Figure 1.1 Generalized instrumentation system The sensor converts energy or information from the measurand to another form (usually electric). This signal is the processed and displayed so that humans can perceive the information. Elements and connections $dG

1
Chapter 1-Webster Basic Concepts of Medical
Instrumentation
2
Figure 1.1 The sensor converts energy or
information from the measurand to another form
(usually electric). This signal is the processed
and displayed so that humans can perceive the
information. Elements and connections shown by
dashed lines are optional for some applications.
Generalized instrumentation system
3
Measurand Physical quantity

• Biopotential
• Pressure
• Flow
• Dimensions (imaging)
• Displacement (velocity, acceleration, force)
• Impedance
• Temperature
• Chemical Concentration

4
Sensor and Transducer

• Transducer
• Converts one form of energy to another
• Sensor
• Converts a physical measurand to an electrical
  output
• Interface with living system
• Minimize the energy extracted
• Minimally invasive

displacement
electric voltage
Strain gage
pressure
diaphragm
5
Signal Conditioning

• Amplification
• Filtering
• Impedance matching
• Analog/Digital for signal processing
• Signal form (time and frequency domains)

6
Output Display

• Numerical
• Graphical
• Discrete or continuous
• Visual
• Hearing

7
Auxiliary Element

• Calibration Signal
• Control and Feedback (auto or manual)
• Adjust sensor and signal conditioning

8
1.3 Alternative Operational Modes

• Direct Mode Measurand is readily accessible
• Temperature
• Heart Beat
• Indirect Mode desired measurand is measured by
  measuring accessible measurand.
• Morphology of internal organ X-ray shadows
• Volume of blood pumped per minute by the heart
  respiration and blood gas concentration
• Pulmonary volumes variation in thoracic
  impedance

9
1.3 Sampling and Continuous Modes

• Sampling and collecting data will depend on the
  following
• The rate of change in the measurand
• Condition of the patient
• Generating and Modulating Sensors
• Generating sensors produce their outputs from
  energy taken from measurand (Photovoltaic cell)
• Modulating Sensors uses the measurand to alter
  the flow of energy from an external source
  (Photoconductive cell)
• Analog and Digital Modes
• Real-Time and Delayed-Time Modes

10
1.4 Medical Measurement Constraints

• Magnitude and frequency range of medical
  measurand are very low
• Proper measurand-sensor interface cannot be
  obtained
• Medical variables are seldom deterministic
• External energy must be minimized to avoid any
  damage
• Equipment must be reliable

11
1.5 Classification of Medical Instrument

• Quantity that is sensed
• pressure, flow, temp
• Principle of transduction
• resistive, capacitive, electrochemical,
  ultrasound
• Organ system
• cardiovascular, pulmonary, nervous
• Medicine specialties
• pediatrics, cardiology, radiology

12
1.6 Interfering and Modifying Inputs
Desired Inputs measurands that the instrument is
designed to isolate. Interfering Inputs
quantities that unintentionally affect the
instrument as a consequence of the principles
used to acquire and process the desired
inputs. Modifying Inputs undesired quantities
that indirectly affect the output by altering the
performance of the instrument itself.
13
Figure 1.2 Simplified electrocardiographic
recording system Two possible interfering inputs
are stray magnetic fields and capacitively
coupled noise. Orientation of patient cables and
changes in electrode-skin impedance are two
possible modifying inputs. Z1 and Z2 represent
the electrode-skin interface impedances.
1.6 Interfering and Modifying Inputs
Desired input Electrocardiographic voltage
Vecg Interfering input voltage due to 60-Hz
14
1.7 Compensation Techniques

• To eliminate interfering and modifying input
• Alter the design of essential instrument
  components to be less sensitive to interference.
  (preferred)
• Adding new components designed to offset the
  undesired inputs.

15
1.7 Compensation Techniques

• Inherent Insensitive
• Negative Feedback to minimize Gd which is
  effected by the modifying inputs
• (xd Hfy)Gd y (1.1)
• xdGd y(1 HfGd) (1.2)
• 
  (1.3)
• Signal Filtering (electric, mechanical, magnetic)
• Opposing Inputs

16
Compensation Techniques- Example
An amplifier with gain 10 that has 20
fluctuation due to temperature and environmental
change. How will compensate the system to
minimize the fluctuation?
17
1.8 Biostatistics

• Applications of Statistics to medical data
• Design experiment
• Clinical Study summarize, explore, analyze
• Draw inference from data estimation, hypothesis
• Evaluate diagnostic procedures assist clinical
  decision making

18
Medical Research Studies

• - Observational Characteristics of patients are
  observed and recorded
• Case-series describe characteristic of group
• Case-control observe group that have some
  disease
• Cross-sectional Analyze characteristics of
  patients
• Cohort determine if a particular characteristic
  is a precursor for a disease.
• Experimental Intervention Effect of a medical
  procedure or treatment is investigated
• Controlled Comparing outcomes to drug and
  placebo
• Uncontrolled No placebo and no comparison
• Concurrent controls patient are selected the
  same way and for the same time.
• Double-blind

19
Statistical Measurements

• Measures of the mean and central tendency
• Mean
• Median Middle value (used for skewed data)
• Mode is the observation that occurs most
  frequently
• Geometric Mean used with data on a logarithmic
  scale

20
Statistical Measurements
Measure of spread or dispersion of data Range
Difference between the largest and smallest
observation Standard deviation is a measure of
the spread of data about the mean For symmetric
distribution 75 of the data lies between (mean -
2s) and (mean 2s) Coefficient of variation
standardize the variation to compare data
measured in different scales.
21
Statistical Measurements
Percentile gives the percentage of a
distribution that is less than or equal to the
percentile number. Standard error of the mean
(SEM) Express the variability to be expected
among the mean in future samples. Correlation
Coefficient r is a measure of a linear
relationship between numerical variables x and y
for paired observations
22

• Methods for inference about a value in a
  population of subjects from a set of
  observations.
• Estimation and confidence of interval
• are used to estimate specific parameters such as
  the mean and the variance.
• Hypothesis testing and P-value
• reveals whether the sample gives enough evidence
  for us to reject the null hypothesis. P-value
  indicates how often the observed difference would
  occur by chance alone.

23

• Methods for measuring the accuracy of a
  diagnostic procedure
• Sensitivity of a test Probability of its
  yielding positive results in patients who
  actually have the disease.
• Specificity of a test Probability of its
  yielding negative results in patients who do not
  have the disease
• Prior Probability the prevalence of the
  condition prior to the test.

24
Characteristics of Instrument Performance

• Two classes of characteristics are used to
  evaluated and compare new instrument
• Static Characteristics describe the performance
  for dc or very low frequency input.
• Dynamic Characteristics describe the performance
  for ac and high frequency input.

25

• 1.9 Generalized Static Characteristics
• Parameters used to evaluate medical instrument
• Accuracy The difference between the true value
  and the measured value divided by the true value
• Precision The number of distinguishable
  alternatives from which a given results is
  selected 2.434 or 2.43
• Resolution The smallest increment quantity that
  can be measured with certainty
• Reproducibility The ability to give the same
  output for equal inputs applied over some period
  of time.

26

• 1.9 Generalized Static Characteristics
• Parameters used to evaluate medical instrument
• Statistical Control Systematic errors or bias
  are tolerable or can be removed by calibration.
• Statistical Sensitivity the ratio of the
  incremental output quantity to the incremental
  input quantity, Gd.

27
Finding static sensitivity Gd using line equation
with the minimal sum of the squared difference
between data points and the line
28
Figure 1.3 (b) Static sensitivity zero drift and
sensitivity drift. Dotted lines indicate that
zero drift and sensitivity drift can be negative.
Zero Drift all output values increase or
decrease by the same amount due to manufacturing
misalignment, variation in ambient temperature,
vibration,. Sensitivity Drift Output change in
proportion to the magnitude of the input. Change
in the slope of the calibration curve.
29
Figure 1.4 (a) Basic definition of linearity for
a system or element. The same linear system or
element is shown four times for different inputs.
(b) A graphical illustration of independent
nonlinearity equals ?A of the reading, or ?B of
full scale, whichever is greater (that is,
whichever permits the larger error).
(x1 x2)
Linearity Independent nonlinearity - A
deviation of the reading - B deviation of the
full scale
x1
y1
(y1 y2)
Linear
Linear
system
system
and
and
Kx1
Ky1
x2
y2
Linear
Linear
system
system
(a)
Least-squares straight line
y (Output)
B of full scale
A of reading
Overall tolerance band
xd (Input)
Point at which
Input Ranges (I) Minimum resolvable input lt I lt
normal linear operating range
A of reading B of full scale
(b)
30
Example
A linear system described by the following
equation y2x3. Find the overall tolerance band
for the system if the input range is 0 to 10 and
its independent nonlinearity is 0.5 deviation of
the full scale and 1.5 deviation of the reading.
31

• Input Impedance
• disturb the quantity being measured.
• Xd1 desired input (voltage, force, pressure)
• Xd2 implicit input (current, velocity, flow)
• P Xd1.Xd2 Power transferred across the
  tissue-sensor interface
• Generalized input impedance Zx

• Goal Minimize P, when measuring effort variable
  Xd1, by maximizing Zx which in return will
  minimize the flow variable Xd2.
• Loading effect is minimized when source impedance
  Zs is much smaller then the Zx

32
1.10 Generalized Dynamic Characteristics
Most medical instrument process signals that are
functions of time. The input x(t) is related to
the output y(t) by
ai and bi depend on the physical and electrical
parameters of the system.
Transfer Functions The output can be predicted
for any input (transient, periodic, or random)
33
Frequency Transfer Function Can be found by
replacing D by j?
Example If x(t) Ax sin (? t) then y(t)
H(?) Ax sin (? t /_H(?))
34
Figure 1.5 (a) A linear potentiometer, an
example of a zero-order system. (b) Linear static
characteristic for this system. (c) Step response
is proportional to input. (d) Sinusoidal
frequency response is constant with zero phase
shift.
Zero-Order Instrument
a0 y(t) b0 x(t)
K static sensitivity
35
First-Order Instrument
Where ? is the time constant
36
First-Order Instrument
Output y(t)
R


Slope
K
1
C
y(t)
x(t)
-
-
Input x(t)
(a)
(b)
Y (jw)
Log
x(t)
scale
X (jw)
1
1.0
?S
0.707
?L
wS
wL
Log scale w
t
(c)
(d)
f
y(t)
0
1
?S
Log scale w
?L
0.63
- 45
-90
?L
?S
t
Example 1.1 High-pass filter
37
Second-Order Instrument
Many medical instrument are 2nd order or higher
Operational Transfer Function
Frequency Transfer Function
38
Figure 1.7 (a) Force-measuring spring scale, an
example of a second-order instrument. (b) Static
sensitivity.
2nd order mechanical force-measuring Instrument
B viscosity constant Ks spring constant
Natural freq.
Damping ratio
(c) Step response for overdamped case ? 2,
critically damped case ? 1, underdamped case ?
0.5. (d) Sinusoidal steady-state frequency
response, ? 2, ? 1, ? 0.5.
39
Overdamped
Critically damped
Underdamped
y(t)
1
Ks
0.5
Damped natural freq.
t
40
Example 1.2 for underdamped second-order
instruments, find the damping ratio from the step
response
and
Logarithmic decrement
41
Time Delay System
Log
Y (jw)
scale
K
X (jw)
Log scale w
f
Log scale w
0
42
Figure 1.8 Design process for medical
instruments Choice and design of instruments are
affected by signal factors, and also by
environmental, medical, and economic factors.
Design Criteria
43
Commercial Medical Instrumentation Development
Process

• Ideas come from people working in the health
  care
• Detailed evaluation and signed disclosure
• Feasibility analysis and product description
• Medical need
• Technical feasibility
• Brief business plan (financial, sales, patents,
  standards, competition)
• Product Specification (interface, size, weight,
  color)
• What is required but nothing about how
• Design and development (software and hardware)

44
Commercial Medical Instrumentation Development
Process

• Prototype development
• Testing on animals or human subjects
• Final design review (test results for,
  specifications, subject feedback, cost)
• Production (packaging, manual and documents)
• Technical support

45
Regulation of Medical Devices
Medical devices is any item promoted for a
medical purpose that does not rely on chemical
action to achieve its intended effect 2 Ways
for Medical Devices Classification First Way
(based on potential hazards) Class I general
controls Class II performance standards
Class III premarketing approval Second Method
(see Table 1.2 in textbook) preamendment,
postamendment, substantially equivalent,
implant, custom, investigational, transitional
46
Regulation of Medical Devices
Second Way of classifications (see Table 1.2 in
textbook) Preamendment Devices on the market
before 5/28/1976 Postamendment Devices on the
market after 5/28/1976 Substantially equivalent
Equivalent to preamendment devices Implant
devices inserted in human body and intended to
remain there for gt30 days. Custom Devices not
available to other licensed and not in finished
form Investigational Unapproved devices
undergoing clinical investigation Transitional
devices that were regulated as drugs and now
defined as medical devices