SDNN index

The SDNN index is the average of the SDNN SDNN SDNN 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. More about SDNN values of all the 5-minute segments in a long recording, in milliseconds.

Why this measure exists

It is the other half of the split the 1996 Task Force made in 24-hour SDNN. SDANN SDANN SDANN 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. More about SDANN keeps the slow drift between 5-minute pieces; the SDNN index keeps what happens inside them. Each piece gets its own standard deviation, so a slow change from morning to night never enters, and the average over the day tells you how much the heart was varying over a few minutes at a time. Shaffer and Ginsberg describe it as reflecting autonomic influence on HRV and note that it correlates with VLF power VLF power VLF 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. More about VLF power over 24 hours.

The formula

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

Cut the recording into $K$ pieces of 5 minutes, work out the SDNN of each piece, and average those $K$ values. A full day gives $K = 288$.

Worked example

SDNN index step by step

Ten beats, every number shown

The ten intervals, in ms (300 to 2000)

Beat 1 Beat 2 Beat 3 Beat 4 Beat 5 Beat 6 Beat 7 Beat 8 Beat 9 Beat 10

SDNN index of these 10 intervals is 29.9 ms.

Step 4 of 4

Back Start at step 1

1. Step 1 of 4 Start with the intervals

   Beat 1	880 ms
   Beat 2	826 ms
   Beat 3	812 ms
   Beat 4	823 ms
   Beat 5	848 ms
   Beat 6	877 ms
   Beat 7	880 ms
   Beat 8	866 ms
   Beat 9	828 ms
   Beat 10	815 ms

   10 intervals between 11 beats, in milliseconds.

2. Step 2 of 4 Cut the recording into pieces of 2.5 seconds

   Piece 1	880, 826, 812 ms
   Piece 2	823, 848, 877 ms
   Piece 3	880, 866, 828 ms

   A day is cut into 5-minute pieces (288 of them). Ten beats are cut into 2.5-second pieces here to show the same steps; the last, incomplete piece is dropped.

3. Step 3 of 4 Work out the SDNN of each piece

   Piece 1	35.9 ms
   Piece 2	27.0 ms
   Piece 3	26.9 ms

   Each piece gets its own standard deviation, so the slow change between pieces never enters.

4. Step 4 of 4 Average them

   35.9 + 27.0 + 26.9 ÷ 3	29.9 ms

   SDNN index 29.9 ms

With JavaScript on, the steps show one at a time and the beats can be changed.

A row of ten editable heartbeat intervals in milliseconds, then the calculation of SDNN index as numbered steps: start with the intervals; cut the recording into pieces of 2.5 seconds; work out the sdnn of each piece; average them. The final step reads SDNN index 29.9 ms. Back and Next buttons move between the steps.

Ten beats cannot be cut into 5-minute pieces, so the example cuts them into 2.5-second pieces of three beats and runs the same steps: an SDNN for each piece, then their mean, 29.9 ms. Compare it with the whole-recording SDNN of the same beats on the SDNN page: the index is larger here only because three-beat pieces are a toy; over a real day the index is smaller than the 24-hour SDNN, because the slow drift has been removed.

What moves it

Breathing, vagal activity vagal activity 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. More about Vagal tone and the ~0.1 Hz blood-pressure wave inside each 5-minute window, averaged over the day.

When it misleads

It needs a long recording; from 5 minutes it is just SDNN. Artifacts Artifacts 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. More about Artifact in a few segments raise the average, and a segment-based average hides which part of the day changed. Like every SDNN relative it is in milliseconds, but it is not SDNN and cannot be compared with a 5-minute or 24-hour SDNN value.

Where you will see it

The Task Force’s name is SDNN index. Kubios HRV prints it as SDNNI for recordings that hold several 5-minute segments. Wearables do not show it.