20-Bio-B6 Analytical Biochemistry · December 2013
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
Paper format: National Exams, December 2013 — 04-Bio-B6 Bioinstrumentation. Three hours, open book, non-communicating calculator permitted. Six questions of equal value (25 marks each); four constitute a complete paper and only the first four appearing in the answer book are marked. All six are solved here as a complete study resource. Every question is a design/essay question (block-diagram instrumentation-system design, or descriptive explanation).
Reference texts (the books a candidate should have reviewed for this subject):
Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.
Myogenic (EMG) noise from scalp, jaw and neck muscles is broadband, roughly 20 Hz to several kHz, with amplitude that can reach the millivolt range — three to four orders of magnitude larger than the sub-µV BSAEP — and its spectrum overlaps directly with the 150-2500 Hz signal band, so it cannot be removed by filtering alone. Power-line interference at 60 Hz plus harmonics (120, 180, 240 Hz…) has amplitude that depends on shielding/grounding quality but can be tens to hundreds of µV uncontrolled; its 180 Hz (and higher) harmonics fall inside the 150-2500 Hz recording band. Stimulus/electromagnetic artifact from the earphone's own drive transient (electromagnetic radiation from the transducer coil, and any acoustic-to-electrode microphonic pickup) occurs synchronously with each click, is broadband, and can be comparable in amplitude to or larger than the genuine neural response in the first few milliseconds after the click.
An isolated, high-CMRR instrumentation amplifier (gain of roughly 2000-5000×, split across two stages to keep each stage's input-referred noise and offset manageable) is used first; because the raw electrode signal is dominated by the much larger background EEG (not the µV-scale BSAEP itself, which only emerges after averaging), the gain is chosen to use the ADC's dynamic range fully on the background EEG without clipping, not simply to maximise the tiny BSAEP amplitude. The electrode source impedance (5 kΩ) together with the 2 m lead's parasitic capacitance (typically ~100 pF/m, so ~200 pF total) forms an unintentional low-pass filter. A bandpass filter set to 150-2500 Hz (matching the stated signal spectrum) follows the amplifier, rejecting most of the (typically <100 Hz) background EEG energy and the low end of any EMG spectrum, before an anti-alias low-pass filter ahead of the ADC. The ADC samples at 10 kHz — comfortably above the 5 kHz Nyquist rate for the 2500 Hz upper band edge — giving 100 samples across the 10 ms response, ample time resolution to resolve the successive brain-stem waves (I-V) making up the BSAEP.
Because the BSAEP is time-locked (synchronous) to the click stimulus while the residual noise is not, coherent (synchronous) averaging across many stimulus repetitions is the standard technique: summing/averaging N stimulus-locked epochs reinforces the repeatable evoked response while the uncorrelated noise (including noise components that share the BSAEP's own frequency band, so ordinary filtering cannot separate them) averages toward zero, improving SNR by a factor of $\sqrt{N}$. In practice N is in the hundreds to low thousands of clicks. This is combined with amplitude-threshold artifact rejection — epochs contaminated by a large EMG burst are discarded before being included in the average, since a single large-amplitude epoch would otherwise disproportionately corrupt the averaged waveform.
