Medical Instrumentation and Signal Filtering

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Vocabulary flashcards covering signal filtering, sensor characteristics, noise cancellation techniques, and medical measurement fundamentals.

Last updated 4:09 AM on 10/1/26
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24 Terms

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Inherent Sensitivity

A sensor design approach where the sensor is physically constructed to accept only the target signal and naturally reject energies originating from other directions or sources.

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Negative Feedback Loop

A configuration where a portion of the output (yy) is fed back through a transfer function (HfH_f) and subtracted from the input (xdx_d) to eliminate the influence of sensor transfer function (GdG_d) fluctuations.

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Fourier Analysis

A mathematical technique demonstrating that any periodic signal can be decomposed into a sum of sinusoidal functions, each defined by specific frequency, amplitude, and phase shift.

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First Harmonic

The fundamental sinusoidal component of a signal that shares the exact same period as the original periodic signal.

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Filter Gain

The ratio of the output signal amplitude to the input signal amplitude (yx\frac{y}{x}), expressed as a function of frequency.

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White Noise

A noise construct in which every constituent frequency across the spectrum carries identical amplitude or energy.

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Notch Filter

A filter designed to reject or attenuate a single specific frequency or very narrow band, commonly used to eliminate power line interference at 60 Hz60\,Hz or 50 Hz50\,Hz.

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Blood Pressure Signal Frequency Spectrum

The physiological frequency domain of real-time blood pressure signals, which typically ranges from 0 Hz0\,Hz to 20 Hz20\,Hz.

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ECG Signal Frequency Spectrum

The frequency domain range required for clinical electrocardiogram monitoring, spanning from 0 Hz0\,Hz to 100 Hz100\,Hz.

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Low-Pass Filter

A filter that preserves low-frequency components with a gain near 11 while attenuating higher-frequency signals.

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Cutoff Frequency

The frequency threshold where a filter's amplitude gain decreases by −3 dB-3\,dB (approximately a factor of 0.70.7 of the input amplitude).

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High-Pass Filter

A filter that attenuates low-frequency components while allowing frequencies above the cutoff frequency to pass.

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Band-Pass Filter

A filter combination created by placing a low-pass and a high-pass filter in series to preserve frequencies within a specified band and reject those outside.

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Band-Stop Filter

A filter configuration that allows frequencies outside a specified range to pass while suppressing frequencies within that target band.

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Opposing Inputs

A noise elimination strategy where ambient noise or motion artifacts are recorded, phase-flipped by 180∘180^\circ, and added back to the signal output to achieve cancellation.

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Observational Studies

Medical study designs conducted without a control group where researchers purely gather data from a specified population or cohort.

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Interventional Studies

Medical research designs that apply set interventions to experimental groups and measure outcomes relative to an untreated control group.

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Biosensors

Devices—either man-made instruments or systems employing living entities like bacteria—that directly interact with biological structures.

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Engineering Sensitivity

The quantitative parameter defining the amount of output produced per unit of applied input.

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Hysteresis

A non-linear phenomenon where sensor output measurements trace different paths depending on whether input values are transitioning from low-to-high versus high-to-low.

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Static Characteristic

The performance parameters of a zero-order sensor evaluated under steady-state inputs where time-dependent dynamic variations are neglected.

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Limit of Detection

The smallest input increment above zero required to yield a detectable change in sensor output.

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Dynamic Characteristic

The performance behavior of a measurement instrument when responding to time-varying input signals, described by metrics such as frequency response and signal-to-noise ratio.

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Signal-to-Noise Ratio (SNRSNR)

A dynamic signal quality metric calculated on a logarithmic scale using the formula 20log⁡10(amplitude of signalamplitude of noise)20 \log_{10}\left(\frac{\text{amplitude of signal}}{\text{amplitude of noise}}\right).