
s
tate.
Ma
ch
in
e
lear
n
in
g
,
w
h
ich
in
clu
d
es
r
ein
f
o
r
ce
m
e
n
t
lear
n
in
g
,
is
a
s
u
b
s
et
o
f
ar
tific
ial
in
tellig
en
ce
.
I
t
en
a
b
les
s
o
f
twar
e
ag
en
ts
an
d
m
ac
h
in
es
to
au
t
o
m
atica
lly
d
ec
id
e
th
e
b
est
co
u
r
s
e
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ith
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t
o
au
to
m
atica
lly
f
in
d
th
e
u
n
iq
u
e
f
ea
tu
r
es
an
d
t
r
an
s
f
o
r
m
atio
n
s
n
ec
ess
ar
y
f
o
r
th
e
task
in
th
e
r
aw
d
ata
in
s
tead
o
f
d
ep
en
d
i
n
g
o
n
a
r
esear
ch
er
’
s
ju
d
g
em
en
t
an
d
ex
p
e
r
ien
ce
to
ch
o
o
s
e
an
d
en
g
in
ee
r
c
h
ar
ac
ter
is
tics
[
3
5
]
.
T
h
er
ef
o
r
e,
d
ee
p
lear
n
in
g
is
cu
r
r
en
tly
b
ein
g
u
s
ed
to
im
p
r
o
v
e
s
p
ee
c
h
s
ig
n
if
ican
tly
[
3
6
]
,
[
3
7
]
an
d
p
ictu
r
e
r
ec
o
g
n
itio
n
,
r
esp
ec
tiv
el
y
.
I
n
t
h
e
f
i
e
l
d
o
f
c
o
m
p
u
t
e
r
v
i
s
i
o
n
a
n
d
p
a
t
t
e
r
n
r
e
c
o
g
n
i
t
i
o
n
(
C
V
PR
)
,
d
e
e
p
l
e
a
r
n
i
n
g
i
s
o
n
e
o
f
t
h
e
m
o
s
t
e
f
f
e
c
ti
v
e
a
n
d
p
o
p
u
l
a
r
m
e
t
h
o
d
s
[
3
5
]
,
[
3
6
]
,
[
3
8
]
,
a
n
d
c
o
u
l
d
l
e
a
d
t
o
a
b
e
t
t
e
r
u
n
d
e
r
s
ta
n
d
i
n
g
o
f
b
e
h
a
v
i
o
r
a
n
d
p
h
y
s
i
o
l
o
g
i
c
a
l
p
a
tt
e
r
n
s
t
o
an
i
n
d
i
v
i
d
u
a
l
’
s
a
f
f
e
ct
i
v
e
m
o
o
d
s
s
u
c
h
a
s
d
is
t
r
ess
,
a
n
x
i
e
t
y
a
n
d
a
n
y
e
l
s
e
.
T
o
s
o
lv
e
p
r
o
b
lem
s
in
v
o
lv
in
g
u
n
s
tr
u
ctu
r
ed
d
ata,
d
ee
p
lear
n
i
n
g
n
etwo
r
k
s
ar
e
th
e
m
ath
em
at
ical
m
o
d
els
u
s
ed
to
m
im
ic
h
u
m
a
n
b
r
ain
s
[
3
9
]
,
[
4
0
]
.
B
esid
es,
Fig
u
r
e
3
r
ep
r
esen
ts
th
e
s
im
p
le
n
e
u
r
al
n
etwo
r
k
.
T
h
ese
m
ath
em
atica
l
m
o
d
els
a
r
e
d
e
v
elo
p
ed
as
n
eu
r
al
n
etwo
r
k
s
,
wh
ich
ar
e
m
ad
e
u
p
o
f
n
eu
r
o
n
s
.
T
h
e
i
n
p
u
t
lay
er
(
in
itial
lay
er
o
f
th
e
n
eu
r
al
n
et
wo
r
k
)
,
th
e
h
i
d
d
en
lay
er
(
all
th
e
m
id
d
le
lay
er
o
f
th
e
n
eu
r
al
n
etwo
r
k
)
,
an
d
th
e
o
u
tp
u
t
lay
er
a
r
e
th
e
th
r
ee
m
ai
n
lay
er
s
(
last
lay
er
o
f
th
e
n
eu
r
al
n
etwo
r
k
)
.
W
h
ile
s
elf
-
lear
n
in
g
r
ep
r
esen
tatio
n
s
ar
e
a
f
ea
tu
r
e
o
f
d
ee
p
lear
n
in
g
alg
o
r
ith
m
s
,
th
e
y
also
r
ely
o
n
ANNs
th
at
s
im
u
late
h
o
w
th
e
b
r
ai
n
p
r
o
ce
s
s
es
in
f
o
r
m
atio
n
[
4
1
]
.
Alg
o
r
ith
m
s
ex
p
lo
it
u
n
k
n
o
w
n
elem
en
ts
i
n
th
e
in
p
u
t
d
is
tr
ib
u
tio
n
t
h
r
o
u
g
h
o
u
t
th
e
tr
ain
in
g
p
h
ase
to
ex
tr
ac
t
f
ea
tu
r
es,
class
if
y
o
b
jects,
an
d
id
en
tif
y
r
elev
an
t
d
ata
p
atter
n
s
.
I
t
tak
es
p
lac
e
o
n
s
ev
er
al
lev
els,
em
p
lo
y
in
g
th
e
alg
o
r
ith
m
s
to
cr
ea
te
th
e
m
o
d
els,
m
u
ch
lik
e
tr
ain
in
g
m
ac
h
in
es
to
lear
n
f
o
r
th
em
s
elv
es.
T
h
er
e
ar
e
a
f
ew
lis
ts
o
f
d
ee
p
lear
n
in
g
alg
o
r
ith
m
m
eth
o
d
s
th
at
ca
n
b
e
u
s
ed
in
th
is
er
a
o
f
g
lo
b
aliz
atio
n
to
class
if
y
th
e
s
ig
n
al
o
f
r
esp
ir
atio
n
,
s
u
ch
as
co
n
v
o
lu
tio
n
al
n
eu
r
al
n
etwo
r
k
s
(
C
NNs),
lo
n
g
s
h
o
r
t
-
ter
m
m
em
o
r
y
n
etwo
r
k
s
(
L
STM
s
)
,
r
ec
u
r
r
en
t
n
eu
r
al
n
et
wo
r
k
s
(
R
NNs),
g
en
e
r
ativ
e
a
d
v
er
s
ar
ial
n
etwo
r
k
s
(
GANs)
,
r
ad
ial
b
asis
f
u
n
ctio
n
n
etwo
r
k
s
(
R
B
FNs
)
,
m
u
ltil
ay
er
p
er
ce
p
tr
o
n
s
(
ML
Ps
)
,
s
elf
-
o
r
g
an
izin
g
m
a
p
s
(
SOMs),
d
e
ep
b
elief
n
etwo
r
k
s
(
DB
Ns),
r
estricte
d
B
o
ltzm
an
n
m
ac
h
in
es
(
R
B
Ms)
an
d
au
to
en
co
d
er
s
[
4
1
]
.
Fig
u
r
e
3
.
Simp
le
n
eu
r
al
n
etwo
r
k
Dep
en
d
in
g
o
n
th
e
ap
p
licatio
n
an
d
th
e
av
ailab
le
d
ata,
d
ee
p
lear
n
in
g
an
d
m
ac
h
in
e
lea
r
n
i
n
g
m
ay
b
e
ef
f
ec
tiv
e
f
o
r
class
if
y
in
g
r
esp
ir
ato
r
y
s
ig
n
als.
C
las
s
if
y
in
g
r
esp
ir
ato
r
y
s
ig
n
als
ca
n
b
e
ac
co
m
p
lis
h
ed
u
s
in
g
eith
er
d
ee
p
lear
n
in
g
o
r
m
ac
h
in
e
lear
n
in
g
;
th
e
ch
o
s
en
a
p
p
r
o
ac
h
d
ep
en
d
s
o
n
th
e
task
an
d
a
v
ailab
le
d
ata.
Fo
r
ex
am
p
le
,
d
ee
p
lear
n
in
g
will
b
e
a
g
o
o
d
a
lter
n
ativ
e
if
th
ey
wan
t
to
ac
h
ie
v
e
h
ig
h
ac
cu
r
ac
y
an
d
h
av
e
a
l
ar
g
e
d
ataset
o
f
r
aw
r
esp
ir
ato
r
y
s
ig
n
als.
On
th
e
o
t
h
er
h
an
d
,
if
th
ey
n
ee
d
m
o
r
e
i
n
ter
p
r
etab
ilit
y
o
r
h
av
e
a
lim
ited
d
ataset,
m
ac
h
in
e
lear
n
in
g
m
a
y
b
e
th
e
b
etter
ch
o
ice.
2.
M
E
T
H
O
D
I
n
th
is
s
ec
tio
n
,
th
e
d
ata
class
i
f
icatio
n
ap
p
r
o
ac
h
es
ar
e
r
ev
ie
wed
.
W
e
u
s
ed
Sco
p
u
s
to
d
o
a
d
atab
ase
s
ea
r
ch
an
d
it
i
s
ab
o
u
t
m
o
r
e
t
h
an
1
0
0
k
in
d
s
o
f
liter
atu
r
e
s
e
ar
ch
es
o
n
th
e
to
p
ic
o
f
th
e
d
a
ta
class
if
icatio
n
o
f
b
r
ea
th
in
g
s
ig
n
als.
Ho
wev
er
,
n
o
t
all
o
f
th
e
liter
atu
r
e
s
ea
r
ch
es
wer
e
in
clu
d
ed
in
th
e
f
in
al
r
ev
iew.
L
u
ck
ily
f
o
u
n
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
S
ystema
tic
r
ev
iew
:
S
ta
te
-
of
-
th
e
-
a
r
t in
s
en
s
o
r
-
b
a
s
ed
a
b
n
o
r
m
a
lity
…
(
N
u
r
F
a
tin
S
h
a
z
w
a
n
i
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r
R
a
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6935
6
6
r
elev
a
n
t
ar
ticle
p
a
p
er
s
wh
i
ch
ar
e
1
0
a
r
ticle
p
ap
er
s
o
n
m
a
ch
in
e
lear
n
in
g
class
if
icatio
n
,
1
6
ar
ticle
p
a
p
er
s
o
n
d
ee
p
lear
n
i
n
g
class
if
icatio
n
an
d
th
e
r
em
ai
n
in
g
a
r
ticle
p
ap
er
s
ab
o
u
t
r
a
d
ar
s
en
s
o
r
-
b
ased
.
T
h
e
r
esear
ch
to
p
ic
h
ad
to
em
p
lo
y
m
a
ch
in
e
lear
n
in
g
o
r
d
ee
p
lear
n
in
g
t
o
ca
teg
o
r
iz
e
b
r
ea
th
in
g
s
ig
n
als,
u
s
e
a
d
a
taset
o
f
b
r
ea
th
in
g
s
ig
n
als
f
r
o
m
h
ea
lth
y
co
n
tr
o
ls
an
d
p
atien
ts
with
r
esp
ir
a
to
r
y
d
is
ea
s
es,
an
d
d
escr
ib
e
th
e
class
if
icatio
n
alg
o
r
ith
m
’
s
ac
cu
r
ac
y
.
At
th
e
s
am
e
tim
e,
th
e
r
esear
ch
to
p
ic
was
ex
clu
d
ed
b
ec
au
s
e
th
e
r
esear
ch
p
a
p
er
was
n
o
t
in
E
n
g
lis
h
an
d
d
i
d
n
o
t
r
e
p
o
r
t
t
h
e
class
if
icatio
n
alg
o
r
ith
m
’
s
ac
cu
r
ac
y
.
T
h
e
ad
v
an
ta
g
es,
th
e
lim
itatio
n
s
,
an
d
th
e
m
ain
ap
p
licatio
n
s
o
f
th
e
m
eth
o
d
s
wer
e
d
escr
ib
ed
al
o
n
g
with
th
eir
tech
n
ical
class
if
icatio
n
b
y
th
eir
al
g
o
r
ith
m
u
s
e
in
th
e
r
ev
iew.
2
.
1
.
Cla
s
s
if
ica
t
io
n o
f
re
s
pira
t
io
n us
ing
m
a
chine le
a
rning
Fo
r
th
e
class
if
icatio
n
o
f
r
es
p
ir
atio
n
p
atter
n
s
f
o
r
b
o
t
h
r
e
al
-
tim
e
an
d
s
im
u
lated
r
esp
ir
atio
n
d
ata,
v
ar
io
u
s
m
ac
h
i
n
e
lear
n
i
n
g
tech
n
iq
u
es
wer
e
u
s
ed
.
Nev
er
th
ele
s
s
,
in
th
is
p
ap
er
,
s
u
p
er
v
is
ed
le
ar
n
in
g
is
a
s
u
itab
l
e
alg
o
r
ith
m
f
o
r
r
esp
ir
atio
n
class
if
icatio
n
.
Fu
r
th
e
r
m
o
r
e
,
it
h
as
b
ee
n
d
em
o
n
s
tr
ated
th
at
u
s
in
g
s
im
u
lated
d
ata
f
o
r
tr
ain
in
g
p
u
r
p
o
s
es
in
cr
ea
s
es
a
cc
u
r
ac
y
.
T
h
e
ar
ticle
s
u
g
g
ests
a
f
r
am
ewo
r
k
f
o
r
en
h
a
n
cin
g
m
ac
h
in
e
lear
n
i
n
g
d
atasets
to
in
cr
ea
s
e
th
e
p
r
ec
is
i
o
n
o
f
class
if
ier
s
.
Usi
n
g
a
s
u
p
e
r
v
is
ed
lear
n
in
g
m
eth
o
d
o
lo
g
y
,
R
eh
m
an
et
a
l.
[
4
2
]
ev
alu
ate
s
ev
er
al
m
ac
h
i
n
e
lea
r
n
in
g
alg
o
r
ith
m
s
,
s
u
ch
as
DT
,
SVM
,
an
d
ANN
.
T
h
e
d
at
aset
is
m
ad
e
u
p
o
f
r
esp
ir
ato
r
y
s
ig
n
als
th
at
wer
e
c
ap
tu
r
ed
f
r
o
m
3
5
p
atien
ts
,
in
cl
u
d
in
g
h
ea
lth
y
p
eo
p
le
an
d
t
h
o
s
e
wh
o
h
a
d
d
if
f
er
en
t
r
esp
ir
ato
r
y
co
n
d
itio
n
s
.
T
h
e
a
u
th
o
r
s
d
iv
id
e
d
th
e
d
ataset
in
to
tr
ain
in
g
an
d
test
in
g
s
ets
b
ef
o
r
e
u
s
in
g
d
ata
au
g
m
en
tatio
n
m
eth
o
d
s
lik
e
r
a
n
d
o
m
cr
o
p
p
in
g
an
d
r
o
tatio
n
t
o
p
r
o
d
u
ce
m
o
r
e
tr
ain
i
n
g
d
ata.
T
h
en
,
u
s
in
g
m
et
r
ics
lik
e
ac
cu
r
ac
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p
r
ec
is
io
n
,
r
ec
al
l,
an
d
F1
s
co
r
e,
th
e
au
th
o
r
s
tr
ain
ed
s
ev
er
al
m
ac
h
in
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lear
n
in
g
class
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ier
s
o
n
th
e
im
p
r
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v
e
d
d
ataset.
T
h
ey
d
is
co
v
er
ed
th
at
ad
d
i
n
g
au
g
m
e
n
te
d
d
ata
in
cr
ea
s
ed
th
e
class
if
ie
r
s
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ac
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r
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with
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p
r
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d
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cin
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t
h
e
b
est o
u
tc
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m
es.
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h
e
KNN
alg
o
r
ith
m
ca
teg
o
r
izes
th
e
test
d
ata
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ased
o
n
th
e
m
ajo
r
ity
class
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f
th
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KNN
af
ter
id
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tify
in
g
t
h
e
KNN
in
th
e
t
r
ain
in
g
d
ata.
T
h
e
SVM
alg
o
r
ith
m
d
iv
id
es
th
e
d
ata
i
n
to
v
a
r
io
u
s
class
es
u
s
in
g
h
y
p
er
p
lan
es
an
d
m
ax
im
izes
th
e
d
is
tan
ce
b
etwe
en
th
e
h
y
p
er
p
lan
es
to
ac
h
iev
e
th
e
b
est
clas
s
i
f
icatio
n
.
T
h
en
,
th
e
r
an
d
o
m
f
o
r
est
(
R
F)
alg
o
r
ith
m
b
u
ild
s
m
u
ltip
le
d
ec
is
io
n
tr
ee
s
an
d
co
m
b
in
es
th
e
class
if
icatio
n
[
4
3
]
.
T
h
e
au
t
h
o
r
s
u
s
ed
ac
cu
r
ac
y
,
s
en
s
itiv
ity
,
an
d
s
p
ec
if
icity
m
etr
ics
to
ass
ess
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
th
r
ee
alg
o
r
ith
m
s
.
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o
r
d
in
g
to
th
e
r
esu
lts
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th
e
KNN
alg
o
r
ith
m
h
ad
th
e
h
i
g
h
est
ac
cu
r
ac
y
(
9
7
.
2
%),
f
o
llo
wed
b
y
th
e
SVM
alg
o
r
ith
m
(
9
4
.
6
% a
cc
u
r
ac
y
)
a
n
d
th
e
R
F a
lg
o
r
ith
m
(
9
2
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9
% a
cc
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r
ac
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)
.
T
h
e
co
m
p
a
r
is
o
n
with
d
if
f
er
en
t
m
ac
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in
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m
eth
o
d
s
was
in
clu
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ed
in
th
is
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h
e
s
y
s
tem
co
n
s
is
ts
o
f
th
r
ee
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m
p
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en
ts
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d
ata
p
r
ep
ar
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d
is
ea
s
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p
r
ed
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an
d
u
s
er
in
ter
f
ac
e
d
ev
elo
p
m
e
n
t.
Oth
er
th
an
th
at,
th
e
d
ep
en
d
ab
ilit
y
o
f
m
ac
h
in
e
lear
n
in
g
alg
o
r
ith
m
s
is
s
ig
n
if
ican
tly
im
p
ac
ted
b
y
th
ese
d
is
cr
e
p
an
cies
in
v
ar
iab
le
in
p
u
t
co
d
in
g
,
an
d
th
e
alg
o
r
ith
m
’
s
ex
ter
n
al
v
alid
ity
is
co
n
s
tr
ain
ed
b
y
th
e
v
ar
iatio
n
in
i
n
p
u
t
v
ar
iab
les
am
o
n
g
in
s
titu
tio
n
s
[
4
4
]
.
L
ik
e
s
u
b
ject
p
o
p
u
latio
n
v
ar
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n
s
,
m
ac
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g
m
o
d
el
g
e
n
er
aliza
b
il
ity
is
co
n
s
tr
ain
ed
.
T
h
en
an
o
th
e
r
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n
e
o
f
th
e
s
im
p
lest
m
ac
h
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lear
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eth
o
d
s
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co
m
p
r
e
h
en
d
is
th
e
KNN
class
if
icatio
n
tech
n
iq
u
e
[
4
5
]
.
T
h
is
r
ev
iew
[
4
6
]
r
ec
o
g
n
ize
d
p
u
lm
o
n
ar
y
ac
o
u
s
tic
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ig
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als
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lth
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v
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lu
n
teer
s
an
d
9
5
p
atien
ts
with
r
esp
ir
ato
r
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illn
ess
es.
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h
ey
t
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o
k
2
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ea
tu
r
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t
o
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th
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ig
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als
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test
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if
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with
th
em
.
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h
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tu
d
y
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s
f
in
d
in
g
s
d
em
o
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s
tr
ated
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at,
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ter
m
s
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f
ac
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r
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en
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d
s
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icity
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tp
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o
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eth
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r
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o
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ier
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s
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atis
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m
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em
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o
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ate
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in
g
class
if
ier
s
ar
e
u
s
ed
b
y
th
e
au
t
h
o
r
s
[
4
7
]
,
i
n
clu
d
in
g
NB
,
SVM
,
RF
,
KNN,
Ad
a
B
o
o
s
t,
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d
two
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p
r
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p
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p
r
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h
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o
r
m
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v
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m
b
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r
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n
d
a
co
m
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ar
is
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n
t
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lier
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attests
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u
p
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r
ity
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h
e
f
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i
n
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s
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r
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tu
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ies,
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em
o
n
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tr
atin
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p
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r
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r
d
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“
E
n
s
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atica
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p
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ea
d
m
o
v
e
m
en
t
an
d
o
b
ject
o
cc
l
u
s
io
n
[
4
8
]
.
Als
o
,
th
e
y
c
r
ea
ted
a
r
ev
o
l
u
tio
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ased
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lcu
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r
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to
m
atica
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y
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T
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p
r
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p
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alg
o
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s
ac
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itio
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m
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T
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T
a
b
le
5
[
4
2
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–
[
4
4
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,
[
4
6
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,
[
4
8
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–
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5
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s
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Evaluation Warning : The document was created with Spire.PDF for Python.
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i
s
s
t
u
d
y
t
o
m
o
re
e
x
t
en
s
i
v
e
a
n
d
mo
r
e
v
ar
i
e
d
d
a
t
a
s
e
t
s
i
s
u
n
k
n
o
w
n
K
N
N
,
SV
M
,
an
d
R
F
[
4
3
]
Brea
t
h
i
n
g
s
o
u
n
d
s
fr
o
m
p
e
rs
o
n
s
w
i
t
h
r
es
p
i
ra
t
o
r
y
p
r
o
b
l
e
ms
w
ere
reco
rd
ed
a
n
d
u
t
i
l
i
z
ed
t
o
g
en
era
t
e
s
p
ec
t
r
o
g
r
am
i
m
ag
es
.
T
h
e
i
m
ag
es
w
er
e
t
h
en
u
s
e
d
t
o
t
ra
i
n
a
C
N
N
mo
d
e
l
,
w
h
i
c
h
w
a
s
ca
p
a
b
l
e
o
f
rel
i
a
b
l
y
cl
as
s
i
f
y
i
n
g
v
ar
i
o
u
s
res
p
i
ra
t
o
ry
d
i
s
ea
s
e
s
.
T
h
e
p
o
t
en
t
i
al
o
f
u
s
i
n
g
l
u
n
g
s
o
u
n
d
s
t
o
acc
u
ra
t
e
l
y
cl
a
s
s
i
f
y
re
s
p
i
ra
t
o
r
y
l
u
n
g
d
i
s
e
as
es
fo
r
t
h
e
r
ap
i
d
a
n
d
p
rec
i
s
e
d
i
a
g
n
o
s
i
s
o
f
res
p
i
ra
t
o
ry
d
i
s
ea
s
e
s
.
U
s
ef
u
l
f
o
r
a
n
a
l
y
z
i
n
g
res
p
i
ra
t
o
ry
s
o
u
n
d
s
an
d
s
p
o
t
t
i
n
g
p
a
t
t
er
n
s
t
h
at
m
i
g
h
t
b
e
s
u
g
g
e
s
t
i
v
e
o
f
res
p
i
ra
t
o
ry
d
i
s
ea
s
e
s
O
n
l
y
res
p
i
ra
t
o
r
y
s
o
u
n
d
s
w
ere
u
s
ed
i
n
t
h
e
re
s
ear
ch
a
s
t
h
e
i
n
p
u
t
d
a
t
a
f
o
r
t
h
e
ma
ch
i
n
e
l
ear
n
i
n
g
al
g
o
r
i
t
h
ms
.
SV
M,
D
T
,
RF
,
an
d
g
ra
d
i
e
n
t
b
o
o
s
t
i
n
g
[
4
4
]
W
h
e
n
v
i
t
a
l
s
a
re
e
x
a
mi
n
e
d
m
o
re
reg
u
l
ar
l
y
,
a
n
al
g
o
r
i
t
h
m
t
ra
i
n
ed
o
n
el
ec
t
r
o
n
i
c
m
ed
i
c
al
rec
o
r
d
(
E
MR)
d
a
t
a
ma
y
l
ear
n
t
h
a
t
a
p
at
i
e
n
t
i
s
mo
r
e
p
r
o
n
e
t
o
d
ec
o
m
p
e
n
s
at
e.
U
s
i
n
g
d
a
t
a
f
ro
m
e
l
e
ct
r
o
n
i
c
h
ea
l
t
h
rec
o
r
d
s
(
E
H
R
s
)
t
o
p
re
d
i
ct
t
h
e
o
n
s
e
t
o
f
ac
u
t
e
res
p
i
ra
t
o
ry
fa
i
l
u
r
e
(
A
R
F)
an
d
a
cu
t
e
re
s
p
i
r
at
o
r
y
d
i
s
t
re
s
s
s
y
n
d
r
o
me
(
A
R
D
S)
i
n
h
o
s
p
i
t
a
l
i
ze
d
p
a
t
i
en
t
s
.
It
s
h
o
w
s
t
h
e
u
s
e
o
f
ML
t
o
an
t
i
c
i
p
at
e
t
h
e
o
n
s
e
t
o
f
A
RF
a
n
d
A
R
D
S
,
w
h
i
ch
ca
n
h
e
l
p
w
i
t
h
e
arl
y
d
i
ag
n
o
s
i
s
a
n
d
t
rea
t
m
en
t
o
f
t
h
e
s
e
i
l
l
n
e
s
s
es
a
n
d
i
mp
ro
v
e
p
a
t
i
en
t
o
u
t
co
me
s
.
T
h
e
l
ac
k
o
f
e
x
t
er
n
al
v
a
l
i
d
a
t
i
o
n
fo
r
t
h
e
m
ac
h
i
n
e
l
ear
n
i
n
g
m
o
d
el
s
i
n
t
h
e
s
t
u
d
y
res
t
r
i
ct
s
t
h
e
g
en
era
l
i
za
b
i
l
i
t
y
o
f
t
h
e
fi
n
d
i
n
g
s
b
e
y
o
n
d
t
h
e
s
t
u
d
y
'
s
p
a
t
i
e
n
t
g
ro
u
p
a
n
d
E
H
R
s
y
s
t
e
m.
K
N
N
a
n
d
SV
M
[
4
6
]
A
d
a
t
a
s
e
t
o
f
res
p
i
ra
t
o
r
y
s
o
u
n
d
s
fro
m
t
h
e
R
.
A
.
L
.
E
l
u
n
g
s
o
u
n
d
d
a
t
a
b
a
s
e
w
a
s
u
s
e
d
a
s
t
h
e
s
t
u
d
y
'
s
d
a
t
a
i
n
p
u
t
.
N
o
r
ma
l
,
ai
r
w
ay
o
b
s
t
r
u
c
t
i
o
n
p
a
t
h
o
l
o
g
y
,
a
n
d
p
are
n
c
h
y
m
al
p
at
h
o
l
o
g
y
ar
e
t
h
e
t
h
ree
cl
as
s
e
s
o
f
p
u
l
m
o
n
ar
y
aco
u
s
t
i
c
s
i
g
n
al
s
t
h
a
t
ar
e
m
an
u
a
l
l
y
cl
a
s
s
i
f
i
e
d
.
Pu
l
m
o
n
ar
y
a
co
u
s
t
i
c
s
i
g
n
al
s
can
b
e
u
s
ed
t
o
i
d
e
n
t
i
f
y
res
p
i
ra
t
o
ry
i
l
l
n
es
s
e
s
acc
u
ra
t
el
y
T
h
e
s
t
u
d
y
e
m
p
h
as
i
ze
s
t
h
e
s
i
g
n
i
fi
ca
n
ce
o
f
feat
u
r
e
s
el
ec
t
i
o
n
s
t
r
at
eg
i
e
s
t
o
d
ec
rea
s
e
t
h
e
d
i
me
n
s
i
o
n
o
f
t
h
e
d
a
t
a
an
d
en
h
a
n
c
e
cl
a
s
s
i
f
i
ca
t
i
o
n
acc
u
rac
y
.
It
o
n
l
y
u
s
e
d
a
t
i
n
y
d
a
t
a
s
et
,
w
h
i
ch
m
i
g
h
t
ma
k
e
t
h
e
fi
n
d
i
n
g
s
l
e
s
s
g
e
n
er
al
i
za
b
l
e
.
K
N
N
[
4
8
]
A
d
a
t
a
s
e
t
o
f
t
h
er
mal
ca
mera
reco
rd
i
n
g
s
o
f
h
u
ma
n
n
o
s
t
r
i
l
s
fro
m
h
ea
l
t
h
y
ad
u
l
t
s
an
d
b
a
b
i
e
s
w
a
s
u
s
e
d
a
s
t
h
e
s
t
u
d
y
'
s
d
at
a
i
n
p
u
t
.
T
h
e
b
r
ea
t
h
i
n
g
ra
t
e
i
s
l
a
b
e
l
l
e
d
o
n
t
h
e
rec
o
r
d
i
n
g
s
a
s
n
o
rma
l
o
r
a
b
n
o
r
ma
l
.
T
h
e
r
es
u
l
t
i
n
g
re
s
p
i
rat
i
o
n
w
a
v
ef
o
r
m
i
s
s
u
b
s
e
q
u
en
t
l
y
p
r
o
ce
s
s
e
d
w
i
t
h
t
h
e
ap
p
r
o
p
ri
at
e
f
i
l
t
er
i
n
g
t
ec
h
n
i
q
u
e
s
t
o
i
n
c
rea
s
e
t
h
e
s
i
g
n
a
l
-
to
-
n
o
i
s
e
ra
t
i
o
(SN
R).
T
h
e
s
u
g
g
e
s
t
e
d
al
g
o
ri
t
h
m
ca
n
d
i
s
c
ri
mi
n
a
t
e
b
e
t
w
ee
n
fas
t
a
n
d
s
l
o
w
res
p
i
ra
t
i
o
n
a
n
d
b
e
t
w
ee
n
n
o
rma
l
an
d
ab
n
o
rma
l
b
r
eat
h
s
,
w
h
i
ch
ca
n
h
e
l
p
d
i
ag
n
o
s
e
a
n
d
t
re
at
res
p
i
ra
t
o
ry
i
l
l
n
es
s
e
s
.
T
h
e
r
es
earc
h
d
o
e
s
n
o
t
men
t
i
o
n
t
h
e
p
erf
o
rma
n
c
e
o
f
t
h
e
p
r
o
p
o
s
e
d
al
g
o
ri
t
h
m
co
m
p
a
re
d
t
o
p
re
v
i
o
u
s
n
o
n
-
co
n
t
ac
t
re
s
p
i
rat
o
r
y
mo
n
i
t
o
r
i
n
g
al
g
o
r
i
t
h
ms
.
T
h
eref
o
r
e,
h
o
w
t
h
e
s
u
g
g
e
s
t
e
d
al
g
o
ri
t
h
m
s
t
ac
k
s
u
p
a
g
a
i
n
s
t
o
t
h
e
r
c
u
t
t
i
n
g
-
e
d
g
e
t
ec
h
n
i
q
u
e
s
i
s
u
n
k
n
o
w
n
w
i
t
h
o
u
t
t
h
i
s
co
m
p
a
ri
s
o
n
.
N
a
ï
v
e
B
ay
es
[4
9
]
T
h
e
e
x
h
a
l
e
d
a
i
rf
l
o
w
c
o
l
l
ec
t
e
d
b
y
t
h
e
m
i
cr
o
p
h
o
n
e
s
er
v
e
s
a
s
t
h
e
i
n
p
u
t
d
a
t
a
f
o
r
t
h
e
rea
l
-
t
i
me
co
n
t
ac
t
l
e
s
s
r
es
p
i
ra
t
i
o
n
mo
n
i
t
o
r
i
n
g
s
y
s
t
em
.
T
h
e
ai
r
fl
o
w
i
s
c
o
n
v
ert
ed
i
n
t
o
a
n
el
ec
t
ri
ca
l
s
i
g
n
a
l
v
i
a
t
h
e
mi
cr
o
p
h
o
n
e
,
w
h
i
ch
i
s
t
h
e
n
an
a
l
y
ze
d
u
s
i
n
g
b
l
i
n
d
s
o
u
r
ce
s
e
p
ara
t
i
o
n
(BSS
)
a
n
d
t
h
e
N
B
cl
a
s
s
i
f
i
er
.
E
m
p
l
o
y
i
n
g
BSS
e
n
a
b
l
es
t
h
e
I
CA
a
l
g
o
r
i
t
h
m
t
o
d
i
s
t
i
n
g
u
i
s
h
b
e
t
w
ee
n
res
p
i
ra
t
o
ry
s
i
g
n
al
s
.
W
h
e
n
u
s
e
d
f
o
r
d
i
s
e
as
e
cat
e
g
o
r
i
za
t
i
o
n
,
t
h
e
N
a
v
e
Ba
y
e
s
c
l
a
s
s
i
f
i
e
r
i
s
c
o
m
p
u
t
a
t
i
o
n
a
l
l
y
effec
t
i
v
e
a
n
d
ca
n
p
r
o
d
u
c
e
g
o
o
d
re
s
u
l
t
s
w
i
t
h
l
i
m
i
t
e
d
d
at
a
s
et
s
.
E
x
t
e
rn
al
e
l
eme
n
t
s
l
i
k
e
n
o
i
s
e
an
d
mo
t
i
o
n
art
efac
t
s
c
o
u
l
d
h
a
v
e
an
i
m
p
ac
t
o
n
t
h
i
s
.
L
D
A
,
SV
M,
FN
N
,
D
T
,
R
F,
an
d
A
N
N
[
5
0
]
A
d
a
t
a
s
e
t
o
f
b
r
eat
h
i
n
g
s
o
u
n
d
s
i
s
u
s
ed
a
s
i
n
p
u
t
f
o
r
t
h
e
re
s
p
i
ra
t
o
r
y
p
a
t
t
ern
c
l
a
s
s
i
f
i
ca
t
i
o
n
t
a
s
k
.
T
h
e
d
a
t
a
s
et
i
n
c
l
u
d
e
s
re
co
rd
i
n
g
s
o
f
res
p
i
ra
t
o
ry
s
o
u
n
d
s
fro
m
b
o
t
h
h
ea
l
t
h
y
p
e
o
p
l
e
a
n
d
p
e
o
p
l
e
w
i
t
h
res
p
i
ra
t
o
ry
d
i
s
o
rd
ers
.
S
o
me
o
f
t
h
e
reco
rd
i
n
g
s
i
n
t
h
e
co
l
l
ec
t
i
o
n
h
a
v
e
mi
s
s
i
n
g
d
a
t
a
s
i
n
c
e
t
h
ey
w
ere
mad
e
i
n
l
o
u
d
e
n
v
i
ro
n
m
en
t
s
.
T
h
e
i
s
s
u
e
o
f
m
i
s
s
i
n
g
d
at
a
i
n
re
s
p
i
r
at
o
r
y
s
i
g
n
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I
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ased
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ask
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[
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ased
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h
is
d
iv
id
ed
in
to
f
o
u
r
s
tep
s
:
f
ea
tu
r
e
e
x
tr
ac
tio
n
,
n
o
is
e
m
ask
in
g
,
clas
s
if
icatio
n
,
an
d
d
ata
p
r
e
-
p
r
o
ce
s
s
in
g
.
First,
th
e
au
th
o
r
s
r
ec
o
r
d
p
atien
t
r
esp
ir
atio
n
s
o
u
n
d
s
with
a
d
ig
ital
s
teth
o
s
c
o
p
e
d
u
r
in
g
th
e
d
ata
p
r
ep
ar
atio
n
s
tag
e.
Af
ter
th
at,
th
e
d
ata
is
p
r
e
-
p
r
o
ce
s
s
ed
to
eli
m
in
ate
an
y
n
o
is
e
an
d
a
r
tef
ac
ts
.
Nex
t,
th
e
au
th
o
r
s
ap
p
ly
a
STFT
to
tu
r
n
ea
c
h
s
eg
m
en
t
in
to
a
s
p
ec
tr
o
g
r
am
r
e
p
r
esen
tatio
n
d
u
r
in
g
th
e
f
ea
tu
r
e
ex
tr
ac
tio
n
s
tag
e.
T
h
en
,
to
ex
tr
ac
t
p
er
tin
e
n
t
f
ea
tu
r
es
f
r
o
m
th
e
r
esp
ir
ato
r
y
s
o
u
n
d
s
,
th
e
s
p
ec
tr
o
g
r
am
is
p
ass
ed
to
a
tr
ain
ed
R
NN.
Nex
t,
to
in
cr
ea
s
e
th
e
r
o
b
u
s
tn
e
s
s
o
f
th
e
R
NN
to
f
lu
ctu
atio
n
s
in
r
esp
ir
ato
r
y
s
o
u
n
d
s
,
t
h
e
s
ci
en
tis
ts
ad
d
r
a
n
d
o
m
Gau
s
s
ian
n
o
is
e
to
th
e
r
etr
ie
v
ed
f
ea
tu
r
es
d
u
r
in
g
th
e
n
o
is
e
m
ask
in
g
s
tag
e.
Fin
ally
,
t
h
e
f
ea
tu
r
es
with
th
e
ad
d
itio
n
al
n
o
is
e
ar
e
u
tili
ze
d
to
p
r
ed
ict
th
e
p
r
esen
ce
o
r
ab
s
en
ce
o
f
r
esp
ir
ato
r
y
illn
ess
es
d
u
r
in
g
th
e
class
if
icatio
n
s
tag
e.
Mo
r
eo
v
er
,
Alq
u
d
ah
et
a
l.
[
6
3
]
f
o
cu
s
ed
o
n
u
s
in
g
s
ev
er
al
d
e
ep
lear
n
in
g
m
o
d
els,
as
d
em
o
n
s
tr
ated
b
y
th
e
co
m
b
in
atio
n
o
f
C
NN
an
d
L
STM
n
eu
r
al
n
etwo
r
k
s
.
T
h
e
d
ev
elo
p
e
d
m
o
d
els
attain
ed
h
ig
h
lev
els
o
f
p
er
f
o
r
m
an
ce
.
T
h
e
h
y
b
r
id
C
NN
-
L
STM
m
o
d
el
y
ield
ed
th
e
h
ig
h
est
ac
cu
r
ac
y
,
s
en
s
itiv
ity
,
an
d
s
p
ec
if
icity
r
esu
lts
,
wh
ich
p
av
e
th
e
p
ath
f
o
r
ap
p
ly
in
g
d
ee
p
lear
n
in
g
i
n
clin
ical
co
n
tex
ts
at
1
0
0
%,
1
0
0
%,
an
d
1
0
0
%,
r
esp
ec
tiv
ely
.
T
h
is
p
ap
er
r
ev
iewe
d
p
r
o
p
o
s
ed
a
d
ee
p
lear
n
in
g
m
o
d
el
b
ased
o
n
a
co
m
b
i
n
atio
n
o
f
L
STM
,
C
NNs,
an
d
b
o
th
.
As
class
if
icatio
n
tech
n
iq
u
es,
v
ar
i
o
u
s
d
ee
p
lear
n
in
g
m
o
d
els
lik
e
C
NN,
L
STM
,
an
d
C
NN
-
L
STM
wer
e
u
s
ed
,
an
d
th
e
r
esu
lts
wer
e
co
m
p
ar
ed
.
Acc
o
r
d
in
g
to
th
e
ex
p
er
im
en
t
al
f
in
d
in
g
s
,
th
e
h
y
b
r
id
C
NN
-
L
STM
class
if
icatio
n
m
o
d
el
p
er
f
o
r
m
s
b
etter
th
an
th
e
C
NN
an
d
L
STM
m
eth
o
d
s
f
r
eq
u
e
n
tly
u
s
ed
in
th
e
liter
atu
r
e.
T
h
r
o
u
g
h
d
ev
elo
p
in
g
a
n
d
a
p
p
ly
in
g
d
ee
p
lear
n
in
g
m
o
d
els
in
clin
ical
co
n
tex
ts
,
th
is
r
esear
ch
p
av
es
t
h
e
p
ath
f
o
r
d
o
cto
r
s
to
m
ak
e
h
ig
h
ly
ac
cu
r
ate
d
ec
is
io
n
s
.
T
h
er
ef
o
r
e,
ac
co
r
d
in
g
to
th
e
p
ap
er
s
th
at
h
av
e
b
ee
n
r
e
v
iewe
d
,
it
is
s
h
o
wn
th
at
C
NNs i
s
th
e
m
o
s
t p
o
p
u
lar
d
ee
p
lear
n
in
g
alg
o
r
ith
m
u
s
ed
to
cl
ass
if
y
th
e
r
esp
ir
atio
n
r
ate
s
y
s
tem
.
Kim
et
a
l
.
[
6
4
]
s
u
g
g
ests
u
s
in
g
d
ee
p
lear
n
in
g
to
class
if
y
r
esp
ir
ato
r
y
s
o
u
n
d
s
s
u
ch
a
s
cr
ac
k
les,
wh
ee
ze
s
,
an
d
r
h
o
n
c
h
i
in
th
e
clin
ical
s
ettin
g
.
I
t
i
s
f
o
u
n
d
th
at
1
,
918
d
atasets
o
f
r
esp
ir
ato
r
y
s
o
u
n
d
s
ca
p
tu
r
e
d
in
a
clin
ical
co
n
tex
t
was
d
iv
i
d
ed
i
n
to
ca
teg
o
r
ies
b
y
t
h
e
au
th
o
r
u
s
in
g
d
ee
p
lea
r
n
in
g
C
NN.
B
y
f
u
s
in
g
a
p
r
e
-
tr
ain
e
d
p
ictu
r
e
f
ea
tu
r
e
ex
tr
ac
to
r
o
f
s
er
ies,
r
esp
ir
ato
r
y
s
o
u
n
d
,
an
d
C
NN
class
if
ier
,
th
ey
cr
ea
te
a
p
r
ed
ictio
n
m
o
d
el
f
o
r
r
esp
ir
ato
r
y
s
o
u
n
d
class
if
icatio
n
.
T
h
e
au
th
o
r
s
s
tate
th
at
th
eir
wo
r
k
p
r
o
v
id
es
g
o
o
d
class
if
icatio
n
ac
cu
r
ac
y
f
o
r
r
esp
ir
ato
r
y
s
o
u
n
d
s
,
alth
o
u
g
h
t
h
e
ca
teg
o
r
izatio
n
ex
clu
d
es p
n
eu
m
o
n
ia.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
9
2
9
-
6
9
4
3
6938
T
h
e
au
th
o
r
class
if
ies
th
e
d
ata
in
to
s
ev
er
al
r
esp
ir
atio
n
p
atter
n
s
,
s
u
ch
as
ty
p
ical
r
esp
ir
atio
n
,
s
h
allo
w
r
esp
ir
atio
n
,
d
ee
p
r
esp
ir
atio
n
,
a
n
d
r
a
p
id
r
esp
ir
atio
n
,
u
s
in
g
a
d
ee
p
lear
n
in
g
tech
n
i
q
u
e,
n
am
el
y
a
C
NN
[
6
5
]
.
T
h
e
s
tu
d
y
f
o
u
n
d
th
at
th
e
s
u
g
g
es
ted
s
tr
ateg
y
h
ig
h
ly
ac
cu
r
atel
y
class
if
ied
v
ar
io
u
s
r
esp
ir
atio
n
p
atter
n
s
u
s
in
g
in
f
o
r
m
atio
n
g
ath
er
ed
f
r
o
m
w
ea
r
ab
le
s
en
s
o
r
s
.
T
o
f
u
r
th
er
h
i
g
h
lig
h
t
th
e
p
o
ten
tial
f
o
r
clin
i
ca
l
ap
p
licatio
n
s
,
th
e
au
th
o
r
s
also
d
em
o
n
s
tr
ated
h
o
w
th
eir
tech
n
iq
u
e
m
ig
h
t b
e
u
s
ed
to
d
etec
t r
esp
ir
atio
n
p
atter
n
s
in
r
ea
l
-
tim
e.
Usi
n
g
a
co
n
v
o
lu
tio
n
al
n
eu
r
al
n
etwo
r
k
,
[
5
5
]
s
u
g
g
ests
class
if
y
in
g
r
e
s
p
ir
ato
r
y
s
o
u
n
d
s
.
T
o
ac
h
iev
e
th
is
,
th
ey
cr
ea
te
d
a
v
is
u
al
r
ep
r
esen
tatio
n
o
f
ea
ch
au
d
io
s
am
p
le
th
at
allo
ws
id
en
tify
in
g
r
eso
u
r
ce
s
f
o
r
class
if
icatio
n
u
s
in
g
th
e
s
am
e
tech
n
iq
u
es
u
s
ed
to
class
if
y
i
m
ag
es
with
h
ig
h
p
r
ec
is
io
n
.
T
h
ey
also
ex
t
r
ac
ted
r
eso
u
r
ce
s
u
s
in
g
Mel
f
r
e
q
u
en
c
y
ce
p
s
tr
al
co
ef
f
icien
ts
(
MFC
C
s
)
to
class
if
y
r
esp
ir
at
o
r
y
d
is
ea
s
es.
T
h
er
ef
o
r
e,
T
ab
le
6
s
u
m
m
a
r
i
ze
s
th
e
ad
v
an
tag
es
an
d
d
is
ad
v
a
n
tag
es o
f
u
s
in
g
a
d
ee
p
lear
n
in
g
alg
o
r
ith
m
.
T
ab
le
2
.
T
h
e
ad
v
a
n
tag
es a
n
d
d
is
ad
v
an
tag
es o
f
u
s
in
g
a
d
ee
p
l
ea
r
n
in
g
alg
o
r
ith
m
A
l
g
o
r
i
t
h
m
D
a
t
a
i
n
p
u
t
Fi
n
d
i
n
g
A
d
v
an
t
a
g
e
L
i
mi
t
a
t
i
o
n
CN
N
,
R
N
N
an
d
h
y
b
ri
d
CN
N
+
R
N
N
[5
3
]
A
d
a
t
a
s
e
t
o
f
s
p
ee
ch
d
at
a
i
s
u
s
e
d
as
t
h
e
s
t
u
d
y
’s
d
at
a
i
n
p
u
t
.
T
h
e
d
at
a
i
s
g
a
t
h
ere
d
f
ro
m
a
v
ar
i
et
y
o
f
s
p
ea
k
er
s
,
i
n
c
l
u
d
i
n
g
t
h
o
s
e
w
h
o
ar
e
h
ea
l
t
h
y
an
d
t
h
o
s
e
w
h
o
h
av
e
res
p
i
ra
t
o
ry
c
o
n
d
i
t
i
o
n
s
.
Su
g
g
es
t
a
u
n
i
q
u
e
me
t
h
o
d
f
o
r
es
t
i
mat
i
n
g
re
s
p
i
ra
t
o
r
y
p
ara
me
t
er
s
f
ro
m
s
p
eec
h
reco
rd
i
n
g
s
u
s
i
n
g
d
e
ep
l
ear
n
i
n
g
arc
h
i
t
ect
u
r
es
.
T
h
i
s
s
t
u
d
y
s
h
o
w
s
t
h
a
t
t
h
e
s
u
g
g
e
s
t
ed
m
et
h
o
d
ca
n
es
t
i
mat
e
r
es
p
i
ra
t
o
ry
p
ara
me
t
er
s
w
i
t
h
h
i
g
h
acc
u
rac
y
an
d
l
i
t
t
l
e
err
o
r.
T
h
e
s
m
a
l
l
s
a
m
p
l
e
s
i
z
e
m
a
y
a
f
f
e
c
t
h
o
w
g
e
n
e
r
a
l
i
z
a
b
l
e
t
h
e
f
i
n
d
i
n
g
s
a
r
e
a
n
d
t
h
e
a
b
s
e
n
c
e
o
f
c
o
m
p
a
r
i
s
o
n
s
w
i
t
h
e
s
t
a
b
l
i
s
h
e
d
t
e
c
h
n
i
q
u
e
s
f
o
r
m
e
a
s
u
r
i
n
g
r
e
s
p
i
r
a
t
o
r
y
p
a
r
a
m
e
t
e
r
s
.
CN
N
an
d
A
N
N
[
5
9
]
T
h
e
s
t
u
d
y
’
s
d
a
t
a
i
n
p
u
t
i
s
a
d
a
t
a
s
e
t
o
f
d
i
g
i
t
a
l
re
s
p
i
ra
t
o
r
y
s
o
u
n
d
s
.
T
h
e
o
p
t
i
m
i
ze
d
S
-
T
ra
n
s
fo
rm
i
s
a
s
i
g
n
al
p
r
o
ce
s
s
i
n
g
a
p
p
r
o
ac
h
fo
r
emp
h
a
s
i
z
i
n
g
t
h
e
ch
arac
t
e
ri
s
t
i
c
s
o
f
w
h
eez
e,
crac
k
l
e,
a
n
d
n
o
rma
l
n
o
i
s
e
s
.
Su
g
g
es
t
a
n
o
v
el
t
e
ch
n
i
q
u
e
f
o
r
reco
g
n
i
zi
n
g
w
h
ee
ze,
cra
ck
l
e
,
an
d
n
o
rma
l
re
s
p
i
ra
t
o
r
y
s
o
u
n
d
s
u
t
i
l
i
z
i
n
g
d
ee
p
r
es
i
d
u
al
n
e
t
w
o
r
k
s
a
n
d
o
p
t
i
mal
S
-
t
ra
n
s
fo
rm
(O
ST
)
(
Res
N
et
s
).
In
t
h
e
mu
l
t
i
-
cl
as
s
i
fi
ca
t
i
o
n
o
f
res
p
i
ra
t
o
ry
s
o
u
n
d
s
,
t
h
e
s
u
g
g
e
s
t
ed
m
et
h
o
d
u
s
i
n
g
o
p
t
i
ma
l
S
-
t
ra
n
s
fo
r
m
(
O
S
T
)
an
d
d
ee
p
re
s
i
d
u
a
l
n
e
t
w
o
r
k
s
(Res
N
et
s
)
s
h
o
w
ed
g
o
o
d
acc
u
rac
y
,
s
en
s
i
t
i
v
i
t
y
,
an
d
s
p
ec
i
fi
ci
t
y
.
T
h
e
s
t
u
d
y
d
i
d
n
o
t
c
o
mp
are
t
h
e
p
r
o
p
o
s
e
d
me
t
h
o
d
t
o
o
t
h
er
cu
t
t
i
n
g
-
e
d
g
e
a
p
p
r
o
ac
h
e
s
t
h
at
u
s
e
v
ar
i
o
u
s
fea
t
u
re
ex
t
ra
ct
i
o
n
an
d
c
l
a
s
s
i
f
i
c
at
i
o
n
s
t
ra
t
e
g
i
e
s
,
w
h
i
ch
m
i
g
h
t
h
a
v
e
re
v
ea
l
e
d
mo
r
e
i
n
fo
r
ma
t
i
o
n
a
b
o
u
t
t
h
e
p
erf
o
r
ma
n
ce
o
f
t
h
e
s
u
g
g
e
s
t
ed
met
h
o
d
.
RN
N
[6
1
]
Pat
i
e
n
t
s
w
i
t
h
a
ra
n
g
e
o
f
r
es
p
i
ra
t
o
ry
d
i
s
e
as
es
c
o
n
t
r
i
b
u
t
e
d
t
o
a
d
at
as
e
t
o
f
res
p
i
ra
t
o
ry
a
u
s
cu
l
t
at
i
o
n
s
o
u
n
d
d
a
t
a.
T
o
cr
ea
t
e
d
a
t
a
fea
t
u
re
s
re
l
a
t
e
d
t
o
res
p
i
ra
t
o
ry
i
l
l
n
es
s
e
s
,
t
h
e
d
at
a
w
a
s
p
re
-
p
r
o
c
es
s
e
d
u
s
i
n
g
s
t
at
e
-
of
-
t
h
e
-
ar
t
feat
u
r
e
e
x
t
rac
t
i
o
n
me
t
h
o
d
s
.
T
h
e
a
p
p
r
o
ac
h
s
u
g
g
es
t
e
d
i
n
t
h
i
s
p
a
p
er
i
s
w
e
l
l
-
d
e
s
i
g
n
e
d
an
d
e
ffi
ci
en
t
i
n
u
s
i
n
g
l
u
n
g
s
o
u
n
d
s
t
o
p
r
ed
i
c
t
r
es
p
i
ra
t
o
r
y
ab
n
o
rma
l
i
t
i
e
s
a
n
d
i
l
l
n
e
s
s
es
.
T
h
e
a
l
g
o
ri
t
h
m
h
as
h
i
g
h
acc
u
rac
y
i
n
i
d
en
t
i
f
y
i
n
g
res
p
i
ra
t
o
ry
a
b
n
o
r
ma
l
i
t
i
es
an
d
d
i
s
o
r
d
er
s
,
ma
k
i
n
g
i
t
a
rel
i
a
b
l
e
t
o
o
l
f
o
r
re
s
p
i
r
at
o
r
y
cat
e
g
o
r
i
za
t
i
o
n
.
T
h
e
a
l
g
o
ri
t
h
m
ca
n
o
n
l
y
cat
e
g
o
r
i
ze
re
s
p
i
r
at
o
r
y
ab
n
o
rma
l
i
t
i
e
s
a
n
d
d
i
s
ea
s
es
b
a
s
e
d
o
n
l
u
n
g
s
o
u
n
d
s
.
N
o
i
s
e
mas
k
i
n
g
recu
rre
n
t
n
e
u
ra
l
n
e
t
w
o
r
k
(N
M
R
N
N
)
[6
2
]
A
d
a
t
a
s
e
t
o
f
l
u
n
g
s
o
u
n
d
d
at
a
w
a
s
u
s
ed
a
s
t
h
e
s
t
u
d
y
’
s
d
a
t
a
i
n
p
u
t
.
D
at
a
i
s
g
at
h
e
re
d
fr
o
m
p
at
i
e
n
t
s
s
u
f
fer
i
n
g
fro
m
v
ar
i
o
u
s
r
es
p
i
ra
t
o
r
y
d
i
s
o
r
d
er
s
.
T
h
e
a
l
g
o
ri
t
h
m
at
t
e
mp
t
s
t
o
i
s
o
l
a
t
e
o
n
l
y
cr
i
t
i
ca
l
res
p
i
ra
t
o
ry
-
l
i
k
e
fr
ame
s
free
o
f
ex
t
ra
n
e
o
u
s
n
o
i
s
e
a
n
d
cl
a
s
s
i
f
i
e
s
l
u
n
g
s
o
u
n
d
s
i
n
t
o
fo
u
r
g
r
o
u
p
s
:
n
o
rma
l
,
co
n
t
ai
n
i
n
g
w
h
e
eze
s
,
co
n
t
ai
n
i
n
g
crac
k
l
e
s
,
a
n
d
co
n
t
ai
n
i
n
g
b
o
t
h
w
h
eeze
s
an
d
crac
k
l
es
.
T
h
e
c
o
mp
u
t
a
t
i
o
n
a
l
c
o
s
t
a
n
d
t
i
me
n
e
ed
ed
f
o
r
f
eat
u
r
e
ex
t
rac
t
i
o
n
are
d
ecre
as
e
d
b
y
t
h
e
N
M
RN
N
a
l
g
o
r
i
t
h
m,
w
h
i
ch
eff
ect
i
v
e
l
y
e
x
t
rac
t
s
p
er
t
i
n
e
n
t
f
ea
t
u
r
es
fr
o
m
l
u
n
g
s
o
u
n
d
s
u
s
i
n
g
a
p
re
-
t
r
ai
n
e
d
RN
N
.
T
h
e
N
M
R
N
N
a
l
g
o
r
i
t
h
m,
l
i
k
e
man
y
d
ee
p
l
ear
n
i
n
g
al
g
o
r
i
t
h
m
s
,
i
s
t
ri
c
k
y
t
o
i
n
t
er
p
r
et
,
m
ak
i
n
g
i
t
ch
a
l
l
e
n
g
i
n
g
t
o
c
o
m
p
re
h
e
n
d
h
o
w
i
t
g
e
n
e
rat
es
i
t
s
p
re
d
i
c
t
i
o
n
s
.
CN
N
-
L
T
SM
[
6
3
]
A
d
a
t
a
s
e
t
o
f
ra
w
l
u
n
g
au
s
c
u
l
t
at
i
o
n
s
o
u
n
d
s
w
a
s
u
s
ed
a
s
t
h
e
s
t
u
d
y
’s
d
a
t
a
i
n
p
u
t
.
D
at
a
i
s
g
at
h
er
ed
fr
o
m
p
a
t
i
en
t
s
s
u
ffer
i
n
g
fr
o
m
v
ari
o
u
s
res
p
i
ra
t
o
ry
d
i
s
o
rd
ers
.
T
h
i
s
s
t
u
d
y
f
o
c
u
s
e
s
o
n
a
p
p
l
y
i
n
g
d
e
e
p
l
e
a
r
n
i
n
g
m
o
d
e
l
s
f
o
r
d
e
t
e
c
t
i
n
g
r
e
s
p
i
r
a
t
o
r
y
d
i
s
e
a
s
e
s
u
t
i
l
i
z
i
n
g
r
a
w
l
u
n
g
a
u
s
c
u
l
t
a
t
i
o
n
s
o
u
n
d
s
.
I
t
e
m
p
h
a
s
i
z
e
s
t
h
e
s
i
g
n
i
f
i
c
a
n
c
e
o
f
c
h
o
o
s
i
n
g
s
u
i
t
a
b
l
e
d
e
e
p
l
e
a
r
n
i
n
g
m
o
d
e
l
s
f
o
r
t
h
i
s
t
a
s
k
.
E
v
al
u
a
t
i
n
g
v
ari
o
u
s
d
ee
p
l
ear
n
i
n
g
m
o
d
el
s
o
n
b
o
t
h
au
g
me
n
t
e
d
a
n
d
n
o
n
-
au
g
me
n
t
e
d
d
a
t
a
s
e
t
s
o
ffer
s
a
t
h
o
r
o
u
g
h
a
n
a
l
y
s
i
s
o
f
v
ar
i
o
u
s
met
h
o
d
s
fo
r
d
i
ag
n
o
s
i
n
g
res
p
i
ra
t
o
ry
d
i
s
ea
s
e
s
.
T
h
e
s
t
u
d
y
i
s
c
o
n
s
t
ra
i
n
e
d
b
y
t
h
e
co
m
p
a
rat
i
v
e
l
y
s
ma
l
l
d
at
as
et
s
i
ze,
w
h
i
c
h
c
an
aff
ec
t
h
o
w
b
r
o
a
d
l
y
t
h
e
fi
n
d
i
n
g
s
ca
n
b
e
ap
p
l
i
e
d
.
CN
N
[6
5
]
T
h
e
s
t
u
d
y
’
s
d
a
t
a
i
n
p
u
t
i
s
a
d
a
t
a
s
e
t
co
m
p
r
i
s
i
n
g
a
cce
l
er
o
m
et
er
a
n
d
g
y
ro
s
c
o
p
i
c
d
a
t
a.
T
h
e
i
n
fo
r
ma
t
i
o
n
w
a
s
g
a
t
h
ere
d
fro
m
1
0
0
h
ea
l
t
h
y
i
n
d
i
v
i
d
u
a
l
s
w
h
o
s
i
m
u
l
at
ed
v
ari
o
u
s
b
rea
t
h
i
n
g
ep
i
s
o
d
e
s
.
T
h
e
w
e
ara
b
l
e
s
e
n
s
o
r
s
an
d
d
ee
p
l
e
arn
i
n
g
ar
e
c
o
m
b
i
n
e
d
t
o
p
re
s
e
n
t
a
n
o
v
e
l
a
p
p
r
o
ac
h
fo
r
cl
a
s
s
i
f
y
i
n
g
a
n
d
d
et
ect
i
n
g
res
p
i
ra
t
i
o
n
p
a
t
t
er
n
s
.
T
h
e
u
s
e
o
f
w
eara
b
l
e
s
e
n
s
o
rs
t
o
c
o
l
l
e
ct
d
at
a
o
n
re
s
p
i
r
at
i
o
n
p
a
t
t
ern
s
,
t
h
e
d
ee
p
CN
N
u
s
ed
f
o
r
cl
a
s
s
i
fi
cat
i
o
n
,
an
d
t
h
e
h
i
g
h
l
e
v
e
l
o
f
acc
u
ra
cy
at
t
ai
n
e
d
w
h
i
l
e
c
l
a
s
s
i
f
y
i
n
g
v
ar
i
o
u
s
res
p
i
ra
t
i
o
n
p
a
t
t
er
n
s
.
U
s
i
n
g
a
l
i
m
i
t
e
d
s
am
p
l
e
s
i
ze
co
u
l
d
affe
ct
h
o
w
g
e
n
e
ral
i
z
ab
l
e
t
h
e
f
i
n
d
i
n
g
s
are
.
CN
N
s
[
6
6
]
T
h
e
s
t
u
d
y
’
s
d
a
t
a
i
n
p
u
t
i
s
a
d
a
t
a
s
e
t
o
f
r
es
p
i
ra
t
o
r
y
s
o
u
n
d
d
a
t
a.
T
h
e
i
n
fo
rma
t
i
o
n
i
s
g
a
t
h
ere
d
f
ro
m
p
a
t
i
en
t
s
s
u
ffer
i
n
g
fr
o
m
v
ari
o
u
s
res
p
i
ra
t
o
ry
d
i
s
o
rd
ers
.
F
o
u
r
i
er
an
a
l
y
s
i
s
i
s
a
ma
t
h
ema
t
i
ca
l
ap
p
r
o
ac
h
fo
r
s
ep
ara
t
i
n
g
a
s
i
g
n
a
l
'
s
co
n
s
t
i
t
u
e
n
t
fr
eq
u
e
n
c
i
e
s
.
T
h
i
s
c
an
b
e
u
s
e
d
t
o
v
i
s
u
a
l
i
ze
a
s
i
g
n
al
’s
s
p
ec
t
r
u
m,
w
h
i
c
h
ca
n
t
h
en
b
e
u
s
ed
t
o
d
i
s
t
i
n
g
u
i
s
h
d
i
f
fere
n
t
s
o
rt
s
o
f
s
o
u
n
d
s
.
T
h
i
s
s
t
u
d
y
p
r
o
p
o
s
e
d
t
o
c
rea
t
e
an
au
g
me
n
t
e
d
d
at
a
s
e
t
.
T
h
e
au
t
h
o
r
s
fi
r
s
t
a
d
d
s
y
n
t
h
e
t
i
c
n
o
i
s
e
t
o
t
h
e
o
r
i
g
i
n
a
l
res
p
i
ra
t
o
ry
s
o
u
n
d
s
.
T
h
e
s
o
u
n
d
s
are
t
h
e
n
d
i
v
i
d
e
d
i
n
t
o
fo
u
r
g
r
o
u
p
s
u
s
i
n
g
a
d
ee
p
CN
N
:
n
o
rma
l
,
w
h
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