A non invasive monitoring of breathing pattern variability in the neonatal intensive care unit

(1)

A NON-INVASIVE MONITORING OF BREATHING

PATTERN VARIABILITY IN THE NEONATAL

(2)

(3)

i

... III ... V ... VI ...XIII

...3

... 4

... 5

... 6

... 9

... 10

... 12

...13 ...15

... 16

...16 ...20

... 21

... 22

...24 ...26 ...26 ...27 ...28 ...29 ...31

... 34

...35 ...35 ...35

... 35

...36 ...36 ...36

(4)

ii

...36 ...36 ...37 ...37

... 41

... 44

...44 ...49 ...51

... 52

...55 ...55 ...58 ...59 ...60 ...61 ...67 ...69

... 70

... 74

... 77

... 79

... 80

... 85 ... 86

... 88

... 91

(5)

iii

... 4

... 5

... 7

... 10

... 44

... 45

... 46

... 47

... 48

... 49

... 50

... 51

... 52

... 54

... 56

... 61

(6)

iv

... 62

... 64

... 65

... 66

... 67

... 71

... 72

... 73

... 75

... 82

... 83

... 84

(7)

v

... 19

... 57

... 74

... 75

... 81

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

(19)

(20)

(21)

(22)

(23)

(24)

(25)

(26)

(27)

(28)

(29)

(30)

(31)

(32)

11 -

-

(33)

(34)

(35)

(36)

(37)

(38)

(39)

(40)

(41)

(42)

(43)

(44)

(45)

(46)

(47)

(48)

(49)

(50)

(51)

(52)

(53)

(54)

(55)

(56)

(57)

(58)

(59)

(60)

39 -

-

(61)

(62)

(63)

(64)

43 -

-

(65)

44 -

-

(66)

45 -

-

(67)

46 -

(68)

47 A

(69)

48

(70)

(71)

(72)

(73)

(74)

53 -

-

(75)

(76)

(77)

(78)

(79)

(80)

(81)

(82)

(83)

(84)

(85)

(86)

65 𝑥̅ =

𝑚

10

𝑚

00

,

𝑦̅ =

𝑚

₀₁

𝑚

00

𝑚

_𝑗𝑖

= ∑(𝑎𝑟𝑟𝑎𝑦(𝑥, 𝑦) ∗ 𝑥

𝑗

_{∗ 𝑦}

𝑖

₎

𝑥,𝑦

(87)

66 𝑀

_𝑙

𝑀

_𝑟

λ (

𝑢

𝑙

𝑣

_𝑙

1 ) = 𝑀

𝑙

(𝐼|0) (

𝑋

𝑌

𝑍

1 ) λ (

𝑢

𝑟

𝑣

_𝑟

1 ) = 𝑀

𝑟

(𝑅|𝑇) (

𝑋

𝑌

𝑍

1 )

𝐿

_𝑟

= 𝑀

_𝑟

(𝑅|𝑇)

𝑢

_𝑙

, 𝑣

_𝑙

𝑢

_𝑟

, 𝑣

_𝑟

,

{

(𝐿

𝑙11

− 𝑢

𝑙

𝐿

𝑙31

)𝑋 + (𝐿

𝑙12

− 𝑢

𝑙

𝐿

𝑙32

)𝑌 + (𝐿

13𝑙

− 𝑢

𝑙

𝐿

𝑙33

)𝑍 = 𝑢

𝑙

𝐿

𝑙34

− 𝐿

𝑙14

(𝐿

𝑙₂₁

_{− 𝑣}

𝑙

𝐿

𝑙31

)𝑋 + (𝐿

𝑙22

− 𝑣

𝑙

𝐿

𝑙32

)𝑌 + (𝐿

𝑙23

− 𝑣

𝑙

𝐿

𝑙33

)𝑍 = 𝑣

𝑙

𝐿

𝑙34

− 𝐿

𝑙24

(𝐿

𝑟11

− 𝑢

𝑟

𝐿

𝑟31

)𝑋 + (𝐿

𝑟12

− 𝑢

𝑟

𝐿

𝑟32

)𝑌 + (𝐿

13𝑟

− 𝑢

𝑟

𝐿

𝑟33

)𝑍 = 𝑢

𝑟

𝐿

𝑟34

− 𝐿

𝑟14

(𝐿

𝑟21

− 𝑣

𝑟

𝐿

𝑟31

)𝑋 + (𝐿

𝑟22

− 𝑣

𝑟

𝐿

𝑟32

)𝑌 + (𝐿

𝑟23

− 𝑣

𝑟

𝐿

𝑟33

)𝑍 = 𝑣

𝑟

𝐿

𝑟34

− 𝐿

𝑟24

(88)

(89)

68 -

-

(90)

69 -

-

𝑥

𝑖

𝑦𝑁 = ∑

𝑁_𝑖=1

(𝑥

𝑖

− 𝑥̅)

𝑦

𝑖

𝑠

𝑛

(𝑛)

𝐹(𝑛) =

(91)

70 √

_𝑁1

∑

𝑁

(𝑦

_𝑖

− 𝑠

_𝑛

(𝑖))

2

(92)

(93)

72

Bland-Altman analysis for IBI

( IBI_OEP(s)+IBI_W(s) )/2

0.4 0.6 0.8 1.0 1.2 1.4 IB IOEP - W (s) -0.15 -0.10 -0.05 0.00 0.05 0.10 0.15 0.20

Linear regression for IBI

IBI_OEP(s) 0.4 0.6 0.8 1.0 1.2 1.4  (s)W 0.4 0.6 0.8 1.0 1.2 1.4 m=0.97 r2_=0.96

Bland-Altman analysis for VT

( VT_OEP(s)+VT_OEP(s) )/2 0 2 4 6 8 10 12 14 16 18 VT O E P -V TW (s) -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8

Linear regression for VT

VT_OEP(s) 0 2 4 6 8 10 12 14 16 18 VT W (s) 0 2 4 6 8 10 12 14 16 18 m=0.980 r2=0.991

(94)

73

Bland-Altman analysis for EELV

( EELVOEP (s) + EELVOEP (s) )/2

-8 -6 -4 -2 0 2 4 6 8 10 12 EELV O E P -E E L VW (s) -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6

Linear regression for EELV

EELV_OEP(s) -8 -6 -4 -2 0 2 4 6 8 10 12 EELV W (s) -8 -6 -4 -2 0 2 4 6 8 10 12 m=0.999 r2 =0.999

(95)

74

α r2 α r2 α r2 N motor input 0.678 ± 0.049 0.985 0.902 ± 0.034 0.996 1.173 ± 0.059 0.992 791 OEP 0.644 ± 0.027 0.995 0.890 ± 0.035 0.995 1.212 ± 0.066 0.991 780 webcam 0.642 ± 0.027 0.995 0.891 ± 0.034 0.996 1.214 ± 0.066 0.991 780 motor input 0.505 ±

0.0

29 0.990 0.487 ± 0.045 0.975 0.507 ± 0.013 0.998 902 OEP 0.565 ± 0.021 0.996 0.498 ± 0.039 0.982 0.483 ± 0.025 0.991 905 webcam 0.558 ± 0.020 0.996 0.497 ± 0.983 0.983 0.491 ± 0.028 0.990 905

Oscillation period Oscillation amplitude minimum oscillations

Correlated series

Scorrelated series

(96)

(97)

(98)

(99)

(100)

79 



(101)

80 -

-

(102)

(103)

82

n 1 10 100 1000 F (n ) 0.1 1 10 100 IB I (s ) 0.2 0.4 0.6 0.8 1.0 1.2 1.4 VT (ar bitrar y unit ) 0 1 2 3 4 5 6 Breath # 0 50 100 150 200 250 300 350 400 eelv (ar bitrar y unit ) 25 26 27 28 29 30 31 32 F (n ) 0.01 0.1 1 10

=1.225

r

2

=0.997

F (n ) 0.1 1 10

=0.829

r

2

=0.994

=0.799

r

2

= 0.995

=0.541

r

2

= 0.998

=0.536

r

2

=0.988

=0.637

r

2

=0.992

(104)

83

EELV day -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 IBI day -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5  0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 rachele matteo perla gabriele riccardo lafit VT day -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 infant 1 infant 2 infant 3 infant 4 infant 5 infant 6

(105)

84

IBI day -2 0 2 4 6 14 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 rachele matteo perla gabriele riccardo lafit EELV day -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 IBI day -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5



0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 rachele matteo perla gabriele riccardo lafit VT day -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 infant 1 infant 2 infant 3 infant 4 infant 5 infant 6

(106)

(107)

(108)

87 α

(109)

(110)

89 α

(111)

(112)

(113)

(114)

(115)

(116)

(117)