Servo-Controlled Blood Vessel Occluder

Ahmed El-Gawish, Alan Chen,Hugo Loo, & Imad Mohammad

Advisor: Ki Chon

Background

Goal: measure effect of drugs and hypertension on MYO and TGF in mediation of renal autoregulation

Needed: a device that will automatically occlude and release blood vessels based on the user’s settings

Requirements

Pressure control intervals: 20 mmHg - simulating rapid step change in renal arterial pressure (RAP)

Control over period of 200 secs – stabilizes pressure effects

Mean controlled pressure range 80 – 120 mmHg – range over which the MYO and TGF mechanisms hypothetically take effect in autoregulation

Components

Occluder

Sensor

Pump

Motor

Software

Occluder

Made from 100% silicon material Proven to be physiology compatibility

Size used is depends on lumen diameter Range is between 2mm to 24 mm

Inject air or liquid into occluder to adjust the diaphragm/lumen diameter

Air

Advantages Simplicity Availability Ease of pressure control Doesn’t damage occluder

Disadvantage Dangerous!

Used for either short or long-term occlusion

Water and saline solution

Advantages Simplicity Availability Ease of pressure control Biocompatibile

Disadvantage Transpires/Evaporates through silicone rubber Causes damage of silicone rubber

Used for short-term occlusion (up to one hour)

Glycerin

Advantages No transpiration No evaporation Doesn’t cause damage occluder Biocompatible

Use for long-term occlusion (excess of one hour)

Sensor

Blood pressure sensor is an invasive or non-invasive sensor Invasive - used or implanted directly at the

measurement site (e.g., intra cardiac, blood vessel) Non-Invasive - measure systolic and diastolic blood

pressure utilizing the oscillometric technique

Designed to measure human blood pressure

Invasive Sensors

Internally placed catheter-tip sensor

Catheter fluid is coupled directly to an external transducer

Blood pressure is measured by observing the cavity’s changes in length with an optical signal conditioner

Measuring scheme is based on white light interferometry

Can be used on rats as well as humans

Fiber Optic Pressure Sensors (Invasive)

Non-Invasive Sensors

For humans: the sensor is attached to the cuff on the wrist.

Oscillometric technique is used to measure the blood pressure

For rats: high cost

Photoplethysmography

Relatively inaccurate

Imprecisely measures systolic blood pressure

Over-saturation of the blood pressure signal by ambient light

Difficulty in obtaining adequate blood pressure signals in dark skinned rodents

Correlate poorly with direct blood pressure measurements

Piezoplethysmography

Similar clinical limitations to Photoplethysmography

Utilizes piezoelectric ceramic crystals to record blood pressure readings

More accurate than light-based/LED sensors

Correlate poorly with direct blood pressure measurements.

Volume Pressure Recording-VPR

Independent clinical validation study in 2003 conducted at Yale University VPR correlated almost 100% with direct blood pressure

measurement

Utilizes a specially designed differential pressure transducer

Measure six (6) blood pressure parameters simultaneously: systolic blood pressure, diastolic blood pressure, mean blood pressure, heart pulse rate, tail blood volume, and tail blood flow

Non-Invasive Sensors

Motor

Drives the medium based on control signals

Two Types Stepper Motor Servo Controlled Motor

Stepper Motors

Resolution is set at steps per revolution

Inexpensive

No need for feedback Remembers current position and knows number of

steps to reach another position

Uses current even when stationary Generates heat (50C - 90C)

Stepper Motors (cont’d)

Digitally controlled Signals cause it to settle in positions based on

coil states

Speed determined by controller

Maintains position without signal changes Higher holding torque

Stepper Motors in Action

Animation source: http://www.interq.or.jp/japan/se-inoue/e_step1.htm

Servo-Controlled Motors

Higher resolution

Smoother motion

Less heat generated

More expensive than stepper motors

Lower Holding Torque

Servo-Controlled Motors (cont’d)

Faster than stepper motor

Feedback determines correct positioning More complex than stepper motor

Oscillates when close to the desired position due to feedback

Servo-Controlled Motors (cont’d)

Diagram Source: http://www.machinedesign.com/ASP/viewSelectedArticle.asp?strArticleId=58153&strSite=MDSite&Screen=CURRENTISSUE&CatID=3

On-Off Controller

Logic control with only two states e.g. temperature control with a boiler that can

only be turned on or off

Determines whether the measurement is below a threshold If below threshold, take action Otherwise, no action is required

PID Controller

Proportional Integral Differential Controller

Alternative to on-off control

(error) = (set point) – (measurement) Set point is what you would like the value to Error would be the difference between the set

point and actual value

PID Controller (cont’d)

Image Source: http://www.netrino.com/Publications/Glossary/PID.html

P (proportional)

If the proportional gain is well chosen, the time it takes to reach a new set point will be as short as possible, with overshoot (or undershoot) and oscillation minimized.

Large proportional gain needed for quick response

Small proportional gain needed to minimize overshoot and oscillation

Achieving both at the same time may not be possible in all systems.

D (differential)

If the output is changing rapidly, there is a high chance of overshoot or undershoot

The derivative is the change in value from the previous sample to the current sample

Adding this to the proportional controller slows down the response time, but also decreases overshoot and ripple effects

I (integral)

If the is no change in value over time, the output may settle at the wrong value.

Integral value is small in general

Persistent error will cause sum to become large enough to cause a change

PID Controller Summary

Derivative and/or integral terms are added to proportional controllers to improve qualitative properties of a particular response.

When all three terms are used together, the acronym used to describe the controller is PID.

Schematic Presentation of PID

Software

Used to configure the PID controller

Manages data acquisition from sensor

DataLab 2000

References

Wang, H. Siu, K., Ju, K., Moore L. C., and Chon, K. H., Identification of Transient Renal Autoregulatory Mechanism Using Time-Frequency Spectral Techniques. IEEE Transactions on Biomedical Engineering, June 2005 (52) 6:1033-1039

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Brainstorming . . .