max_hr

Maximum Heart Rate

Definition

Maximum heart rate. Formally: 60000 / max(IBI).

What does normal look like?

Fitted normative prior: Normal(μ = 65.69, σ = 13.75), KS p = 9e-68, n = 61715.

Empirical distribution over the pooled nsrdb+nsr2db normative windows (360-beat windows, 120-beat stride), overlaid with the fitted Normal 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.

Elevated resting/mean heart rate is one of the most consistently replicated clinical predictors: dose-response meta-analyses pooling dozens of prospective cohorts (> 1.2 million subjects) show a near-linear rise in all-cause and cardiovascular mortality, coronary heart disease, heart failure and even cancer incidence per +10 bpm. Age-predicted HRmax (208 − 0.7·age) is itself a load-bearing exercise-testing constant from a 351-study meta-analytic pooling.

Dominant reported direction: up: higher resting HR → higher mortality/CV risk (≈RR 1.08–1.17 per 10 bpm).

Key references: (Zhang et al., 2016); (Aune et al., 2017); (Tanaka et al., 2001).

Sports & peak performance

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

Lower resting HR ("training bradycardia") and faster post-exercise heart-rate recovery (HRR) are classic, meta-analyzed markers of positive training adaptation, but the same meta-analysis found faster HRR also accompanies functional overreaching, so the identical directional signal reads as both "good" and "bad" depending on context.

Dominant reported direction: down at rest / faster HRR, but HRR speed alone cannot separate adaptation from overreaching.

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

Contemplative practice

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

A 45-RCT meta-analysis finds meditation reduces heart rate overall (concentrated in "open monitoring" styles), but this is contested: a more recent physiological study found HR unchanged or significantly increased during Chi/Kundalini-yoga meditation, explicitly arguing raw HR is a poor real-time biofeedback signal.

Dominant reported direction: contested: meta-analytic decrease vs. style-specific increase/no-change.

Key references: (Pascoe et al., 2017); (Natarajan, 2023).

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

BPM re-expression 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.