20-Bio-B6 Analytical Biochemistry · May 2015
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
Paper format: National Exams, May 2015 — 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.
Approach. Two independent, simultaneously-sampled acquisition channels (EEG spectral power, core temperature) feed a common windowing/averaging stage, whose paired time series are then combined by a correlation engine; noise rejection is designed into each analog front end before digitisation, plus artifact-rejection logic in software.
Ag/AgCl scalp electrodes (standard 10-20 placement over the region of interest, referenced to mastoid) feed a differential instrumentation amplifier with high common-mode rejection (>100 dB), gain ~1000-10,000×, a 0.5-32 Hz bandpass to match the stated EEG range, and a 60 Hz notch to reject mains pickup. An anti-alias low-pass filter precedes the ADC, which samples at 128 Hz — comfortably above the 64 Hz Nyquist rate for a 32 Hz signal, leaving margin for a realisable anti-alias filter roll-off.
The digitised EEG is broken into successive epochs and, for each epoch, a power spectral density estimate (Welch's averaged periodogram, or an FFT with a Hann window to control spectral leakage) is computed. The theta (4-7 Hz) and delta (1-3.5 Hz) band powers are summed from the PSD bins and expressed as a percentage of the total power in the full 0.5-32 Hz band. A 30-second epoch is a reasonable window: it is the standard length used for sleep-stage scoring, long enough to contain many cycles of even the slowest 1 Hz delta component (30 cycles) for a statistically stable spectral estimate, yet short enough to track how the sleep-stage-dependent spectrum evolves over the night. Over an 8-hour recording this yields 960 successive %power values per band.
A thermistor probe in the ear canal (chosen for its large, predictable resistance change over 35-40°C) forms one arm of a Wheatstone bridge; the bridge output is amplified by an instrumentation amplifier and digitised. Because core temperature varies slowly (thermal time constants of minutes), a low sample rate (e.g. 1 sample per second) is more than sufficient; the digitised readings are averaged over the same 30-second epochs used for the EEG channel so the two data streams are time-aligned sample-for-sample.
At the end of the recording (or continuously, as a running estimate), the microcontroller/host computer computes the Pearson correlation coefficient between the %power-in-band time series and the epoch-averaged temperature time series — giving the requested measure of linear dependence between EEG spectral content and core temperature across the sleep cycle. All raw epoch values (theta %, delta %, temperature, timestamp) are logged to onboard flash memory or streamed to a host PC/database for the full 8 hours; a real-time display shows scrolling trend plots of both band-power percentages and temperature on a common time axis, with the running correlation coefficient updated and displayed numerically.
EMG from scalp muscles is broadband and extends well above 32 Hz, so the 0.5-32 Hz analog bandpass already removes most of it; residual in-band EMG contamination is further suppressed by monitoring epoch RMS amplitude and flagging/discarding epochs whose amplitude exceeds a threshold (e.g. >100 µV, well above the stated 30 µV EEG level) as artifact-corrupted. Movement artifact produces large, low-frequency baseline shifts; the 0.5 Hz high-pass edge removes slow drift, and a small accelerometer mounted on the headband provides an independent movement channel that flags epochs coincident with a motion event for exclusion from the correlation calculation, rather than letting a contaminated epoch bias the result. Patient safety and comfort are addressed by using lightweight, flexible gel electrodes and a battery-powered, electrically isolated front-end amplifier (isolation is elaborated in Question 5) so no direct galvanic path exists between the sleeping subject and mains-powered recording equipment.
