SDNN

SDNN, or standard deviation of normal-to-normal (NN) intervals, is a time-domain measure used in heart rate variability (HRV) analysis. It represents the variability in the intervals between consecutive normal heartbeats during a recording, computed as the standard deviation of NN intervals. NN intervals are derived from ECG by identifying R peaks and measuring the time between successive normal beats; artifacts and ectopic beats are typically removed before calculation to avoid skewing results.

Calculation and recording length: SDNN can be computed from short (usually 5 minutes) or long recordings, with 24-hour Holter monitoring being common for assessing overall autonomic function. In long recordings, SDNN reflects total variability driven by both branches of the autonomic nervous system and by circadian and activity-related factors. In very short recordings, SDNN values are less stable and more influenced by transient factors.

Interpretation and use: Higher SDNN indicates greater overall HRV and greater autonomic adaptability, whereas lower SDNN is associated with reduced variability and may be linked to aging, cardiovascular risk, stress, or disease. However, because SDNN aggregates multiple influences, it does not distinguish sympathetic from parasympathetic contributions and should be interpreted alongside other HRV measures such as RMSSD, pNN50, and SDANN.

Guidelines and caveats: SDNN calculation follows standard methods described in HRV guidelines, and values depend on recording length, data quality, and population characteristics. Proper preprocessing to remove artifacts and non-sinus beats is essential for reliable estimation.