Basic Concepts of Medical Instruments/ Transducers

1. The key physiological parameters measured in clinical settings.
2. Define biomedical instrumentation and its unique challenges in design.
3. The core Structure of a general medical instrument.

1. Basic Concepts of
Medical Instruments
By Assoc. Prof. Ramy Elghwas

2. Introduction of Medical Instruments
•Hello Everyone
•I am your Instructor through this course
•Our course will focus on transducers used for
Healthcare
•The first lecture will be general overview for:
1.The key principles
2.Why do these principles matter?
3.How are these principle connected ?

3. Introduction of Medical Instruments
In the beginning
•Think of a device U used recently to measure a sign or symptom in
the body.

4. Introduction of Medical Instruments
•Learning objectives & Plan
•By the end of this lecture, students will be able to:
1.List key physiological parameters measured in clinical settings.
2.Define biomedical instrumentation and its unique challenges.
3.Explain the core Structure of a general medical instrument.
4.Identify major classes of biomedical instruments.
5.Discuss critical safety considerations (patient, operator, device).
6.Recognize the required accuracy levels for common vital signs.

5. Introduction of Medical Instruments
•Learning objectives & Plan
•By the end of this lecture, students will be able to:
1.List key physiological parameters measured in clinical settings.
2.Define biomedical instrumentation and its unique challenges.
3.Explain the core Structure of a general medical instrument.
4.Identify major classes of biomedical instruments.
5.Discuss critical safety considerations (patient, operator, device).
6.Recognize the required accuracy levels for common vital signs.

6. Introduction of Medical Instruments
•Global expenditure on
healthcare as a share of world
income has been increasing.
•Healthcare financing in
developing countries in the 21st
century has been largely shaped
by the flow of resources.
•The data show, in 1880
government health spending
was below 1% of GDP in all
countries.
•In the first half of the 20th
century, and by 1970
government spending on
healthcare was above 2% of GDP
in all these countries.
Why Should Engineers Care about Medicine?

7. Introduction of Medical Instruments
What physiological parameters Should Engineers help
Physicians to measure?

8. Introduction of Medical Instruments
•Learning objectives & Plan
•By the end of this lecture, students will be able to:
1.List key physiological parameters measured in clinical settings.
2.Define biomedical instrumentation and its unique challenges.
3.Explain the core components of a general medical instrument.
4.Identify major classes of biomedical instruments.
5.Discuss critical safety considerations (patient, operator, device).
6.Recognize the required accuracy levels for common vital signs.

9. Introduction of Medical Instruments
•Learning objectives & Plan
•By the end of this lecture, students will be able to:
1.List key physiological parameters measured in clinical settings.
2.Define biomedical instrumentation and its unique challenges.
3.Explain the core Structure of a general medical instrument.
4.Identify major classes of biomedical instruments.
5.Discuss critical safety considerations (patient, operator, device).
6.Recognize the required accuracy levels for common vital signs.

10. Introduction of Medical Instruments
Biomedical instrumentation and its unique
challenges.

11. Introduction of Medical Instruments
Define biomedical instrumentation and its unique
challenges.
Category Core Challenge Example
Safety & Regulations
1.Strict regulatory frameworks (FDA, ISO 13485) require extensive documentation, testing, and
validation before approval.
2.Devices must meet biocompatibility, electrical safety, and sterility standards.
3.Risk management (ISO 14971) demands identification and mitigation of all potential hazards —
mechanical, electrical, biological, or software-related.
1.A patient monitor must undergo electrical
leakage testing and fail-safe design to
prevent harm during a power fault.
Human Factors &
Usability
1.Designing for users (nurses, patients, clinicians) requires intuitive interfaces and minimal training.
2.Avoiding user errors through ergonomic design, clear displays, and standardized controls.
3.Ensuring accessibility for a diverse population (age, disability, language barriers).
1.Poorly placed alarm buttons on infusion
pumps have led to clinical errors; redesigns
must follow human factors engineering
standards
Accuracy, Precision, and
Reliability
1.Maintaining measurement accuracy and sensitivity across environmental and physiological
variations.
2.Designing for long-term reliability —sensors can drift or degrade in harsh biological environments.
3.Calibration and self-checking systems must ensure consistent performance over time.
1.Blood glucose meters must stay within ±15%
accuracy over thousands of readings.
Miniaturization &
Integration
1.Creating smaller, portable, or implantable systems without sacrificing accuracy or battery life.
2.Integrating sensing, computing, and communication into compact systems (e.g., wearable ECGs,
smart patches).
3.Managing thermal control, signal noise, and power constraints at small scales.
1.Wearable ECG patch

12. Introduction of Medical Instruments
Define biomedical instrumentation and its unique
challenges.
Category Core Challenge Example
Data Management &
Cybersecurity
1.Handling large volumes of patient data securely (HIPAA/GDPR compliance).
2.Preventing cyberattacks on networked medical devices (e.g., wireless infusion pumps or
pacemakers).
3.Ensuring interoperability between different hospital systems (HL7, DICOM standards)
A wireless ventilator must encrypt
communication to prevent unauthorized control
or data leaks.
Cost &
Manufacturability
1.Balancing performance and cost —hospitals and developing markets often require affordable,
robust devices.
2.Designing for mass production while maintaining calibration and quality control.
3.Planning for serviceability, spare parts, and reusable components in clinical environments.
Low-cost portable ultrasound machines must
deliver acceptable imaging quality using fewer
components
Ethics
1.Designing systems that respect privacy and autonomy (especially with AI and wearable monitoring).
2.Avoiding bias in algorithms trained on non-representative populations.
3.Ensuring equitable access and avoiding devices that serve only wealthy institutions or regions.
AI-based diagnostic tools may underperform in
patients of different ethnic backgrounds if
training data are limited.
Innovation vs.
Regulation
1.Balancing rapid innovation (e.g., AI, nanotech, robotics) with slow regulatory approval cycles.
2.Managing clinical validation timelines —sometimes years before commercialization.
3.Avoiding overengineering that makes devices complex or difficult to use
Robotic surgery systems undergo years of
validation before FDA approval despite rapid
software iteration cycles.

13. Introduction of Medical Instruments
•Learning objectives & Plan
•By the end of this lecture, students will be able to:
1.List key physiological parameters measured in clinical settings.
2.Define biomedical instrumentation and its unique challenges.
3.Explain the core Structure of a general medical instrument.
4.Identify major classes of biomedical instruments.
5.Discuss critical safety considerations (patient, operator, device).
6.Recognize the required accuracy levels for common vital signs.

14. Introduction of Medical Instruments
•Learning objectives & Plan
•By the end of this lecture, students will be able to:
1.List key physiological parameters measured in clinical settings.
2.Define biomedical instrumentation and its unique challenges.
3.Explain the core Structure of a general medical instrument.
4.Identify major classes of biomedical instruments.
5.Discuss critical safety considerations (patient, operator, device).
6.Recognize the required accuracy levels for common vital signs.

15. Introduction of Medical Instruments
The core
Structure of a
general medical
instrument
Basic
Signals
Instruments Design
Safety
Math
Practice
Research
Questions
Summary

16. Introduction of Medical Instruments
•Key signal characteristics include:
1.Amplitude:The magnitude or
strength of the signal.
2.Frequency:The rate at which
the signal repeats itself (cycles
per second, or Hertz).
3.Phase:The relative position of a
point in time (an instant) on a
waveform cycle.
4.Period:The time it takes for one
complete cycle of the signal.
•Common signal types include:
1.Sinusoidal Signals:Pure tones,
described by amplitude,
frequency, and phase.
2.Square Waves:Signals that
alternate abruptly between two
levels.
3.Triangle Waves:Signals that
linearly increase and decrease
between two levels.
4.Noise:Unwanted signals that
can corrupt the desired signal.
Basic
Signals

17. Introduction of Medical Instruments
•Devices measure physical quantities and
convert them into signals to be processed
and interpreted. Key components of an
instrument include:
•Sensor:The element that directly
interacts with the physical quantity being
measured (e.g., a temperature sensor, a
pressure sensor).
•Signal Conditioning:Circuits that amplify,
filter, or otherwise modify the sensor's
output signal to make it suitable for
further processing.
•Analog-to-Digital Converter (ADC):
Converts analog signals into digital signals
for processing by a computer or
microcontroller.
•Digital-to-Analog Converter (DAC):
Converts digital signals into analog signals
for controlling actuators or displaying
information.
•Display:Presents the measured value to
the user (e.g., a digital display, a graph).
Instruments

18. Introduction of Medical Instruments
•Medical instrument characteristics include:
•Accuracy:The closeness of the measured value to
the true value.
•Precision:The repeatability of the measurement.
•Resolution:The smallest change in the measured
quantity that the instrument can detect.
•Sensitivity:The change in the instrument's output
for a given change in the measured quantity.
•Linearity:The degree to which the instrument's
output is proportional to the measured quantity.
•Range:The minimum and maximum values that the
instrument can measure.
Instruments

19. Introduction of Medical Instruments
•Problem 1 —Accuracy (Digital clinical thermometer)
•Learning objective:quantify accuracy(bias and typical error) of a thermometer vs.
a reference standard.
•Problem:During calibration, a clinical digital thermometer gives these readings
while a laboratory reference instrument reports the true core temperature values:
•Reference (°C): 36.5, 37.0, 37.5, 38.0Thermometer (°C): 36.7, 37.2, 37.8, 38.1
•Calculate:
1.The error for each measurement (device − reference).
2.The bias(mean error).
3.The mean absolute error (MAE)and the root-mean-square error (RMSE).
4.Based on a manufacturer accuracy claim of ±0.2 °C, does this device meet the claim?
•Solution (step-by-step):
1.Individual errors:
errors = [36.7−36.5, 37.2−37.0, 37.8−37.5, 38.1−38.0] = [0.20, 0.20, 0.30, 0.10] °C.
2.Bias (mean error):
bias = (0.20 + 0.20 + 0.30 + 0.10) / 4 = 0.20 °C.
3.MAE and RMSE:
MAE = (|0.20|+|0.20|+|0.30|+|0.10|)/4 = 0.20 °C.
RMSE = sqrt((0.20² + 0.20² + 0.30² + 0.10²)/4) ≈ sqrt(0.045) ≈ 0.212 °C.
4.Interpretation vs spec:
•The biasis +0.20 °C and the average absolute error is 0.20 °C. RMSE ≈ 0.212 °C.
•The device is right atthe ±0.2 °C claim for bias/MAE, while RMSE slightly exceeds it (0.212 °C). This
suggests marginal compliance; a larger sample or formal calibration would be needed to certify
compliance.
Accuracy
The closeness of the measured
value to the true value.

20. Introduction of Medical Instruments
•Problem 2 —Precision (Pulse oximeter repeated-readings)
•Learning objective:compute precisionusing standard
deviation and coefficient of variation (CV).
•Problem:A pulse oximeter gives these repeated SpO₂
readings on a steady patient: 95, 94, 95, 96, 95 (%) .
Compute:
1.The mean SpO₂.
2.The sample standard deviation (precision).
3.The coefficient of variation (CV = sd/ mean ×100%).
Comment whether the device has good precision if the target CV is
<1%.
•Solution (step-by-step):
1.Mean:(95 + 94 + 95 + 96 + 95)/5 = 95 %.
2.Sample standard deviation (s):
Deviations from mean: [0, −1, 0, +1, 0] → squared sum = 2.
Sample variance = 2/(n−1) = 2/4 = 0.5 → s = sqrt(0.5) ≈ 0.707 %.
3.CV:CV = 0.707 / 95 ×100% ≈ 0.744%.
4.Interpretation:CV ≈ 0.74% < 1% → precision is goodrelative to the
target CV.
Precision
The repeatability of the
measurement.

21. Introduction of Medical Instruments
•Problem 3 —Resolution (Patient-weighing scale)
•Learning objective:understand resolution(LSB) and how
quantization affects relative error for small vs large masses.
•Problem:A bedside scale reports weight with a display increment
(resolution, LSB) of 0.1 kg(it rounds to the nearest 0.1 kg).
1.What is the maximum quantization error (worst-case) for any reading?
2.For a patient of 70.30 kg, what is the maximum relative error (%) due
to quantization?
3.For a small specimen of 0.15 kg, what is the maximum relative error
(%)? Comment on suitability of the scale for both tasks.
•Solution (step-by-step):
1.Half-LSB (max quantization error):LSB = 0.1 kg → max error = ±(LSB/2)
= ±0.05 kg.
2.Relative error for 70.30 kg:(0.05 / 70.30) ×100% ≈ 0.0711%(tiny —
acceptable).
3.Relative error for 0.15 kg:(0.05 / 0.15) ×100% ≈ 33.33%(huge —
unacceptable).
4.Interpretation:The scale’s resolution (0.1 kg) is fine for adult weights
but inadequatefor small masses (e.g., specimens or neonate micro-
measurements) where the quantization error becomes a large fraction
of the value.
Resolution
The smallest change in the measured
quantity that the instrument can detect.

22. Introduction of Medical Instruments
•Problem 4 —Sensitivity (Blood-pressure transducer)
•Learning objective:convert sensor voltage to pressure using
sensitivityand compute the minimum detectable pressure from
ADC resolution.
•Problem:An invasive blood-pressure transducer has an output of
0.50 Vat 0 mmHg and increases by 0.01 V per mmHg(sensitivity =
0.01 V/mmHg). The measurement system’s A/D converter has a
voltage LSB of 1.0 mV (0.001 V).
1.If the ADC reads 1.10 V, what is the calculated blood pressure
(mmHg)?
2.What is the smallest change in pressure the system can detect due to
ADC LSB? (in mmHg)
3.Comment whether this detectability (resolution) is clinically useful if
clinicians need to resolve 1 mmHg changes.
•Solution (step-by-step):
1.Convert voltage to pressure:Pressure (mmHg) = (V − V0) / sensitivity =
(1.10 − 0.50) / 0.01 = 60 mmHg.
2.Minimum detectable pressure step from ADC LSB:ΔP_min= LSB_V /
sensitivity = 0.001 / 0.01 = 0.1 mmHg.
3.Interpretation:The system can resolve 0.1 mmHgsteps (better than 1
mmHg), so the ADC resolution is more than adequatefor a clinical
need of 1 mmHg resolution.
Sensitivity
The change in the instrument's output for
a given change in the measured quantity.

23. Introduction of Medical Instruments
•Problem 5 —Linearity (Sensor calibration)
•Learning objective:evaluate linearityby fitting a straight line to calibration data
and computing maximum non-linearity as percent of full-scale.
•Problem:A pressure sensor is calibrated at three known pressures:
•Pressure (mmHg): 0, 50, 100
•Measured output (V): 0.02, 0.52, 1.05
1.Using linear least squares, find the slope (V/mmHg) and intercept (V).
2.Compute predicted outputs at the three calibration pressures and the residuals
(measured − predicted).
3.Find the maximum absolute residual and express it as a percentage of the full-scale range
(FSR = max_output− min_output). If the linearity spec is ±2% FSR, does the sensor meet
it?
•Solution (step-by-step):
•Least-squares line:slope ≈ 0.01030 V/mmHg, intercept ≈ 0.01500 V.
1.Predicted outputs and residuals:
•At 0 mmHg: predicted = 0.01500 V, measured = 0.02 V → residual = 0.0050 V.
•At 50 mmHg: predicted = 0.53 V, measured = 0.52 V → residual = −0.0100 V.
•At 100 mmHg: predicted = 1.045 V, measured = 1.05 V → residual = 0.0050 V.
2.Max absolute residual and percent of FSR:
•FSR = 1.05 − 0.02 = 1.03 V.
•Max |residual| = 0.0100 V.
•Percent non-linearity = (0.0100 / 1.03) ×100% ≈ 0.97% FSR.
3.Interpretation:The maximum non-linearity ≈ 0.97% FSR, which is well withinthe ±2% FSR
linearity spec.
Linearity
The degree that the instrument's output
is proportional to the measured quantity.

24. Introduction of Medical Instruments
•Problem 6 —Range of measurement (Infusion pump flow range & dynamic
range)
•Learning objective:understand rangeand dynamic rangeand evaluate if a device’s
range covers clinical needs.
•Problem:An infusion pump is specified to deliver rates from 0.5 mL/h(minimum)
to 500 mL/h(maximum). A neonatal protocol may require 0.1 mL/hflows.
•Compute:
1.The device dynamic range ratio (max/min) and the dynamic range in decades(log10) and
dB(use 20·log10(ratio)).
2.Can the pump deliver the neonatal 0.1 mL/h? If not, by what factor would the minimum
need to change? Express how much higher the pump’s minimum is relative to the
neonatal requirement (percentage).
•Solution (step-by-step):
1.Dynamic range:
•Ratio = 500 / 0.5 = 1000.
•Decades = log10(1000) = 3.0 decades.
•Dynamic range in dB = 20·log10(1000) = 60 dB.
2.Neonatal coverage check:
•Required neonatal minimum = 0.1 mL/h. Device min = 0.5 mL/h.
•The pump cannotdeliver 0.1 mL/h; its minimum is 5×the neonatal need.
•Percent higher than required = (0.5 − 0.1)/0.1 ×100% = 400%higher.
3.Interpretation:The pump’s overalldynamic range is large (1000×, 60 dB) which suits
many applications, but the minimum stepis too large for very low neonatal flows; a
different device or a method (e.g., syringe pump with finer microflow) is required.
Range
The minimum and maximum values that
the instrument can measure.

25. Introduction of Medical Instruments
•Key design considerations include:
•Measurement Objectives:Clearly define
what needs to be measured and the
required accuracy, precision, and
resolution.
•Sensor Selection:Choose sensors that are
appropriate for the physical quantity
being measured and the environmental
conditions.
•Signal Conditioning Design:Circuits to
amplify, filter, and linearize the sensor's
output signal.
•Data Acquisition System Selection:
Choose a system that can sample the
signal at the required rate and provide
sufficient resolution.
•Calibration:In order to ensure accuracy.
•Power Consumption:Consider the power
especially for portable applications.
•Cost:Balance performance requirements
with cost constraints.
Design

26. Introduction of Medical Instruments
•The first step is to define what you need to measure. Vague objectives lead to flawed
designs.
•Is it electrical (like ECG), mechanical (like blood pressure), chemical (like glucose), or
thermal (temperature in case of ablation)?
•Research Question: "Can we continuously and accurately measure interstitial glucose
levels in diabetic patients within a range of 20-500 mg/dL, with a clinical accuracy of
±15% for values over 100 mg/dLand ±15 mg/dLfor values under 100 mg/dL, to enable
automated insulin dosing?"
Measurement
Objectives

27. Introduction of Medical Instruments
•The sensor is the interface with the biological world, converting a physiological
quantity into an electrical signal.
•Key Considerations:
1.Measurand: Match the sensor to the parameter (e.g., a chemical sensor for
glucose, a pressure sensor for blood pressure) .
2.Biocompatibility: For implantable or skin-contact sensors, materials must
be non-toxic, non-carcinogenic, and not cause allergic reactions .
3.Sensitivity and Selectivity: The sensor must produce a strong enough signal
for small changes in the measurand (sensitivity) and must not be affected
by other substances (selectivity). For example, a glucose sensor must
respond to glucose without significant interference from acetaminophen .
4.Size and Invasiveness: Design goals may require miniaturized or non-
invasive sensors for patient comfort and safety .
Sensor
Selection

28. Introduction of Medical Instruments
Sensor
Selection
Real-World Example: Glucose Sensor
Type: Enzymatic Biosensor
Principle: It uses the enzyme Glucose
Oxidase (GOD). The reaction of glucose
with GOD consumes oxygen and
produces hydrogen peroxide (H₂O₂). An
electrochemical transducer then
measures the change in O₂
concentration or the production of
H₂O₂, generating a current proportional
to the glucose level

29. Introduction of Medical Instruments
Biological signals from sensors are often weak, noisy, and non-linear.
Therefor, signal conditioning circuits prepare these signals for accurate
measurement. Such preparation steps may include:
1.Amplification: For instance, the current from a glucose sensor may
be in microamperes (µA) or nanoamperes (nA). Instrumentation
amplifier is used to boost this signal to a level suitable for the data
acquisition system (e.g., 0-5V) .
2.Filtering: Signals are corrupted by noise, such as 50/60 Hz power line
interference on ECG signals or motion artifacts on a continuous
glucose monitoring (CGM). Anti-aliasing filters (low-pass) are crucial
to remove high-frequency noise before the signal is digitized .
3.Linearization: Many sensors do not have a perfectly linear response.
Linearization circuits or software algorithms correct this, ensuring
the output is proportional to the input across the entire range
Signal
Conditioning

30. Introduction of Medical Instruments
Signal
Conditioning
Linearization
The 1st plot (readings vs measurand):“The
orange lineis the ideal proportional
response. The blue curve, the raw sensor
output, diverges especially at higher values.
The dashed green curve is the corrected
reading after linearization,lies nearly on the
ideal line across the range.
The error plot: raw error grows with the
measurand. After applying the linearizer, the
corrected error becomes small and close to
zero across the range. This demonstrates
why linearization is useful for meeting
accuracy specs.

31. Introduction of Medical Instruments
•The real world is analog; computation is digital. This
step is the bridge.
•Analog-to-Digital Converter (ADC):We select an ADC
with sufficientresolution(e.g., 16-bits to distinguish
tiny changes in the pulse amplitude) andsampling
rate(e.g., 100 Hz is plenty for a ~1 Hz heart rate signal,
satisfying the Nyquist criterion).
•Microcontroller:A microcontroller sequences the LEDs
(turning them on/off rapidly), reads the digitized values
from the ADC, and temporarily stores the data.
Data
Acquisition

32. Introduction of Medical Instruments
Data
Acquisition

33. Introduction of Medical Instruments
•Calibration creates the mathematical
relationship between your digital readings and
the true physiological value.
•The Procedure:
•You collect the reading from your device.
•You correlate this reading with ground-truth
measurements (e.g., from a CO-device in a lab study
on healthy volunteers).
•This empirical data is used to create a calibration
curve or lookup table, which is programmed into
your device's firmware.
Calibration

34. Introduction of Medical Instruments
Calibration
•A new Glucometer outputs a voltage V
(volts) that depends approximately
linearly on blood glucose conc. G (
mg/dL).
•A reference analyzer provides the true
glucose conc. G for a set of calibration
standards. The following paired
measurements were collected during
calibration:
y = 0.4814x -0.0067
R² = 0.9999
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
2.8
3
3.2
3.4
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
0 1 2 3 4 5 6 7
V (volts)
Glucose Conc. (mg/dl)
Measurements
Comp. bet. Stand. Glucometer &
New Glucometer
True glucose G (mg/dL) Sensor voltage V (Volt)
Linear (True glucose G (mg/dL))Linear (Sensor voltage V (Volt))

35. Introduction of Medical Instruments
Power in Medical Devices: It's a Life-Supporting Parameter
•InConsumer electronics, power management is maximizing battery life for
convenience. InMedical equipment, it's a fundamental safety and reliability
requirement. Let's break down why."
•1. Patient Safety & Device Availability
•Medical devices support or monitor vital functions. A power failure is unacceptable.
•Example:A ventilator must function continuously during a patient transfer or a power outage.
•2. Thermal Management & Device Longevity
•Waste power becomes heat. Excessive heat can:
•Damage sensitive electronic components.
•Cause patient discomfort or even burns (e.g., in wearable devices).
•Require bulky and expensive cooling systems, increasing size and cost.
•3. Portability & Usability
•Hospitals rely on mobile equipment (infusion pumps, portable monitors).
•Longer battery runtime means clinical workflow efficiency and reduced risk of interrupting
therapy.
•4. Regulatory & Cost Requirements
•FDA and international bodies (IEC 60601-1) have strict standards for power systems, including
backup duration and electrical safety.
•Efficient designs use smaller, lighter, and cheaper batteries, reducing the total cost of the device.
•Key Takeaway:Power consumption is not an afterthought; it is a core design
constraint that intersects with safety, reliability, and usability.
Power
Consumption

36. Introduction of Medical Instruments
Case Study: Power Budget for an Infusion Pump
•
Imagine we're designing a large-volume infusion pump, a common device in every hospital. Our
requirement is that it must run for at least 8 hours on battery during a power loss or patient transport."
Step 1: Define the Power Profile
•
Motor (Pumping):10 W (when active, ~30% of the time)
•
Electronics (CPU, Display, Sensors):5 W (constant)
•
Alarms & Connectivity:2 W (intermittent, we'll average as constant for safety)
Step 2: Calculate Average Power Draw
•
Motor Average Power = 10 W * 0.3 = 3 W
•
Total Average Power (P_avg) =3 W (Motor) + 5 W (Electronics) + 2 W (Alarms) =10 W
Step 3: Calculate Total Energy Required
•
Time on Battery (t) =8 hours
•
Energy (E) = P_avg* t =10 W * 8 h =80 Watt-hours (Wh)
Step 4: Select and Size the Battery
•
We choose a common Lithium-ion battery with a nominal voltage of14.4 V(4S configuration).
•
Required Battery Capacity (Ah) = Energy (Wh) / Voltage (V)
•
Capacity = 80 Wh/ 14.4 V ≈ 5.6 Ah (or 5600 mAh)
Step 5: Apply the Engineering Safety Margin
•
Batteries degrade over time. Components may draw more power than estimated.
•
We apply a20% safety margin.
•
Final Design Capacity = 5.6 Ah * 1.20 ≈ 6.7 Ah
•
Design Implication:Our pump design must be efficient enough to fit a 14.4V, ~6.7 Ah battery within its
physical and cost constraints.
Power
Consumption

37. Introduction of Medical Instruments
•Designing for the Market: Cost and Value
•"In Engineering, we often focus on Cost ▼. In the Medical Field, we must
design forValue ▲. Let's define these two key terms."
•What is COST?
•The total expenditure to create, produce, and support the device.
•Includes:R&D, Components bill of materials (BOM), Manufacturing, Testing, Regulatory
Approval, Service, and Support.
•It's what we, the manufacturer, spend.
•What is VALUE?
•The benefits and worth of the device from the customer's perspective (the hospital).
•Includes:Clinical Outcomes, Reliability, Usability, Workflow Efficiency, Total Cost of
Ownership (TCO), and Brand Reputation.
•It's what the customer believes they are getting.
•The Engineering Challenge:
•Not to make thecheapestdevice, but the device with the highestValue-to-Cost ratio.
•Value > Costis what creates a successful product.
•Key Question:How can we design features that create significant value for the
customer without proportionally increasing our cost?
•Key Takeaway:Understanding the difference between cost and value is the
first step in designing a competitive medical device.
Cost
$$$$$

38. Introduction of Medical Instruments
•Knowing Your Enemy: Competitors and Cost Drivers
•"You cannot design in a vacuum. You must understand the competitive
landscape to position your product effectively. This involves a deep dive into
both your costs and your competitors' value propositions."
•Step 1: Analyze the Competition
•Identify 2-3 key competitors and their flagship products.
•Create a feature-value matrix:
Cost
$$$$$
Feature
Competitor A
(Basic)
Competitor B
(Premium)
Our Planned Design
Price $1,000 $1,500 ?
Dosing Accuracy ±5% ±3% ±3%
Drug Library No Yes Yes
EMR Connectivity No Yes (Wireless)Yes (Wired)
Battery Life 6 hours 8 hours ?

39. Introduction of Medical Instruments
•Knowing Your Enemy: Competitors and Cost Drivers
•Step 2: Understand Your Total Cost Structure
•Direct Costs:BOM, Labor, Assembly.
•Indirect Costs:R&D, Regulatory (FDA/IEC 60601), Marketing,
Overhead.
•Cost of Ownership for Customer:Service Contracts, Training,
Downtime.
•Design Insight:A more reliable device might have a higher BOM
cost but a lower Total Cost of Ownership for the hospital, which is a
powerful value argument.
•Identifying the Gap:
•Where can we add value that competitors miss?
•Where can we reduce cost without sacrificing critical value?
•Key Takeaway:A thorough competitive analysis reveals
opportunities to create a superior value proposition by
strategically managing cost drivers.
Cost
$$$$$

40. Introduction of Medical Instruments
Case Study: Justifying a Price with a
Value Calculation
"Let's put it all together. We're designing an infusion
pump.
•The Scenario:
1.Our design has a BOM cost of$700.
2.We include a drug library andwiredEMR
connectivity—a key differentiator from
Competitor A.
3.Competitor A (no connectivity) is priced
at$1,000.
4.Competitor B (wireless connectivity) is priced
at$1,500.
•The Value Calculation: How do we justify our
price?
•Value Proposition:Our wired connectivity
automates charting, saving nurse time.
•Numerical Evidence:
•Time saved per patient:5 minutesof manual
documentation per infusion.
•Nurse fully-loaded hourly rate:$45/hour(includes
salary, benefits, etc.).
•Cost savings per infusion: (5 min / 60 min) * $45
=$3.75 per infusion.
•Annual Savings for a Hospital:
•Assume a hospital performs50 infusions per
day(300 days/year).
•Annual Time Savings:50 infusions/day *
$3.75/infusion * 300 days =$56,250.
•Setting Our Price:
•Our target price:$1,200.
•For a hospital, the additional$200over Competitor
A is justified by the$56,250in annual savings.
•Return on Investment (ROI):The price premium
pays for itself in a matter of days.
•Compared to Competitor B, we offer similar
connectivity value at a$300discount, making our
product the cost-effective choice.
•Design Implication:We designed a wired
connectivity solution (lower BOM cost than
wireless) that delivers immense operational
value. This cost-value analysis directly justifies
our market position and price point.
•Key Takeaway:By quantifying value in terms of
customer savings, engineering decisions
directly translate into competitive advantage
and business success.
Cost
$$$$$