range

Range Of Inter-Beat Intervals

Definition

Range of inter-beat intervals. Formally: max(IBI) - min(IBI).

What does normal look like?

Fitted normative prior: Gamma(α = 3.49, θ = 94.08), KS p = 4.4e-14, n = 61715.

Empirical distribution over the pooled nsrdb+nsr2db normative windows (360-beat windows, 120-beat stride), overlaid with the fitted Gamma prior density. Vertical lines mark the median and the 5–95% range.

Normal-range summary (pooled nsrdb+nsr2db)

n varies by feature only through per-window validity over the full pooled nsrdb+nsr2db table (n up to 61 715; e.g. sampen/mse drop windows where the statistic is undefined). ulf is the one exception: a 360-beat (~5 min) window contains no ULF-band power, so it uses a long-window NSRDB-only extraction (see its own page).

Use cases

• Short-term vagal / parasympathetic tone (esp. successive-difference measures).
• Ultra-short and 5-min HRV screening; biofeedback targets.
• Stress, recovery, and training-load monitoring.

Applications by area

Evidence is reported at the measure-family level; a specific variant may not be the exact index measured in every cited study.

Clinical

Coverage: statistics. A pooled literature; reviews or meta-analyses exist.

SDNN/SDANN are among the most validated HRV mortality predictors: low values predict higher cardiac/all-cause mortality post-MI, in heart failure, and even in the general population (8 cohorts, n = 21,988). CVNNI has its own well-established sub-literature as a diabetic cardiac autonomic neuropathy screening marker. One acute-decompensated-HF study reports the opposite polarity (higher SDNN/SDANN in the poor-prognosis group).

Dominant reported direction: down: low SDNN/SDANN/CVNNI → higher mortality (one acute-HF exception reversed).

Key references: (Hillebrand et al., 2013); (Rueda-Ochoa et al., 2024).

Sports & peak performance

Coverage: individual papers. A small, scattered literature with no pooled meta-analysis.

Comparatively under-used next to RMSSD in sports HRV monitoring: the field's dedicated meta-analysis pools RMSSD/HF/SD1, not SDNN. Individual studies find SDNN falls with heavy training/overreaching and recovers during taper, and tends to be higher in higher-level athletes, but effect sizes are small-sample and heterogeneous.

Dominant reported direction: down with overreaching, recovers with taper (RMSSD-dominated literature, SDNN secondary).

Key references: (Bellenger et al., 2016).

Contemplative practice

Coverage: individual papers. A small, scattered literature with no pooled meta-analysis.

The weakest of the three domains for this family: two dedicated meta-analyses found the evidence for resting and vagally-mediated HRV (including SDNN) inconclusive or null, with only a handful of trials reporting SDNN at all. Individual acute-state studies diverge sharply in direction (SDNN falls during Heartfulness meditation, rises during Chi/Kundalini-yoga).

Dominant reported direction: contested: meta-analytic null vs. technique-dependent individual-study increases/decreases.

Key references: (Rådmark et al., 2019); (Brown et al., 2021).

See the effect-distribution meta-analysis page for the harvested per-study effect sizes/p-values behind these domain summaries (docs/zoo_gen/effect_stats.csv).

Resources

Resource-intensity rank ◍◍◌◌◌ low is measured: median wall-clock time and allocations over a 360-beat window on synthetic realistic RR (docs/zoo_gen/bench_resources.jl; full grid in resource_bench.csv).

Cold = fresh memoization caches (builds every shared representation from scratch); warm = shared representations (diff, periodogram, Poincaré coords, DFA fluctuation) already cached, so only this feature is recomputed. The tier is derived from the cold cost; see Level 1–2 (base statistics over successive differences).

Citation

Descriptive primitive of the Task Force (1996) time-domain panel.

Seminal reference(s): (Task Force, European Society of Cardiology / North American Society of Pacing & Electrophysiology, 1996).

See the References page for the full bibliography.