Clinical cardiovascular Clinical cardiovascular identification with limited identification with limited data and fast forward data and fast forward simulation simulation 6 th IFAC SYMPOSIUM ON MODELLING AND CONTROL IN BIOMEDICAL SYSTEMS C. E. Hann 1 , J. G. Chase 1 , G. M. Shaw 2 , S. Andreassen 3 , B. W. Smith 3 1 Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand 2 Department of Intensive Care Medicine, Christchurch Hospital, Christchurch, New Zealand 3 Centre for Model-based Medical Decision Support, Aalborg University, Aalborg, Denmark
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Clinical cardiovascular identification with limited data and fast forward simulation
Clinical cardiovascular identification with limited data and fast forward simulation. 6 th IFAC SYMPOSIUM ON MODELLING AND CONTROL IN BIOMEDICAL SYSTEMS C. E. Hann 1 , J. G. Chase 1 , G. M. Shaw 2 , S. Andreassen 3 , B. W. Smith 3 - PowerPoint PPT Presentation
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Clinical cardiovascular identification with Clinical cardiovascular identification with limited data and fast forward simulationlimited data and fast forward simulation
6th IFAC SYMPOSIUM ON MODELLING AND CONTROL IN BIOMEDICAL SYSTEMS
C. E. Hann1, J. G. Chase1, G. M. Shaw2, S. Andreassen3, B. W. Smith3
1Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand2 Department of Intensive Care Medicine, Christchurch Hospital, Christchurch, New Zealand3 Centre for Model-based Medical Decision Support, Aalborg University, Aalborg, Denmark
• Problem: Cardiac disturbances difficult to diagnose– Limited data
– Reflex actions
• Solution: Minimal Model + Patient-Specific Parameter ID– Interactions of simple models to create complex dynamics
– Primary parameters
– Identification must use common ICU measurements
– E.g. increased resistance in pulmonary artery pulmonary embolism, atherosclerotic heart disease
• However: Identification for diagnosis requires fast parameter ID– Must occur in “clinical real-time”
– Limits model and method complexity (e.g. parameter numbers, non-linearities, …)
Diagnosis and TreatmentDiagnosis and Treatment
Heart ModelHeart Model
D.E.’s and PV diagramD.E.’s and PV diagram
2
2232
2
1
1121
1
21
L
RQPPQ
L
RQPPQ
QQV
2
0
)375.0(80
)(02
)(
),1())(1()()(
t
VVdes
ete
ePteVVEteP
Fast Forward SimulationFast Forward Simulation
• Formulate in terms of Heaviside functions:
• No looking for sign changes and restarting DE solver
done automatically
• E.g. filling (P1>P2, P2 ):
(close on flow)
2
22322322
1
11211211
2211
)()5.0)()((
)()5.0)()((
)()(
L
QRPPQHPPHHQ
L
QRPPQHPPHHQ
QQHQQHV
0)(,1
0)(,0))((
tK
tKtKH
)(
1tan)(tan
1
2
1))(( 11
tKtKtKH
0,,0
0,,1)5.0)()((
112
112121
QPP
QPPQHPPHH
Fast Forward SimulationFast Forward Simulation
• Ventricular interaction solve every time step (slow)
Substitute:
• Linear in Vspt Analytical solution very fast
)1())(1()()(
)1())(1()()(
)1())(1()()(
)(,0,
)(,0,
)(,0,,
,0
,0
,0
sptrvrvf
sptlvlvf
sptsptspt
VVrvfsptrvrvfes
VVlvfsptlvlvfes
VVsptsptdsptsptes
ePteVVEte
ePteVVEte
ePteVVEte
rvfrvrvfV
lvflvlvfV
sptsptsptV
bVaebVaebVae rvrvflvlvfsptspt ,,
Method (20 Heart beats) CPU time (s) Speed increase factor
• Venous constriction – increase venous dead space
• Increased HR
• Increased ventricular contractility
Varying HR as a linear function of Pao
Simple interactions to create overall complex dynamic behaviour in the full system model
Disease StatesDisease States
• Pericardial Tamponade:– Build up of fluid in pericardium– Decrease: dead space volume V0,pcd
• Pulmonary Embolism:– Increase: Rpul
• Cardiogenic shock:– Not enough oxygen to myocardium (e.g. from blocked coronary artery)– Decrease: Ees,lvf, Increase: P0,lvf A more complex set of changes/interactions