Every HRV parameter, in one place

HRV apps and software report dozens of numbers. Here they all are, grouped by family, each with what it measures, its unit, how long a recording it needs and a link to the full explanation.

To watch these numbers change on sample recordings, open the HRV workbench. To work them out from your own beat-to-beat data, use the HRV calculator. For terms that are not parameters, see the glossary.

Time domain

Statistics taken straight from the list of beat-to-beat intervals: averages, spreads and counts of big jumps. Most apps report one of these, usually RMSSD.

Mean RR, HR

Mean RR interval and mean heart rate

The average time between heartbeats in a recording, in milliseconds. Heart rate is the same number upside down: 60,000 divided by the mean RR.

Unit

ms (HR in bpm)

Mainly reflects

How fast the heart beats on average; every other number is read against it.

Recording

Any length Any recording; it is the average of whatever you record.

$\mathrm{RR}_{\mathrm{mean}} = \frac{1}{N}\sum_{i=1}^{N}\mathrm{RR}_i,\qquad \mathrm{HR} = \frac{60\,000}{\mathrm{RR}_{\mathrm{mean}}}$
RHR

Resting heart rate

How many times your heart beats per minute while you are fully at rest. For adults it is usually 60 to 100 beats per minute, and lower in well-trained athletes.

Unit

bpm

Mainly reflects

Heart rate at rest; fitness lowers it over months, and illness, poor sleep and stress raise it.

Recording

Any length A rested reading: some devices take it during sleep, some in a daytime check.

$\mathrm{HR} = \frac{60\,000}{\mathrm{RR}_{\mathrm{mean}}}$
RMSSD

Root mean square of successive differences

Root mean square of successive differences: an HRV metric built from how much each heartbeat interval differs from the next, in milliseconds. It mainly reflects vagal activity.

Unit

ms

Mainly reflects

Fast, breathing-linked changes from beat to beat, which mainly reflect vagal activity.

Recording

Under 5 min Holds up in short recordings: lying down, a 10-second stretch gave a valid value against 5 minutes.

$\mathrm{RMSSD} = \sqrt{\frac{1}{N-1}\sum_{i=1}^{N-1}\left(\mathrm{RR}_{i+1}-\mathrm{RR}_i\right)^2}$
lnRMSSD

Natural logarithm of RMSSD

The natural logarithm of RMSSD, with no unit. Taking the log evens out the spread of RMSSD values, which makes day-to-day changes easier to compare and analyse.

Unit

no unit (log of ms)

Mainly reflects

The same vagal activity as RMSSD, on a scale that makes day-to-day changes comparable.

Recording

Under 5 min As for RMSSD, which it is calculated from.

$\mathrm{lnRMSSD} = \ln\left(\mathrm{RMSSD}\right)$
SDSD

Standard deviation of successive differences

The standard deviation of the differences between neighbouring NN intervals, in milliseconds. It is almost the same number as RMSSD and measures the same fast, beat-to-beat change.

Unit

ms

Mainly reflects

The same fast beat-to-beat change as RMSSD; at rest the two are almost the same number.

Recording

Under 5 min As for RMSSD, since the two nearly coincide.

$\mathrm{SDSD} = \sqrt{\frac{1}{N-2}\sum_{i=1}^{N-1}\left(\Delta_i-\Delta_{\mathrm{mean}}\right)^2},\quad \Delta_i = \mathrm{RR}_{i+1}-\mathrm{RR}_i$
SDNN

Standard deviation of NN intervals

The standard deviation of all NN intervals in a recording, in milliseconds. It measures overall variability, and its value depends strongly on how long the recording lasts.

Unit

ms

Mainly reflects

Overall variability at every speed, from breathing swings to slow drifts.

Recording

5 min Usually 5 minutes or 24 hours; it grows with length, so compare equal lengths only.

$\mathrm{SDNN} = \sqrt{\frac{1}{N-1}\sum_{i=1}^{N}\left(\mathrm{RR}_i-\mathrm{RR}_{\mathrm{mean}}\right)^2}$
NN50

Count of successive differences over 50 ms

The number of pairs of neighbouring NN intervals that differ by more than 50 milliseconds. Dividing it by the number of intervals gives pNN50.

Unit

count

Mainly reflects

How often the gap between beats jumps by more than 50 ms, a vagally driven change.

Recording

Under 5 min 2 minutes is the shortest conventional epoch; counts from different lengths do not compare.

$\mathrm{NN50} = \#\left\{\,i : \left|\mathrm{RR}_{i+1}-\mathrm{RR}_i\right| > 50\ \mathrm{ms}\right\}$
pNN50

Percentage of successive differences over 50 ms

The percentage of neighbouring NN intervals that differ by more than 50 milliseconds. It tracks fast, vagally driven changes, like RMSSD, but as a share rather than a size.

Unit

%

Mainly reflects

The same fast, vagally driven change as RMSSD, as a share, not a size; it depends strongly on heart rate.

Recording

Under 5 min As for NN50, which it divides by the number of intervals.

$\mathrm{pNN50} = \frac{\mathrm{NN50}}{N-1}\times 100$
pNN20

Percentage of successive differences over 20 ms

The percentage of neighbouring NN intervals that differ by more than 20 milliseconds. A lower-threshold cousin of pNN50 that still moves in people whose beat-to-beat changes are small.

Unit

%

Mainly reflects

Smaller fast changes, for hearts that rarely jump 50 ms in one beat.

Recording

Under 5 min As for pNN50; the threshold is the only difference.

$\mathrm{pNN20} = \frac{\#\left\{\,i : \left|\mathrm{RR}_{i+1}-\mathrm{RR}_i\right| > 20\ \mathrm{ms}\right\}}{N-1}\times 100$
SDANN

Standard deviation of the 5-minute average NN intervals

The standard deviation of the mean NN interval of each 5-minute segment of a 24-hour recording, in milliseconds. It measures the slow changes over a day and ignores everything faster.

Unit

ms

Mainly reflects

Slow changes in heart rate across the day, with the fast swings averaged out.

Recording

24 h Meant for 24-hour recordings, cut into 5-minute segments.

$\mathrm{SDANN} = \sqrt{\frac{1}{K-1}\sum_{k=1}^{K}\left(\mathrm{RR}_{\mathrm{mean},k}-\mathrm{RR}_{\mathrm{mean}}\right)^2}$
SDNNI

SDNN index

The mean of the SDNN of each 5-minute segment of a 24-hour recording, in milliseconds. It keeps the variability inside each segment and drops the slow drift between them.

Unit

ms

Mainly reflects

Variability within each few minutes, averaged over the day; it correlates with VLF power.

Recording

24 h A 24-hour recording, cut into 5-minute segments.

$\mathrm{SDNNI} = \frac{1}{K}\sum_{k=1}^{K}\mathrm{SDNN}_k$

Geometric

Measures read from the shape of the histogram of intervals. The triangular index and TINN were built for 24-hour Holter recordings.

HTI

HRV triangular index

The number of NN intervals in a recording divided by the height of the tallest bar of their histogram. A unitless geometric measure of overall variability that a few bad beats barely move.

Unit

ratio

Mainly reflects

Overall variability, like SDNN, in a form that a few bad beats barely move.

Recording

24 h At least 20 minutes, ideally 24 hours; 5 minutes is the usual short epoch, 2 a proposed minimum.

$\mathrm{HTI} = \frac{N}{\max_k\, n_k}$
TINN

Triangular interpolation of the NN interval histogram

The width, in milliseconds, of the base of the triangle that best fits the histogram of NN intervals. A geometric measure of overall variability from 24-hour Holter analysis.

Unit

ms

Mainly reflects

Overall variability, as the width of the interval histogram.

Recording

24 h Intended for 20 minutes to 24 hours; a day makes a much wider histogram than 5 minutes.

$\mathrm{TINN} = N_t - M_t,\quad (M_t, N_t) = \arg\min_{M,N}\sum_k \left(n_k - T_{M,N}(k)\right)^2$
SI

Baevsky stress index

A number built from the histogram of heartbeat intervals, with no unit. It rises as the rhythm gets steadier and less variable, which Baevsky read as strain on the body's regulation.

Unit

ratio

Mainly reflects

How steady and narrow the rhythm is; it rises as variability falls. It comes from Soviet space medicine.

Recording

5 min 5 minutes in recent studies; a longer recording catches slow drifts that widen the range.

$\mathrm{SI} = \frac{\mathrm{AMo}}{2\,\mathrm{Mo}\,\mathrm{MxDMn}}$

Frequency domain

The interval series split into rhythms of different speeds, like a sound split into notes. Each band holds the variation that repeats at its own pace.

ULF

Ultra-low-frequency power

The variance of the heartbeat intervals below 0.003 Hz, in ms²: rhythms slower than one cycle every 5 minutes, including the day-night cycle. It can only be measured from a 24-hour recording.

Unit

ms²

Mainly reflects

The slowest rhythms, under one cycle every 5 minutes, including the day-night cycle.

Recording

24 h Only from a 24-hour recording.

$\mathrm{ULF} = \int_{0}^{0.003} P(f)\,\mathrm{d}f$
VLF

Very-low-frequency power

The variance of the heartbeat intervals in the 0.003 to 0.04 Hz band, in ms²: rhythms repeating every 25 seconds to 5 minutes. It needs at least a 5-minute recording and is best read over 24 hours.

Unit

ms²

Mainly reflects

Rhythms repeating every 25 seconds to 5 minutes; their meaning in short recordings is doubtful.

Recording

24 h At least 5 minutes, and best read over 24 hours.

$\mathrm{VLF} = \int_{0.003}^{0.04} P(f)\,\mathrm{d}f$
LF

Low-frequency power

The variance of the heartbeat intervals that falls in the 0.04 to 0.15 Hz band, in ms²: rhythms repeating every 7 to 25 seconds. Once read as sympathetic activity, which is now disputed.

Unit

ms²

Mainly reflects

At rest, mostly blood-pressure waves near 0.1 Hz; it is not a clean sympathetic measure.

Recording

5 min About 2 minutes at least; 5 minutes is the standard short recording.

$\mathrm{LF} = \int_{0.04}^{0.15} P(f)\,\mathrm{d}f$
HF

High-frequency power

The variance of the heartbeat intervals that falls in the 0.15 to 0.40 Hz band, in ms²: the range of normal breathing. It mainly reflects vagal activity when breathing is 9 to 24 breaths a minute.

Unit

ms²

Mainly reflects

The breathing rhythm, and vagal activity when breathing is 9 to 24 breaths a minute.

Recording

Under 5 min About 1 minute at least; 5 minutes is the standard short recording.

$\mathrm{HF} = \int_{0.15}^{0.40} P(f)\,\mathrm{d}f$
TP

Total power

The sum of the power in every band of the spectrum, in ms²: the variance of the heartbeat intervals. For a 5-minute recording it is VLF + LF + HF; over 24 hours ULF is added.

Unit

ms²

Mainly reflects

All the variance in the intervals: the frequency-domain twin of SDNN.

Recording

5 min 5 minutes or 24 hours; like SDNN it depends on the length.

$\mathrm{TP} = \mathrm{ULF} + \mathrm{VLF} + \mathrm{LF} + \mathrm{HF} = \int_{0}^{0.40} P(f)\,\mathrm{d}f$
LF/HF

LF/HF ratio

LF power divided by HF power, with no unit. It was proposed as a gauge of balance between the sympathetic and parasympathetic systems, but research shows it cannot measure that reliably.

Unit

ratio

Mainly reflects

LF against HF; breathing moves it a lot, and it is not a reliable measure of “sympathovagal balance”.

Recording

5 min 5 minutes, the length its reference values come from.

$\frac{\mathrm{LF}}{\mathrm{HF}} = \frac{\int_{0.04}^{0.15} P(f)\,\mathrm{d}f}{\int_{0.15}^{0.40} P(f)\,\mathrm{d}f}$
LF nu, HF nu

Normalised units

LF or HF power as a percentage of their sum (LF + HF), rather than in ms². The two always add up to 100, so they carry one piece of information between them.

Unit

nu

Mainly reflects

The split between LF and HF with their total size removed; they always add up to 100.

Recording

5 min 5 minutes, as for LF and HF.

$\mathrm{LF}_{\mathrm{nu}} = \frac{\mathrm{LF}}{\mathrm{LF}+\mathrm{HF}}\times 100,\qquad \mathrm{HF}_{\mathrm{nu}} = \frac{\mathrm{HF}}{\mathrm{LF}+\mathrm{HF}}\times 100$
LF peak, HF peak

Peak frequency

The frequency, in Hz, at which a band of the HRV spectrum has its highest power. The HF peak is usually the breathing rate; the LF peak is usually near 0.1 Hz.

Unit

Hz

Mainly reflects

Which rhythm dominates a band; the HF peak is usually the breathing rate.

Recording

5 min 5 minutes, as for the spectrum it is read from.

$f_{\mathrm{peak}} = \arg\max_{f \in \text{band}} P(f)$
Coherence

A HeartMath score for how much of the HRV spectrum sits in one narrow peak between 0.04 and 0.26 Hz. Slow breathing at about 6 a minute produces it, so it largely measures breathing pace.

Unit

ratio

Mainly reflects

How much of the spectrum sits in one narrow peak; it largely measures breathing pace.

Recording

5 min Read from a short-term spectrum, as for LF and HF; HeartMath’s apps report it.

$\mathrm{Coherence} = \frac{P_{\mathrm{peak}}}{P_{\mathrm{total}} - P_{\mathrm{peak}}},\quad P_{\mathrm{peak}} = \int_{f_0 - 0.015}^{f_0 + 0.015} P(f)\,\mathrm{d}f$

Nonlinear

Measures of pattern rather than size: how predictable the beat series is, and how its wobble scales from a few beats to many.

DFA α1, α2

Detrended fluctuation analysis exponents

The short-term scaling exponent of detrended fluctuation analysis. Near 1 the beats have memory at every scale; near 0.5 they behave like noise. α2 is the same slope over longer stretches.

Unit

exponent

Mainly reflects

How correlated the beats are over short (α1) and longer (α2) stretches; α1 is used to estimate exercise intensity thresholds.

Recording

Under 5 min 120 seconds is a proposed minimum for α1; the method was designed for hours.

$F(n) \propto n^{\alpha},\qquad \alpha_1 = \frac{\mathrm{d}\log F(n)}{\mathrm{d}\log n}\ \text{for}\ 4 \le n \le 16$
SampEn

Sample entropy

How unpredictable the heartbeat series is: minus the log of the chance that runs of beats that match also match one beat longer. Near 0 is a repeating pattern; 2 or more is close to random.

Unit

nats

Mainly reflects

How unpredictable the beat series is: near 0 is a repeating pattern, 2 or more near random.

Recording

Under 5 min Can be computed from under 200 beats, but the value depends on the length and on the settings m and r.

$\mathrm{SampEn}(m, r) = -\ln\frac{A}{B}$
ApEn

Approximate entropy

The older cousin of sample entropy, with no unit: a regularity measure that counts each run of beats as matching itself, which biases it towards low values on short recordings.

Unit

nats

Mainly reflects

Regularity of the beat series, biased towards low values on short recordings.

Recording

5 min Proposed for about a thousand points; it reads lower on shorter records and depends on the settings m and r.

$\mathrm{ApEn}(m, r) = \Phi^{m}(r) - \Phi^{m+1}(r)$

Poincaré plot

Each interval plotted against the next makes a cloud of dots. Its width and length give two numbers that echo RMSSD and SDNN.

SD1, SD2, SD1/SD2

Poincaré plot standard deviations

Two measures of the spread of dots in a Poincaré plot, in milliseconds. SD1 is the width and tracks short-term variability, like RMSSD; SD2 is the length and tracks overall variability.

Unit

ms

Mainly reflects

SD1 short-term variability, like RMSSD; SD2 overall variability, like SDNN; and their ratio.

Recording

5 min SD1 behaves like RMSSD; SD2 grows with recording length, as SDNN does.

$\mathrm{SD1} = \frac{\mathrm{RMSSD}}{\sqrt{2}},\qquad \mathrm{SD2} = \sqrt{2\,\mathrm{SDNN}^2-\mathrm{SD1}^2}$

Heart rate dynamics and clinical indices

Measures of how the heart responds around particular beats, rather than of overall spread. Both were developed on 24-hour ECG recordings in cardiology research.

TO, TS

Heart rate turbulence

The brief speed-up and slower recovery of the heart rhythm after a premature ventricular beat, measured from a 24-hour ECG as two numbers: turbulence onset (%) and turbulence slope (ms per beat).

Unit

% and ms/beat

Mainly reflects

How the rhythm speeds up and settles after a premature ventricular beat, through the baroreflex.

Recording

24 h A clean 24-hour ECG with real premature ventricular beats.

$\mathrm{TO} = \frac{(\mathrm{RR}_{+1}+\mathrm{RR}_{+2})-(\mathrm{RR}_{-2}+\mathrm{RR}_{-1})}{\mathrm{RR}_{-2}+\mathrm{RR}_{-1}}\times 100$
DC

Deceleration capacity

The average size of the heart's slow-downs, in milliseconds, found by averaging the pattern around every beat slower than the one before. A 24-hour vagal measure used after heart attacks.

Unit

ms

Mainly reflects

The average size of the heart’s slow-downs, a measure of vagal activity.

Recording

24 h Developed on 24-hour Holter ECGs; a 5-minute value has also been studied.

$\mathrm{DC} = \frac{X(0)+X(1)-X(-1)-X(-2)}{4}$

Not parameters themselves, but you will need them to read the numbers above. The glossary has the rest.

RR interval
The time from one heartbeat to the next, measured in milliseconds between the R peaks of an ECG. HRV is calculated from a series of these intervals.
NN interval
An RR interval between two normal heartbeats, in milliseconds, after extra beats and measurement errors are removed. Most HRV metrics are calculated from NN intervals.
Tachogram
A line chart of heartbeat intervals in the order they happened, one point per beat, in milliseconds. It shows HRV as a wavy line instead of a single number.
Poincaré plot
A scatter plot of each heartbeat interval against the one after it, in milliseconds on both axes. The shape of the cloud of dots shows short-term and overall variability at a glance.
Artifact
An error in a heartbeat recording, such as a missed, extra or mistimed beat, often caused by movement or poor sensor contact. Artifacts can badly distort HRV numbers.
Ectopic beat
A heartbeat that starts outside the heart's normal pacemaker and usually comes early. Ectopic beats are common, but they distort HRV unless removed or corrected.
Stationarity
The assumption that the rhythms in a recording stay the same from start to finish. Frequency measures such as LF and HF need it; a recording that changes partway through breaks it.
Breathing rate
How many breaths you take a minute. It moves HRV on its own: slower, deeper breathing makes the beat-to-beat swing larger, and below about 9 breaths a minute it shifts from the HF band into LF.
Vagal tone
The ongoing influence of the vagus nerve on the heart, which slows it down. It is usually estimated from HRV measures such as RMSSD and HF power.
Baseline
Your own usual HRV level and range, built from weeks of readings taken the same way. Comparing a reading with your baseline says more than comparing it with other people.

Recording lengths follow the sources cited on each glossary page, where you will find the details. These pages explain what the numbers mean; they do not diagnose anything.