Page 162 - Computational Modeling in Biomedical Engineering and Medical Physics

Bioimpedance methods 151

2008; Osypka, 2009, Grollmuss et al., 2012; Henry et al., 2012)iseducedfromgeneral car-
diac output observances and injury espial of myocardial ischemic (Mellert et al., 2011).
EVM model analyses the change in impedance of the aortic blood soon after aortic valve
opening, due to the red blood cells (erythrocytes) alignment with the flow.
The observed EVM/ECM bioimpedance signal bears also the concurring effects of
respiration and fluctuations in the cardiac cycle: Z(t) 5 Z 0 1 ΔZ R 1 ΔZ C ,where Z 0
is the “quasi-static” part, referred to as the base impedance. ΔZ R accounts for the effects
of respiration and it is suppressed to the estimate SV. ΔZ C is caused by changes due to
the cardiac cycle, produced by the thoracic fluids, the thoracic blood volume included.
In TEB, the stroke volume is calculated using (Osypka, 2009)

SV TEB 5 C p Uv FT UFT; ð5:9Þ
21
where C p [mL] is a patient constant, v FT [s ] is the mean velocity index measured
during the flow time, FT [s]. EVM introduces the peak aortic acceleration

dZ tðÞ

dt
ICON 5 min 3 1000; ð5:10Þ
Z 0
and uses it to calculate v FT yielding
v ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

u
dZ tðÞ
u
dt
t
v FT;EVM 5 min ; ð5:11Þ
Z 0
and “corrects” the flow time rate, which is calculated using the left-ventricular ejec-
tion time, LVET and the ECG R-R interval, T RR , yielding
p ffiffiffiffiffiffiffiffiffi
FT C 5 LVET= T RR ; ð5:12Þ
Hence, using the body mass index, V EPT , the stroke volume by ECM yields (Osypka,
2009)

SV EVM 5 V EPT Uv FT;EVM UFT C ; ð5:13Þ

and the cardiac output is

SV EVM
CO 5 3 HR; ð5:14Þ
1000
where HR is the measured heart rate.
To distinguish between ICG and EVM, ICON, Eq. (5.10), in the ICG model
(Woltjer et al., 1997) is an index of peak velocity. In contrast, EVM considers it an