2010

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UNSW ENGINEERING @

UNSW

10Author – Huaiyu Scott Lin

Supervisor : Andrey Savkin / Co-Supervisor: Nigel Lovell / Assessor: Victor Solo

Investigation in LVAD&CVS interaction and A Non-Invasive control approach

Introduction

Existing designs of Left Ventricular Assist Device have their limitations in responding to recipients’ changing physiological status. The aim of this thesis is to investigate the interaction between the Cardiovascular system and its assisting device, then take a non-invasive approach to control the device thus avoid the extreme scenarios in terms of assistance failure which further damages the native heart. While the invasive methods are commonly used in current researches, it is essential to seek for a non-invasive approach that minimise the risks of thrombus formation caused by implementing physiological sensors and transducers. In additional, a control strategy which is able to track for a changing optimal operating point is the key in designing future fully adaptive control algorithms.

1. Optimal operating point searching using Extremum Seeking Algorithm for suction avoidance

1. Measurement of system PreloadPulsatile waveforms present throughout the blood circulation of body due to the contractile force of cyclic heart beats. Such pulsatile signal indicates the status of left ventricle function as it responds to physiological blood demand. It can be obtained as:

PI = LPF(abs(HPF(X)))2. Feedback approach to compensate system afterloadDue to the major system linearity between a mean pump flow and the mean rotational speed is caused by changing systemic peripheral resistance (afterload) once a high pump flow is required. We required a speed compensation in order to keep up with the desired flow hence follow the starling law.

0 20 40 60 80 100 120 140 1601600

1800

2000

2200

2400

2600

2800

3000PI(w) Vs Pump Speed

PI(w)

mea

n P

ump

spee

d (r

pm)

Low Afterload

Medium AfterloadMedium High Afterload

High Afterload

2. Non-linearity between pump speed and flow for varying afterload

Part1: Biological Signal Analysis

Maintaining a desire pump flow by adjusting a right amount of pump speed is critical in order to achieve a target assistance. Experimental results showed that an increase in speed is required for maintaining a target flow for each increment of systemic afterload as shown on the left. This is true for high flow values and it provides us with an approximated linear relationship between PI(speed) and flow within the drawn box. Clinically, this is the expected working range for an appropriately controlled LVAD since PI(w) can not be less than a certain level which induces suction, and non-linearity beyond the right boundary of the box.

Result is able to track the reference PI value with inversely change of the input rotational speed. The right top figure shows the tracking process for reaching the desired optimal value obtained from ESC. The bottom figure shows the changing speed with respect to that.

0 20 40 60 80 100 120 140 1602

2.5

3

3.5

4

4.5

5

5.5

6

6.5

7PI(w) Vs Mean Pump Flow

PI(w)

Mea

n P

ump

Flo

w(L

/min

)

Low Afterload

Medium AfterloadMedium High Afterload

High Afterload

Part2: Non-invasive control approach

3. Optimal operating pointAn optimal operating point for full assist can be defined as the minimum gradient of PI w.r.t speed thus gives the maximum possible assistance with leaving enough safe margin before suction.

ESC tracks the optimal point of PI by watching its cost function, which is defined as gradient of PI w.r.t speed

GPI = dPI/dwA small sinusoidal perturbation is added in order to track the slope of changing convex function of GPI. A simulation work has been carried out by assigning a second order polynomial as plant.

Result on the left shows a convergence of output value as input is stable.

Output

Input

PI

speed