05496581

201O International Conference on E-Health Networking, Digital Ecosystems and Technologies
Simulation of spontaneous respiration nonlinear model driven by muscle
pressure
He Zhonghai, Shan Fang,
Sun Meirong
Automation engineering department
Northeastern Universisty at Qinhuangdao
Hospital
Northeastern Universisty at Qinhuangdao
Qinhuangdao, China
E-mail:summeirong@eyou.com
Qinhuangdao, China
E-mail: zhhe@mail.neug.edu.cn
sf 313316@126.com
Abstract:
The spontaneous respiratory simulation is one
main task of medical patient simulator.
physiology factors respiratory is one of the most
important characteristic. Study on the generation of
respiratory has practical significance.
There are many papers [1-5] about respiratory
system model, most of which focus on structure of
respiratory system, have no mention on driven part.
Ronald [6] study the original power of breath. He
studied on the respiratory model based on breath
muscle pressure. But his model is not consistent in the
model widely used later. One important factor is less
of airway resistance influence in his work. This paper
is aimed at construction of normal human respiratory
system model, combined the widely used respiratory
model and muscle pressure driven power.
We have designed muscle driven respiratory model
using simulink in matlab [7] and LabVIEW [8]
respectively. In both ways we can get correct lung
flow curve. Linear relationship or fixed parameters of
airway resistance and compliance are used in the
papers to illustrate the muscle pressure validate clearly.
However, the fixed mechanical parameters is too
simplified so that many details are neglected, which
cause considerable inaccuracy flow in breath
simulation. The numerically simulated model features
a two-component resistance, representing the series
association of a linear resistor with a flow-dependent
resistor. The latter models nonlinear tracheal tube
characteristics and the former lumps the linear part of
the tracheal tube resistance together with the
equivalent linear resistor of respiratory system.
Based on the
principle of breath, muscle pressure as source power is
input into the breath system. Breath system is simulated
as two lumped compartments, airway resistance and
compliance.
The output of the breath system is the flow
of respiratory. Compared to the former method that two
fixed parameters (Rand C) are used as linear coefficient,
we avoided the oversimplifications inherent in previous
models,
namely
linear
treatment
of
the
breathing
mechanics. Nonlinear resistance is used in this model. In
order to complete the complicated model and control
actuator simultaneous, LabVIEW and simulink program
are used both, simulation interface toolkits (SIT) being
the bridge between the two different languages.
The
simulated flow wave is more similar to the real breathing
in that the expiratory flow is smoother than in the linear
model.
The parameters of Rand C can be adjusted by
knob in LabVIEW.
And the controlling peripheral
apparatus task can also be accomplished by LabVIEW
DAQcard.
Keywords: respiratory model, nonlinear compliance,
simulink, simulation interface toolkits
I.
INTRODUCTION
With the microprocessors the sophistication of
simulators exploded. Simulators became the backbone
of training in aviation. More recently medicine has
developed simulators that are becoming increasingly
sophisticated, especially in anesthesia training but also
to train intensive care personnel. This is an area that
will rapidly advance in the future and will have great
impact on medical education medical.
Patient simulators are increasingly used in the
education and training of physicians, nurses,
emergency care personnel and many other healthcare
professionals. Learners can effectively acquire both
basic and advanced clinical skills using patient
simulation. It is widely studied that physiology-driven
simulator. So generating correct physiology is a key
task in design of patient simulator. In the human
II.
SIMULATION METHOD
There are two methods that we can use to
simulate the respiratory system.
First, simulink
toolkits in matlab are the commonly used tool for
simulation. But the simulink can not interface control
system real-time, although it is powerful in model
simulation. Second, the control design and simulation
module in LabVIEW can also be used. On advantage
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978-1-4244-5517-1/10/$26.00 ©201O IEEE
EDT2010
of LabVIEW's interface convenience, the model
design by control design and simulation module can be
used in real actuator control very easy. But the
disadvantage of the module is it can not design model
by block. If the model is somewhat complicate, the
P
=
(Kl + K2IV(t �)v(t)+ E· V(t)
The respiratory muscle pressure data from Ronald
[6] in Fig. 1 is used as input of model. We construct
the nonlinear model of breath system using simulink,
muscle pressure cun.e with respiratory time
6 ,----,-----,---r--=-�--,_--_.--_,--�
�
:::J
(/)
(/)
� 4
0..
�
0
(/)
:::J
E
2
co
:8
o
'---..L...-_"---__
----'-_
o
0.5
-----"---
-----'--
1.5
2
----L- _
2.5
1-- _---'----
3
3.5
4
Fig.! Pressure waveform generated by respiratory muscle
c
SignalProbe
SignalProbe
O.Og'ab�lJflJ
Fen
Fig.2 Simulink model with muscle pressure
as
input and linear compliance nonlinear
resistance varied with flow
control design and simulation module will become
powerless.
Fortunately, the National Instruments
Company realize the problem, they provide a tool, i.e.,
simulation interface toolkits, used to transform
Simulink model to LabVIEW program. Combine the
advantage of powerful model construction of simulink
and interface convenience with peripheral actuator of
LabVIEW and the bridge tool simulation interface
toolkits (SIT), we design a program based on
LabVIEW with SIT interface with simulation model
generated by simulink. The program can control
actuator and designs the simulation model complicate,
which take advantage while eliminate disadvantage of
the two languages.
The equation of motion that represents the
nonlinear model is [9]:
the following block in Fig. 2 being the model,
parameters were selected from [10]. The LabVIEW
8.6 and SIT 5.0 is used in the main program, DAQ is
configured to output signal with PCI-6221M card
equipped. The calculated flow wave is to be tracked
by proportional flow valve. Fig.3 is part of front panel
when SIT is used interface with simulink. FigA is the
simulated flow using the aforementioned simulation
condition: respiratory muscle used as input, nonlinear
parameter of resistance that flow-dependent is used,
and compliance is fix number..
III. CONCLUSION
Compared with the flow wave generated with
fixed resistance [7], the inspiratory flow part has little
30
change, but the expiratory flow parts are smoother. In
general, the flow is more similar to the real curve.
0.3
Model Controls
'"
\
0.5O. B
I
'"
0.20.1""
o
/
R
HB�O
(2) respiratory model is more complicated and precise
with resistance flow-dependent parameterized, and the
computed flow is even similar to real breath; (3)
LabVIEW is used as the main program to
interface with peripheral equipment, simulink is
used as model construction program to cope with
model complication, SIT is used to bridge the two
program efficiently. The mentioned program
method should be the optimum solution by our
practice.
..
References
[1]
A. F. M. Verbraak, 1. M. Bogaard, 1. E. W.
Beneken, E.Hoorn, , "Serial lung model for
simulation and parameter estimation in body
plethysmography",
Medical
&
biological
engineering & computing, 1991, 29, pp 309-317.
[2]
Samir
Mesic,
Robert
Babuska,
Henk
C.
Hoogsteden,
and
Anton
F.
M.
Verbraak,
"Computer-controlled mechanical simulation of
the artificially ventilated human respiratory
system",
IEEE transactions on biomedical
engineering, 2003, 50(6), pp 731-743.
O. 75
0.5
0.25
o
Fig. 3 Part of front panel of LabVIEW program when simulation interface
toolkits are used to embed simulink model
V. V. Meka and J. H. van Oostrom, "Bellows-less
lung system for the human patient simulator",
Medical & biological engineering & computing,
2004, 42,pp 413-418.
[3]
[4]
A. F. M. Verbraak, P. R. Rijnbeek, 1. E. W. Beneken, 1.
M. Bogaard, et ai., "A new approach to mechanical
simulation of lung behaviour: pressure-controlled and
time-related piston movement", Medical & biological
engineering & computing, 2000, 38, pp 82-89.
[5]
A. F. M. Verbraak, J. E. W. Beneken, J. M. Bogaard,
and A. Versprille, "Computer-controlled mechanical
lung model for application in pulmonary function
studies",
Medical
&
biological
engineering
&
computing, 1995, 33,pp 776-783.
[6]
Ronald W. Jodat, James D. Horgen, and Ramon L.
Lange,
"Simulation
of
respiratory
mechanics",
Biophysical journal, 1966, 6, pp 733-785.
[7]
He Zhonghai, "Simulation study on human respiratory
system based on muscle pressure driven", International
conference on engineering computation, Hong Kong:
IEEE computer society, 2009, pp 33-35.
[8]
He Zhonghai, Shan Fang,
"Adjustable parameters
respiratory flow generation simulation method realized
by LabVIEW",
Third international symposium on
intelligent
information
technology
application,
Nanchang, China: IEEE computer society, 2009, pp299301.
[9]
Frederico
C.
Jandre,
Alysson
Roncally
Silva
Carvalho,Alexandre
Visintainer
Pino,
Antonio
Giannella-Neto, "Effects of filtering and delays on the
estimates of a nonlinear respiratory mechanics model",
Respiratory Physiology & Neurobiology, 2005, 148, pp
309-314.
Fig.4 Simulation result of flow using muscle pressure as input and
nonlinear airway resistance
IV. DISCUSSION
We have tried the two foregoing methods both
respectively [7-8].
But we can not realize the
simulation construction and output simulated result by
one program. If the model is simple, the control
design and simulation module in LabVIEW can
competent for the task, as we have done in previous
work. With the complicate of respiratory model, by
practice, we conclude that the combination of simulink
and LabVIEW bridged by simulation interface toolkits
is the optimum option.
There are three main key points in the paper: (1) the
respiratory muscle pressure is used as system input,
which is accorded with spontaneous breath principle;
[10] Tang
Yuansheng, Zhang Xiuzhen, Han diancun,
Parameters and concept of human medical, Jinan,China:
Jinan publishing house, 1995. "in Chinese"
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