Biomedical engineering cheat sheet
Biological measurements, signals and device evaluation.
Biological systems
A biomedical model links physical or computational variables with a biological question. State what the model leaves out.
A simplified flow model does not represent every feature of circulation.
Measurement chain
A sensor, conditioning stage and recording system each influence the measured signal.
Noise can enter at more than one stage.
Sampling
Sampling converts a changing signal into discrete measurements. Sampling rate and signal bandwidth affect interpretation.
For an ideal band-limited signal, the sampling rate must exceed twice its highest frequency.
Evaluation
Evaluate measurement accuracy, repeatability, uncertainty and suitability for the intended use as distinct questions.
A repeatable measurement can still have systematic bias.
Accuracy, precision and calibration
Accuracy concerns closeness to a reference; precision concerns repeatability. Calibration relates an instrument’s output to known reference inputs under specified conditions.
Repeated readings can agree closely while sharing the same systematic offset.
Signal and noise
A measurement contains the desired signal plus unwanted contributions. Filtering can reduce some noise but can also remove or distort useful information.
Specify which frequency components matter before choosing a filter.
Sampling and aliasing
A sampled signal can misrepresent frequencies above the supported range. The Nyquist condition concerns a band-limited signal and requires an appropriate analogue anti-aliasing strategy.
To represent a 40 Hz band-limited signal, the sampling rate must exceed 80 samples/s under the ideal sampling model.
Biocompatibility and context
A material’s interaction with the body depends on contact type, duration and the device’s intended use. A successful bench test alone does not establish clinical safety or effectiveness.
Evaluate a device as a complete system, including users and the intended environment.
Worked example: sampling interval
A recorder samples at 200 samples/s. The interval between samples is 1/200 s = 0.005 s, or 5 ms. This does not by itself establish the sensor’s bandwidth.
Sample rate and measurement accuracy describe different properties.
Common mistake: correlation validates a device
A high correlation can coexist with systematic bias. Agreement, calibration range, uncertainty and performance on the intended population also need evaluation.
Plot differences against a reference rather than reporting correlation alone.
Check your understanding
Can a sensor be precise but inaccurate?
Yes. Its repeated readings may be close to one another while all are offset from the reference.
Curriculum connections
Australia
Design and Technologies / Physics foundations
sensors and measurement · signal sampling · validation and uncertainty
Senior courses and assessment requirements are set by state and territory authorities.
ACARA · Technologies ACARA · Senior secondary subjectsJapan
工業科の基礎
sensors and measurement · signal sampling · validation and uncertainty
MEXT course connections include optional and specialist subjects; the cards are original revision notes.
MEXT · 工業United States
NGSS engineering design / physical-science foundations
sensors and measurement · signal sampling · validation and uncertainty
Courses vary by state and school. Common Core, NGSS, CSTA, ACTFL and AP are frameworks or pathways, not one federal curriculum.
NGSS · Engineering design NGSS · Physical science topicsUnited Kingdom
Engineering / Design and Technology — England
sensors and measurement · signal sampling · validation and uncertainty
England uses the GCSE/A level labels shown here. Scotland, Wales and Northern Ireland have their own curricula and qualifications.
DfE · GCSE subject content (England)