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I
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4864
I
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Ma
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2025
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35
-
47
36
lif
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h
o
ar
e
liv
i
n
g
alo
n
e
at
h
o
m
e,
h
o
m
ec
ar
e
r
es
ea
r
ch
is
p
ar
ticu
lar
l
y
i
m
p
o
r
ta
n
t
in
s
o
lv
i
n
g
th
e
a
g
in
g
is
s
u
e
.
A
p
p
r
o
ac
h
es
lik
e
ca
m
er
a
-
b
ased
m
o
n
ito
r
i
n
g
a
n
d
w
ea
r
ab
le
b
as
ed
s
m
ar
t
d
ev
ices
w
er
e
tr
ied
b
u
t
d
id
n
o
t
g
e
t
th
e
r
esu
lt
s
as
e
x
p
ec
ted
[
6
]
.
T
h
e
ca
r
eg
iv
er
s
ar
e
n
o
w
b
ein
g
tr
ai
n
ed
u
s
in
g
A
I
r
o
b
o
ts
w
h
ich
u
s
e
v
is
u
al
b
ased
f
ee
d
b
ac
k
s
u
c
h
as
p
ain
lev
e
l
w
h
ic
h
g
i
v
es
tr
ain
ee
s
m
o
r
e
ex
p
er
ien
ce
[
7
]
.
R
o
b
o
tics
an
d
A
I
to
g
eth
er
h
av
e
a
b
r
ig
h
t
f
u
tu
r
e
in
eld
er
l
y
ca
r
e
an
d
ass
is
tiv
e
tec
h
n
o
lo
g
ies.
T
h
e
p
r
o
p
o
s
ed
s
y
s
te
m
ai
m
s
to
en
h
an
ce
t
h
e
q
u
alit
y
o
f
li
f
e
b
y
p
r
o
v
id
in
g
d
i
g
ital
co
m
p
a
n
io
n
s
h
ip
an
d
m
as
s
ag
e
t
h
er
ap
y
to
th
e
eld
er
ly
.
T
h
ese
o
b
j
ec
tiv
es
ar
e
ac
h
iev
ed
b
y
i
n
teg
r
ati
n
g
an
elec
tr
o
n
ic
s
y
s
te
m
o
f
en
d
ef
f
ec
t
o
r
s
w
i
th
an
A
I
d
r
iv
en
co
n
v
er
s
atio
n
a
l
ass
i
s
tan
t.
T
h
e
ass
is
ta
n
t
is
d
esi
g
n
ed
to
g
en
er
ate
a
s
tip
u
late
d
r
esp
o
n
s
e
b
y
a
n
al
y
zi
n
g
t
h
e
i
n
ten
t
a
n
d
e
m
o
tio
n
b
eh
i
n
d
t
h
e
u
s
er
’
s
i
n
p
u
t.
A
n
o
v
el
i
n
te
n
t
r
ec
o
g
n
itio
n
s
y
s
te
m
u
s
i
n
g
f
e
w
-
s
h
o
t le
ar
n
i
n
g
an
d
a
f
i
n
e
-
t
u
n
ed
e
m
o
tio
n
cla
s
s
i
f
ier
i
s
p
r
o
p
o
s
ed
.
T
h
e
A
I
as
s
is
tan
t
d
ec
id
es th
e
r
e
s
p
o
n
s
e
b
y
cla
s
s
i
f
y
in
g
u
s
er
in
p
u
t
in
to
ce
r
tain
p
r
ed
ef
in
ed
in
te
n
t
cla
s
s
es.
F
u
r
th
er
m
o
r
e,
e
m
o
tio
n
al
an
al
y
s
is
o
f
n
at
u
r
al
lan
g
u
a
g
e
i
n
te
x
t
is
p
er
f
o
r
m
ed
to
s
i
m
u
late
h
u
m
a
n
-
li
k
e
co
n
v
er
s
atio
n
s
w
it
h
t
h
e
eld
er
l
y
.
T
h
e
co
m
p
lex
m
a
s
s
a
g
e
s
y
s
te
m
s
ea
m
les
s
l
y
co
llab
o
r
ates
w
it
h
t
h
e
A
I
co
n
v
er
s
atio
n
al
r
o
b
o
t
th
er
eb
y
e
n
s
u
r
i
n
g
p
h
y
s
ical
a
n
d
m
e
n
tal
ass
is
tan
ce
f
o
r
th
e
eld
er
l
y
.
T
h
e
d
ev
elo
p
m
e
n
t
o
f
th
e
A
I
ass
i
s
t
an
t
co
n
tr
ib
u
tes
to
th
e
ex
i
s
ti
n
g
w
o
r
k
in
ter
m
s
o
f
p
r
o
v
id
in
g
co
m
p
a
n
io
n
s
h
ip
to
t
h
e
eld
er
l
y
.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
R
esear
ch
er
s
h
av
e
w
o
r
k
ed
o
n
eld
er
ly
ca
r
e
to
p
r
o
v
id
e
an
ass
is
ti
v
e
f
r
a
m
e
w
o
r
k
f
o
r
eld
er
ly
as
w
ell
a
s
s
o
m
e
k
i
n
d
o
f
p
h
y
s
ical
aid
.
Fu
r
th
er
,
th
e
w
o
r
k
d
o
n
e
b
y
r
esear
ch
er
s
is
d
is
cu
s
s
ed
alo
n
g
w
it
h
it
s
o
u
tco
m
es.
S
m
ar
t
eld
er
ly
ca
r
e
r
o
b
o
ts
eq
u
ip
p
ed
w
i
th
A
I
f
ea
t
u
r
es
p
r
o
v
id
e
p
er
s
o
n
alize
d
ca
r
e,
c
o
m
p
an
io
n
s
h
ip
cr
ea
tin
g
p
er
s
o
n
alize
d
d
atasets
to
ass
es
s
P
FC
an
d
W
M
to
ch
ec
k
cu
r
r
en
t
u
n
d
er
s
tan
d
i
n
g
o
f
s
to
r
y
telli
n
g
an
d
m
e
m
o
r
y
a
n
d
d
if
f
ic
u
lt
y
i
n
u
n
d
er
s
tan
d
i
n
g
t
h
e
s
to
r
y
,
t
h
e
m
o
d
el
h
as
t
h
e
ac
cu
r
ac
y
s
co
r
e
o
f
8
9
%
[
3
]
.
Dee
p
le
ar
n
in
g
ap
p
r
o
ac
h
es,
s
u
c
h
as
co
n
v
o
lu
tio
n
al
n
eu
r
al
n
et
w
o
r
k
s
(
C
N
N)
an
d
r
ec
u
r
r
en
t
n
eu
r
al
n
et
w
o
r
k
s
(
R
NN)
,
h
av
e
i
m
p
r
o
v
ed
t
h
e
ac
cu
r
ac
y
(
9
2
.
3
1
%)
o
f
ac
tiv
it
y
r
ec
o
g
n
itio
n
b
y
ca
p
tu
r
i
n
g
s
p
a
tial
an
d
te
m
p
o
r
al
r
elatio
n
s
h
ip
s
,
b
u
t
t
h
e
y
r
eq
u
ir
e
lar
g
e
a
m
o
u
n
t
s
o
f
tr
ai
n
i
n
g
d
at
a
an
d
h
av
e
s
lo
w
tr
ain
in
g
s
p
e
ed
s
[
4
]
.
T
h
e
co
m
b
in
a
tio
n
o
f
f
all
d
etec
tio
n
a
n
d
h
u
m
a
n
p
o
s
e
esti
m
at
io
n
u
s
i
n
g
v
ar
io
u
s
p
ip
eli
n
es
s
u
c
h
as
Mo
v
Net,
tr
an
s
f
o
r
m
er
,
lo
n
g
s
h
o
r
t
-
ter
m
m
e
m
o
r
y
(
L
ST
M
)
,
an
d
A
lp
h
aP
o
s
e.
T
h
e
p
o
o
r
est
r
esu
lts
w
er
e
o
b
tain
ed
b
y
Mo
v
Net
6
9
%,
w
h
ile
th
e
g
r
ea
test
r
esu
l
ts
w
er
e
attain
ed
b
y
A
lp
h
aP
o
s
e
8
9
.
2
2
%
f
o
r
p
o
s
e
d
etec
tio
n
an
d
tr
an
s
f
o
r
m
er
9
0
%
f
o
r
ac
tio
n
ca
te
g
o
r
izatio
n
[
5
]
.
T
h
e
th
r
ee
p
h
ase
s
o
f
t
h
e
b
eh
a
v
io
r
id
en
tif
ica
tio
n
al
g
o
r
i
th
m
(
B
I
A
)
ar
e
s
en
s
o
r
ev
e
n
t
b
ased
g
r
o
u
p
in
g
(
SEG)
,
h
is
to
g
r
a
m
s
i
m
ilar
it
y
b
ased
g
r
o
u
p
in
g
(
HSG)
,
a
n
d
b
eh
av
io
r
b
ase
d
m
atc
h
in
g
(
B
M)
.
T
h
e
B
I
A
h
as
t
h
e
F1
-
s
co
r
e
o
f
ar
o
u
n
d
9
5
%
[
6
]
.
T
h
e
in
tr
o
d
u
ctio
n
o
f
t
h
e
ca
r
e
tr
ai
n
i
n
g
ass
i
s
tan
t
r
o
b
o
t
r
ev
o
lu
tio
n
ize
s
ca
r
eg
i
v
er
tr
ain
in
g
,
o
f
f
er
i
n
g
v
i
s
u
al
-
b
a
s
ed
f
ee
d
b
ac
k
i
n
eld
er
l
y
ca
r
e
ed
u
ca
tio
n
en
v
ir
o
n
m
e
n
t
s
.
T
h
is
i
m
m
er
s
i
v
e
ap
p
r
o
ac
h
allo
w
s
tr
ain
ee
s
to
ac
q
u
ir
e
an
d
p
r
ac
tic
e
ess
en
t
ial
ca
r
eg
i
v
i
n
g
s
k
i
lls
,
el
ev
ati
n
g
t
h
e
s
ta
n
d
ar
d
o
f
eld
er
l
y
ca
r
e
s
er
v
ices
w
it
h
p
ain
lev
el
s
f
r
o
m
0
to
1
.
9
9
w
h
i
ch
g
i
v
es t
h
e
ca
r
eg
i
v
er
m
o
r
e
ex
p
o
s
u
r
e
f
o
r
p
r
ac
tical
ap
p
licatio
n
s
[
7
]
.
A
s
m
ar
t
eld
er
l
y
a
s
s
i
s
tan
ce
s
y
s
te
m
w
h
ic
h
u
s
es
co
m
p
u
ter
v
i
s
io
n
al
g
o
r
ith
m
s
to
id
en
ti
f
y
f
a
l
l
co
n
d
itio
n
h
as
b
ee
n
d
ev
e
lo
p
ed
.
T
h
e
li
m
it
atio
n
o
f
t
h
e
s
y
s
te
m
is
th
e
r
eq
u
ir
e
m
en
t
o
f
p
r
o
p
er
lig
h
ti
n
g
co
n
d
itio
n
s
.
T
h
e
a
u
th
o
r
clai
m
s
ac
cu
r
ac
y
o
f
9
8
:5
%,
s
e
n
s
it
iv
i
t
y
o
f
9
7
%
an
d
th
e
s
p
ec
if
icit
y
o
f
1
0
0
%
f
o
r
th
e
alg
o
r
ith
m
[
8
]
.
A
s
m
ar
t
r
o
b
o
tic
ar
m
E
m
m
a
is
d
esig
n
e
d
f
o
r
m
ed
ical
m
ass
a
g
e
w
it
h
f
ee
d
b
ac
k
o
f
f
o
r
ce
a
p
p
lied
th
r
o
u
g
h
en
d
ef
f
ec
to
r
s
.
I
t
f
u
r
t
h
er
h
as
a
ca
m
er
a
f
o
r
ex
ac
t
p
lace
m
e
n
t
o
f
f
i
n
g
er
an
d
p
al
m
m
a
s
s
a
g
e
m
a
n
ip
u
lato
r
to
co
n
d
u
ct
f
ee
d
b
ac
k
co
n
tr
o
l
w
ith
r
esp
ec
t
to
f
o
r
ce
[
9
]
.
Ho
m
eM
ate
is
a
s
y
s
te
m
w
h
ic
h
tr
ie
s
to
estab
li
s
h
a
m
b
ien
t
a
s
s
i
s
ted
li
v
in
g
ar
o
u
n
d
t
h
e
eld
er
l
y
.
So
cial
r
o
b
o
t
is
a
n
o
th
er
a
s
s
i
s
ti
v
e
f
r
a
m
e
wo
r
k
th
at
h
a
s
h
u
m
a
n
r
o
b
o
t
in
te
r
ac
tio
n
(
HR
I
)
a
n
d
tr
ies
to
estab
lis
h
co
m
m
u
n
icati
o
n
w
i
th
eld
er
l
y
[
1
0
]
.
T
h
e
au
th
o
r
h
as
p
r
o
v
id
ed
an
o
v
er
v
ie
w
o
n
1
2
eld
er
ly
ca
r
e
s
y
s
te
m
s
f
o
c
u
s
ed
o
n
ass
i
s
ti
v
e
ca
r
e
th
at
ca
n
b
e
p
r
o
v
id
ed
f
o
r
ex
er
cise
an
d
r
eh
ab
ilit
atio
n
t
h
r
o
u
g
h
co
g
n
iti
v
e
b
ased
ass
is
tan
ce
b
o
t
(
C
As)
an
d
p
er
s
o
n
al
r
o
b
o
t
b
ased
ass
is
tan
t
b
o
t
(
P
R
A
s
)
.
P
HAROS
i
s
a
co
m
b
i
n
atio
n
o
f
r
o
b
o
tic
as
w
ell
as
e
v
en
t
p
lan
n
i
n
g
f
o
r
eld
er
l
y
m
o
n
i
to
r
in
g
,
w
h
ile
th
e
y
p
er
f
o
r
m
p
h
y
s
ical
tas
k
s
.
S
te
v
ie
is
an
o
th
er
ass
is
ti
v
e
r
o
b
o
t
w
h
ic
h
e
n
g
a
g
es
in
s
o
ci
al
in
ter
ac
tio
n
s
w
ith
eld
er
l
y
th
r
o
u
g
h
g
e
s
tu
r
e
s
an
d
s
p
ee
ch
[
1
1
]
.
T
h
e
au
th
o
r
d
is
cu
s
s
es
s
m
ar
t
h
o
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l
y
p
eo
p
le.
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h
e
s
y
s
te
m
p
r
o
p
o
s
ed
in
t
h
is
w
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k
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n
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r
ate
s
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atio
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al
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I
ass
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ta
n
ce
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o
r
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er
ly
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ed
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ed
s
y
s
te
m
f
o
r
f
o
o
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an
d
ca
lf
m
a
s
s
a
g
e.
T
h
e
s
y
s
te
m
u
n
d
er
s
tu
d
y
p
r
o
v
id
es
p
h
y
s
ical
aid
in
th
e
f
o
r
m
o
f
f
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t
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d
ca
lv
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ass
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alize
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I
a
s
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ich
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ill
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o
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tr
o
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th
e
m
a
s
s
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g
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s
y
s
te
m
th
r
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g
h
th
e
m
o
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ile
ap
p
lica
tio
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d
p
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p
a
n
io
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s
h
ip
th
r
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u
g
h
co
n
v
e
r
s
atio
n
.
3.
M
E
T
H
O
D
T
h
e
s
y
s
te
m
co
n
s
is
t
s
o
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A
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ased
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atio
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r
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te
m
f
o
r
f
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o
t
s
o
le
an
d
ca
lf
m
ass
a
g
e.
T
h
e
en
tire
s
y
s
te
m
is
co
n
n
ec
ted
to
a
m
o
b
ile
ap
p
licatio
n
v
ia
B
l
u
eto
o
th
f
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ter
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s
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v
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ice
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d
tex
t
co
m
m
an
d
s
.
T
h
e
s
y
s
te
m
co
m
p
r
i
s
es
f
o
u
r
m
aj
o
r
co
m
p
o
n
e
n
ts
:
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p
latf
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r
m
f
o
r
f
o
o
t
w
h
ic
h
co
n
s
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s
o
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t
s
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ased
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th
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r
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lo
g
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t
w
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m
ed
ica
l
cu
f
f
s
ar
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f
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x
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it
h
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air
p
u
m
p
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ca
l
f
m
a
s
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a
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e,
w
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f
late
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lates
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ate
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t
h
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ar
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ith
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lled
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r
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lu
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as
r
ep
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esen
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Fig
ur
e
1
.
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h
is
s
y
s
te
m
i
s
co
m
p
o
s
ed
o
f
t
w
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m
ain
s
u
b
s
y
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te
m
s
:
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atio
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r
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b
o
t
w
it
h
f
o
o
t
s
o
le
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as
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o
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it
h
a
m
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ile
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p
licatio
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f
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co
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llin
g
th
e
in
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it
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th
e
m
a
s
s
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e.
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h
e
R
asp
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er
r
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ts
as t
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it f
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m
.
3
.
1
.
Dev
el
o
p
m
ent
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f
co
nv
er
s
a
t
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n r
o
bo
t
T
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as
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p
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tal
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th
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r
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r
ch
ar
ticle.
T
h
e
A
I
i
s
d
esig
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ed
to
p
r
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v
id
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co
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p
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ip
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ed
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m
an
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m
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t
t
h
r
o
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m
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er
s
.
A
I
lear
n
s
f
r
o
m
u
s
er
in
t
er
ac
tio
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s
,
ad
ap
tin
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its
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esp
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n
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es
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v
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e.
T
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A
I
tr
an
s
lates
th
e
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j
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Vo
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14
,
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Ma
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2025
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u
r
e
1
.
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ass
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ta
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t d
r
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n
m
as
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ag
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3
.
1
.
1
.
Cus
t
o
m
i
nte
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re
co
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nitio
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s
t
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m
us
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it
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3
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ar
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:
−
I
n
ten
t 1
: (
"
C
o
n
v
er
s
e
w
i
th
eld
e
r
l
y
"
)
:
"
C
o
n
v
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s
e
w
it
h
a
n
eld
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l
y
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s
o
n
ab
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u
t th
e
ir
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a
y
.
"
−
I
n
ten
t
2
:
(
"
Ma
n
ip
u
late
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as
s
ag
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co
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tr
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l"
)
:
"
A
d
j
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s
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th
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o
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tic
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as
s
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g
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co
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tr
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l
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y
s
te
m
to
a
g
e
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tle
in
te
n
s
it
y
.
"
−
I
n
ten
t
3
:
(
"
Set
m
ed
icatio
n
r
e
m
in
d
er
s
"
)
: "
C
r
ea
te
a
m
ed
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r
em
i
n
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er
f
o
r
a
d
aily
d
o
s
ag
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o
f
[
Me
d
icatio
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Na
m
e]
.
"
T
h
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GPT
m
o
d
el
is
tr
ain
ed
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th
e
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e
f
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t
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ize
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h
e
c
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ied
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te
n
t is t
h
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n
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ap
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to
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ed
f
u
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s
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r
task
s
.
3
.
1
.
2
.
E
m
o
t
io
n r
ec
o
g
nitio
n
T
h
e
alg
o
r
ith
m
f
o
r
e
m
o
tio
n
cl
ass
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f
icatio
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is
i
n
itiated
w
h
en
th
e
in
ten
t
cla
s
s
i
f
ier
r
ec
o
g
n
ize
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at
t
h
e
u
s
er
w
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n
ts
to
h
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v
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co
n
v
er
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atio
n
.
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n
th
is
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t
u
d
y
,
w
e
e
m
p
lo
y
ed
a
b
id
ir
ec
tio
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en
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er
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p
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tatio
n
s
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m
tr
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s
f
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(
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)
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ased
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o
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o
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d
ataset.
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e
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ataset
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s
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t
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)
t
h
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ataset
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s
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4
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Up
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s
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ass
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re
lated
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ctio
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co
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as
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asp
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x
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m
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ith
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ates
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cr
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s
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ed
w
it
h
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(
1
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(
|
|
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′
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1
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a
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eter
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ac
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ac
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.
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eg
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w
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t
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n
d
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m
a
s
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g
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elate
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s
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s
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d
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tr
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w
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ld
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"
.
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h
is
in
f
o
r
m
at
io
n
ca
n
th
e
n
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e
u
ti
lized
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ar
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th
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o
tic
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y
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te
m
ac
co
r
d
in
g
l
y
.
Me
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icatio
n
r
em
i
n
d
er
:
u
p
o
n
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tify
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g
th
e
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n
t
a
s
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m
ed
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r
e
m
in
d
er
s
,
"
th
e
alg
o
r
ith
m
e
m
p
lo
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s
r
eg
e
x
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m
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t
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elate
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c
h
as
m
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n
a
m
es,
d
o
s
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an
d
f
r
eq
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s
,
f
r
o
m
th
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u
s
er
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in
p
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T
h
e
u
s
er
_
in
p
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=
"
Set
a
r
e
m
in
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f
o
r
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zit
h
r
o
l a
t 9
A
M
ev
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a
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ter
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tr
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ter
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o
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tr
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ted
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to
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m
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h
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t
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ith
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itiati
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ip
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
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I
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t J
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o
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f
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m
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Sy
s
t
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Vo
l.
14
,
No
.
1
,
Ma
r
c
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2025
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35
-
47
42
A
l
g
o
r
ith
m
1
.
A
l
g
o
r
it
h
m
f
o
r
m
ass
a
g
e
co
n
tr
o
l a
n
d
r
esp
o
n
s
e
g
en
er
at
io
n
Input:
Mobile application string(X1) and voice input(X2)
Output:
Run foot sole massage(Y1), adjust intensity of calves massage(Y2)
and provide response(Y3)
Initialize:
Device Bluetooth connection
1.
Loop
:
2. UserInput = X2
3.
CharacterInput=X1
4.
if
X1 is "Running foot sole massage"
then
5.
Invoke Y1
6.
else if
CharacterInput is "Running calves massage"
then
7.
Invoke Y2(5)
8.
if
IncreaseButtonPressed()
then
9.
Invoke Y2(5+1)
10.
end if
11.
else if
D
ecreaseButtonPressed()
then
12.
Invoke Y2(5
-
1)
13.
end if
14.
end if
15.
else if
X1 is "Stop button pressed"
then
16.
StopMassage()
17.
end if
18.
if
Prompt(X2)
then
19.
Emotion= ExtractEmotion(X2)
20.
Invoke Y3(Emotion)
21.
end if
22.
Return
4.
RE
SU
L
T
S AN
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r
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ased
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ir
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o
o
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as
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ile
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o
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et
u
p
is
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r
o
v
id
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th
e
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er
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test
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o
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atio
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r
o
b
o
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e
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tio
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ed
b
elo
w
.
E
g
.
u
s
er
i
n
p
u
t
“
Gi
v
e
m
ed
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r
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at
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elat
ed
to
A
zit
h
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m
y
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let”,
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e
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s
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h
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h
t
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o
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o
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ar
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n
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ical
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ata
o
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l
t
h
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I
r
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e
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iv
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u
er
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lo
tted
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n
Fig
u
r
e
4
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h
e
s
tan
d
ar
d
d
ev
iatio
n
o
f
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h
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r
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o
n
s
e
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r
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i
s
at
1
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2
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ea
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f
ee
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b
ac
k
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ata
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o
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ts
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.
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0
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h
e
em
o
tio
n
clas
s
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f
icatio
n
m
o
d
el
w
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s
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n
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t
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th
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atio
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B
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ase
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el
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tr
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h
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Dair
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ai
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ataset.
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h
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v
alid
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ata
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et
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s
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I
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Valu
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ated
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ates
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r
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r
s
u
r
p
r
is
e
co
m
e
i
n
to
p
l
ay
.
Evaluation Warning : The document was created with Spire.PDF for Python.