Quasi-DC: What it is, Its Significance, and How to Measure It.

In electrical engineering, quasi-DC refers to a signal or voltage/current that behaves mostly like DC (direct current) but has small, slow fluctuations or low-frequency components riding on top.

It’s called “quasi” (meaning almost) because:
1. It has a DC-like average or baseline.
2. It’s not perfectly constant. There may be ripples, drift, or slow variations.
3. It typically covers signals with very low frequency (much less than the main AC frequencies), sometimes down to millihertz (mHz) or microhertz (µHz).

Examples:

  • DC power supplies with ripple.

  • Slowly drifting sensor outputs.

  • Low-frequency components in biomedical signals (like EEG or ECG baseline drift).

  • Ground loops are causing slow voltage fluctuations.


Why is Quasi-DC Significant?

Quasi DC matters because many systems assume DC signals are perfectly stable, but in reality, small low-frequency fluctuations can:

  1. Affect sensitive measurements (e.g., sensor bias, instrumentation drift).

  2. Cause control system instability (especially if the system integrates errors over time).

  3. Interfere with precision circuits (like ADCs or amplifiers that expect clean DC bias).

  4. Contribute to EMI/EMC issues if these slow fluctuations couple into other system parts.

In power systems, quasi-DC currents on AC grids (for example, from geomagnetic disturbances or HVDC grounding issues) can overheat transformers or cause saturation, so detecting and managing them is critical.


How Do You Test for Quasi-DC?

Testing for quasi-DC depends on the system and the context, but typical approaches include:

Using a low-frequency spectrum analyzer or an FFT tool

  • Look at the frequency content down to millihertz or below.

  • Instruments like lock-in amplifiers or dynamic signal analyzers can help.

High-precision multimeters or nanovoltmeters

  • Measure very small, slow DC drifts or offsets over time.

Oscilloscopes with a long timebase

  • Set long time/div and look for slow baseline movement.

  • Some scopes allow you to apply digital filtering to isolate low-frequency components.

Data logging over extended periods

  • Use precision DAQ systems to log DC voltage/current over hours or days, then analyze drift or ripple.

Specialized quasi-DC meters (for power systems)

  • Dedicated quasi-DC measurement equipment in grid engineering monitors DC bias on AC lines.

When dealing with sensitive medical devices, quasi-DC is especially important because even tiny low-frequency fluctuations can:

Affect sensor baselines (e.g., ECG, EEG, EMG, drifting signals)
Interfere with amplifiers or ADCs expecting clean DC references
Introduce artifacts in patient monitoring that may look like physiological events but are just electronic drift
Compromise safety or regulatory compliance, especially under FDA or IEC 60601 standards


How to Test Quasi-DC in Medical Devices

For medical electronics, here’s how you typically approach it:

  1. Use High-Precision Multimeters or Nanovoltmeters

  • Measure DC voltages or currents at nanovolt or microvolt levels.

  • Suitable for checking slow drift on sensor outputs or bias circuits.

Recommended tools:

  • Keithley 2182A nanovoltmeter

  • Keysight 34465A/34470A high-precision DMMs

2. Use a Long-Timebase Oscilloscope or Data Acquisition System

  • Record signals over minutes to hours to observe drift or low-frequency fluctuations.

  • Medical-grade DAQ systems (like NI PXI, BioPac, or ADInstruments) are often used.

3. Apply Low-Frequency Spectrum Analysis

  • Use an FFT tool or a dynamic signal analyzer to separate low-frequency components from the rest of the signal.

  • Helps isolate quasi-DC from random noise or higher-frequency interference

4. Check Against EMC and Regulatory Tests

  • Medical devices must comply with standards like IEC 60601-1-2 for EMC; some EMC labs specifically check for quasi-DC currents/voltages affecting device function.

  • Pre-compliance testing at an EMC lab can reveal quasi-DC coupling paths.

5. Implement Drift and Offset Monitoring

  • Implement software baseline correction for devices like ECG or EEG to remove quasi-DC artifacts.

  • But remember, finding and fixing the hardware source is better if possible.