System Characteristics

Class 3

Recap

SYSTEM CHARACTERISTICS

Medical Measurement Constraints

The amplitude and frequency ranges for each parameter

are the major factors that aff ect the design of all

instrument components

Proper measurand-sensor interface cannot be obtained

Medical variables are seldom deterministic

External energy must be minimized to avoid any damage

Nearly all biomedical measurements depend on some form of energy

being applied to the living tissue or to the sensor, for example:

X-ray, ultrasonic imaging and electromagnetic or Doppler

ultrasonic

Blood flow-meters depend on externally applied energy interacting

with living tissue

Safe level of applied energy is an important consideration

Equipment must be reliable

Additional Medical Measurement Constraints

ReliableSimple to operateWithstand physical abuse and exposure to corrosive chemicalsElectrical safety (minimize electric shock hazard)

Classification of Biomedical Instruments

Quantity being sensed:Pressure, flow, temperature, potential, etc.

Advantage: easy comparison of different methods for measuring any quantity

Principle of transduction:Resistive, capacitive, inductive, ultrasonic or electrochemicalAdvantages: a. different applications of each principle can be used to strengthen understanding of each conceptb. newer applications readily apparent

Measurement technique for each physiological system:

Cardiovascular, pulmonary, nervous, endocrineAdvantage: isolates all important measurements for specialistsDisadvantage: considerable overlap of quantities sensed and the principles of transduction used

Classification of Biomedical Instruments...

Clinical medicine specialties:Pediatrics, Obstetrics, Cardiology, Radiology, etc.Advantage: valuable for medical personnel interested in specialized instruments

Interfering and Modifying Inputs

Desired input: the measurand that the

instrument is designed to isolate and measure

Interfering inputs: quantities that inadvertently

affect the instrument as a consequence of the

principles used to acquire & process the desired

inputs

Modifying inputs: undesired quantities that

indirectly affect the output by altering the

performance of the instrument itself

Modifying inputs can affect processing of either desired or

interfering inputs

Some undesirable quantities can act as both a modifying

input and an interfering input

Example

A simplified ECG recording system provides a good example:

In this recording system:

The desired input is: Vecg –electrocardiographic voltage between 2 electrodes (RA & LA)

The interfering inputs are:

50 Hz or 60 Hz (power-line) noise voltage induced in the shaded loop by ac magnetic fields

Also the difference between the currents running through each of the electrodes to the patient and to the ground causes a voltage on Zbody

Example...

In ECG, the example of a modifying input is the orientation of the patient cables. If the plane of the cable is parallel to the ac magnetic field, magnetically introduced interference is zero. If the plane of the cables is perpendicular to the ac magnetic field, magnetically introduced interference is maximal.

Time–dependent changes in electrode impedance

Electrode motion

Elimination of Interfering and Modifying Inputs

To reduce or eliminate the effects of most interfering and modifying inputs we have two alternatives:

1. Alter the design of essential instrument components (preferred, but hard to achieve)

2. Add new components to offset the undesired inputs

Sensor characteristics

Static characteristicsThe properties of the system after all transient effects have settled to their final or steady stateAccuracy, Discrimination, Precision, Errors, Drift, Sensitivity, Linearity, Hysteresis (backslash)

Dynamic characteristicsThe properties of the system transient response to an inputZero order systemsFirst order systemsSecond order systems

Accuracy & discrimination

Accuracy is the capacity of a measuring instrument to give RESULTS close to the TRUE VALUE of the measured quantity

Accuracy is related to the bias of a set of measurements

(IN)Accuracy is measured by the absolute and relative errors

More about errors in a later

Discrimination is the minimal change of the input necessary to produce a detectable change at the output

Discrimination is also known as RESOLUTION When the increment is from zero, it is called THRESHOLD

Precision

The capacity of a measuring instrument to give the same

reading when repetitively measuring the same quantity

under the same prescribed conditions

Precision implies agreement between successive readings, NOT

closeness to the true value

Precision is related to the variance of a set of measurements

Precision is a necessary but not suffi cient condition for accuracy

Two terms closely related to precision

Repeatability

The precision of a set of measurements taken over a short time

interval

Reproducibility

The precision of a set of measurements BUT

taken over a long time interval or

Performed by different operators or

with different instruments or

in different laboratories

Example

Shooting dartsDiscrimination

The size of the hole produced by a dartWhich shooter is more accurate?Which shooter is more precise?

Shooter A Shooter B

Accuracy and ErrorsSystematic errors

Result from a variety of factorsInterfering or modifying variables (i.e., temperature)

Drift (i.e., changes in chemical structure or mechanical stresses)

The measurement process changes the measurand (i.e., loading errors)

The transmission process changes the signal (i.e., attenuation)

Human observers (i.e., parallax errors)Systematic errors can be corrected with COMPENSATION methods (i.e. feedback, fi ltering)

Random errorsAlso called NOISE: a signal that carries no information True random errors (white noise) follow a Gaussian distributionSources of randomness:

Repeatability of the measurand itself (i.e., height of a rough surface)Environmental noise (i.e., background noise picked by a microphone)Transmission noise (i.e., 60Hz hum)

Signal to noise ratio (SNR) should be >>1With knowledge of the signal characteristics it may be possible to interpret a signal with a low SNR (i.e., understanding speech in a loud environment)

Example: systematic and random errors

More static characteristics

Input range

The maximum and minimum value of the physical variable that can be measured (i.e., -40F/100F in a thermometer)

Output range can be defi ned similarly

Sensitivity

The slope of the calibration curve y=f(x)

An ideal sensor will have a large and constant sensitivity

Sensitivity-related errors: saturation and “dead-bands”

Linearity

The closeness of the calibration curve to a specifi ed straight line (i.e., theoretical behavior, least-squares fi t)

Monotonicity

A monotonic curve is one in which the dependent variable always increases or decreases as the independent variable increases

Hysteresis

The diff erence between two output values that correspond to the same input depending on the trajectory followed by the sensor (i.e., magnetization in ferromagnetic materials)

Backslash: hysteresis caused by looseness in a mechanical joint