What are HRV Frequency Measurements (LF, HF, LF/HF)

Heart Rate Variability (HRV) is a term that describes many metrics and analysis techniques, including Time Domain, Frequency Domain, and Non-Linear Analysis.

Frequency Domain Analysis is a complex analysis technique that shows how much of a signal lies within one or more frequency bands (ranges). With regards to Heart Rate Variability, research has identified certain frequency bands that tend to correlate with certain physiological phenomena, such as Parasympathetic nervous system activity. We use the FFT-based Welch's Periodogram method to transform the time series data into frequency data.

(Scroll to the bottom to understand the difference between units of measurement)

Common Frequency Domain HRV metrics include:

  • High-Frequency power (HF): frequency activity in the 0.15 - 0.40Hz range (green in the above chart)
  • Low-Frequency power (LF): frequency activity in the 0.04 - 0.15Hz range (yellow in the above chart)
  • LF/HF Ratio: A ratio of Low Frequency to High Frequency. Some consider this indicative of Sympathetic to Parasympathetic Autonomic Balance, but that is controversial. Please see this article and this article for more information.

Note that obtaining accurate lower frequency measurements requires longer reading times (minimum 4 minutes or more).

You may also have seen frequency values in Hertz (Hz) or milliseconds (ms) or milliseconds squared (ms 2).

Hertz (Hz) refers to the frequency band or the location on the frequency band. For example, there may be frequency activity at 0.4 Hz - or whichever band is the "peak" of the spectrum. This tells you where in the frequency spectrum you are referring to.

The actual activity in that band is typically expressed in terms of "power", which uses the units milliseconds squared (ms 2) for a particular Hertz (Hz) band. Think of it as "area under the curve".

For example, you might have 590 ms 2 of power in the 0.4hz frequency band (hypothetical example). The research studies that list 2 Hz of frequency activity are just saying that's where the "peak" frequency occurred in the spectrum.

An analogy: If your HRV is analogous to a song played with many instruments, the frequency domain breaks down the song into what each instrument plays on its own. The high frequency could be the guitar and vocals, the low frequency could be the bass and drums. The "power" could be how often and loud each instrument is playing.

When you take an HRV reading with our app, the frequency numbers you see are the average frequency power measured throughout the reading. 

Regarding use of these measurements: HF, LF and other frequency parameters are much more complex to calculate than the Time Domain and even some of the Non-Linear HRV indices. There are many ways to convert a time series of values into frequency values, and Frequency Domain is also much more sensitive to artifact handling. That is one reason why the Frequency Domain can be so controversial in the research and hard to compare between studies and between platforms and devices -- small changes in setup/artifact handling/calculations can create larger differences in the final results in the Frequency Domain.

What about Ultra Low/Very Low-Frequency measurements?: while we have the ability to add these calculations to the app, 99%+ of our readings are under 5 minutes, so at this time it is not a priority to add in VLF/ULF. Aside from the actual calculations, longer duration readings have different artifact detection/correction requirements, due to processing power. We will likely address all of these in the future.

Using Frequency Domain for HRV Analysis

Reading duration should be a minimum of 4 minutes to be accurate. 4 mins is for confidence in Low Frequency (LF) values. High frequency (HF) can reliably be measured in 60 seconds. You can start to measure LF in as little as 2 minutes, but research says 4 minutes+ is best for LF.

While analyzing Frequency Domain metrics is a bit more advanced, in general, you will look for:

- Higher Total Power

- Higher HF values

- A higher LF/HF ratio

Keep in mind this is a very basic explanation and we are endeavoring to add more education into the app for our users! 

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