Biomedical Engineering (BME) 3 Practice Test

The practical implication is that you must sample biomedical signals at least twice the highest frequency content you care about, and you should filter before sampling to prevent aliasing. This comes from the Nyquist principle: to faithfully reconstruct a signal from its samples, the sampling rate must be at least two times the signal’s bandwidth. If you sample slower than that, higher-frequency components fold into lower frequencies, distorting the signal and potentially creating artifacts. In practice, you place an anti-aliasing (low-pass) filter before the analog-to-digital converter to remove frequency content above half the chosen sampling rate. Then you pick a sampling rate that is at least twice the signal’s bandwidth. For biomedical signals, that means identifying the relevant frequency range—for example, ECG up to about 100 Hz, EEG up to around 100 Hz (depending on application), and EMG that can extend into the kHz range—and selecting a sampling rate accordingly (commonly several hundred hertz to a few kilohertz for safety and fidelity). Why the other ideas don’t fit: sampling at a rate tied only to the highest frequency or using interpolation after cannot guarantee faithful reconstruction if high-frequency content is present or not captured; sampling much slower (or relying on post hoc smoothing) leads to aliasing and loss of information.