A
Acute Stress
Short-term stress caused by a specific event (meeting, workout, argument, deadline).
Why it matters: Acute stress is normal. Problems arise when it doesn’t resolve.
Reference: McEwen, 1998
Accentuated Antagonism
A physiological effect where parasympathetic (vagal) signals have a stronger impact when sympathetic activity is already present.
Why it matters: Explains why vagal “braking” after stress or exercise can be powerful even when the body is still activated.
Reference: Shaffer & Ginsberg, 2017
Allostatic Load
The cumulative “wear and tear” on the body from repeated or chronic stress.
Why it matters: Sustained low HRV often reflects high allostatic load, not a single bad day.
Reference: McEwen & Stellar, 1993
Approximate Entropy (ApEn)
A non-linear HRV metric that measures how predictable or regular heart rhythm patterns are. Lower values suggest more rigid physiology; higher values suggest more complexity.
Limitation: Sensitive to data length and noise, which is why it’s used less today.
Artifact
Any error in heart rhythm data caused by movement, poor sensor contact, missed beats, or electrical noise.
Why it matters: Even a single artifact can dramatically distort HRV metrics if not corrected.
Autonomic Nervous System (ANS)
The system that regulates automatic body functions like heart rate, digestion, and breathing. It includes:
- Parasympathetic branch (rest and recovery)
- Sympathetic branch (activation and stress)
Why it matters: HRV reflects how flexible and balanced the ANS is.
Reference: Shaffer & Ginsberg, 2017
B
Baroreflex
A fast feedback system that adjusts heart rate in response to blood pressure changes.
Why it matters: One of the main drivers of resting HRV—often more influential than stress itself.
Reference: La Rovere et al., 2008
Baroreflex Sensitivity (BRS)
A measure of how strongly heart rate responds to changes in blood pressure. Higher sensitivity generally reflects better cardiovascular adaptability.
Why it matters: A major driver of resting HRV, often misattributed to “vagal tone.”
Baseline HRV
Your typical HRV level when measured under consistent conditions (usually mornings at rest).
Important: Baselines are individual. Comparisons between people are often meaningless.
Why it matters: HRV must be interpreted relative to your own baseline, not population averages.
Reference: Plews et al., 2017
C
Chaos (Physiological)
Healthy biological systems show controlled irregularity, not perfect order. HRV reflects this “organized chaos.” Too little or too much chaos can both signal dysfunction.
Correlation Dimension (D2)
A non-linear metric estimating how many variables influence heart rhythm dynamics. Higher values suggest greater physiological complexity.
Chronic Stress
Stress that persists without sufficient recovery.
Why it matters: Chronic stress is associated with prolonged HRV suppression.
Reference: Thayer et al., 2012
Circadian Rhythm
Your body’s internal 24-hour clock.
Why it matters: HRV follows circadian patterns, which is why morning measurements are more reliable.
Reference: Portaluppi et al., 2012
D
Data Fatigue
Mental exhaustion caused by excessive health data and alerts.
Why it matters: Over-monitoring can increase stress and reduce motivation.
Reference: Owens et al., 2018
Detrended Fluctuation Analysis (DFA α1 / α2)
Non-linear metrics describing short-term (α1) and long-term (α2) correlations in HRV. Used in fatigue, endurance, and overtraining research.
Reference: Peng et al., 1995
Dynamic Autonomic Relationship
The parasympathetic and sympathetic systems do not work like a seesaw. They can increase together, suppress each other, or act independently.
This is why simple “balance scores” are misleading.
E
ECG (Electrocardiogram)
A method that measures the heart’s electrical activity directly.
Why it matters: ECG is the gold standard for HRV measurement.
Reference: Task Force of the ESC, 1996
Electrodermal Activity (EDA)
Often used in high-end wearables (like Fitbit or Oura) to measure “stress” via skin conductance.
Why it matters: Reflects sympathetic arousal but is highly context- and sweat-dependent; not a direct ‘stress score.’
Emergent Property
HRV is not produced by one organ or pathway. It emerges from interactions between the heart, brain, lungs, hormones, and blood vessels.
F
Frequency-Domain HRV
HRV analysis that looks at how heart rhythm variability is distributed across frequency bands. Useful, but easy to misinterpret without strict measurement conditions.
Reference: Shaffer & Ginsberg, 2017
H
HF Band (High Frequency, 0.15–0.40 Hz)
Reflects fast heart rhythm oscillations, strongly influenced by breathing. Often associated with parasympathetic modulation—but not a direct vagal meter.
HF Power
The amount of variability in the HF band. Highly sensitive to breathing rate and posture.
What it reflects: Parasympathetic (vagal) modulation linked to respiration.
Reference: Grossman & Taylor, 2007
HR Max − HR Min
Difference between highest and lowest heart rate during a breathing cycle. Reflects respiratory sinus arrhythmia, not vagal tone directly.
Heart Rate (HR)
The number of heartbeats per minute.
Why it matters: Heart rate alone does not reflect stress or recovery quality.
Reference: Billman, 2011
Heart Rate Variability (HRV)
The variation in time between consecutive heartbeats.
Why it matters: HRV reflects how well the body adapts to stress and recovers.
Reference: Task Force of the ESC, 1996
HRV Biofeedback
A training technique that uses real-time feedback (visual, auditory, or tactile) to help a person increase their heart rate variability, typically through paced breathing at their resonance frequency (~0.1 Hz or 5–6 breaths per minute).
Why it matters: HRV biofeedback is used to improve autonomic regulation, reduce stress, enhance emotional control, and support recovery.
Reference: Lehrer & Gevirtz, 2014
HRV Triangular Index (HTI)
A geometric HRV metric based on the distribution of RR intervals over time. Total number of RR intervals divided by the height of their histogram. Mostly used in long-term recordings.
Reference: Task Force of the ESC, 1996
I
Interbeat Interval (IBI / RR Interval)
The time between consecutive heartbeats. All HRV metrics are derived from these intervals.
Interoception
The ability to sense internal bodily signals.
Why it matters: Excessive reliance on data can reduce trust in bodily awareness.
Reference: Mehling et al., 2012
L
LF Band (Low Frequency, 0.04–0.15 Hz)
Represents slower oscillations influenced by baroreflex and breathing.
Not a clean marker of sympathetic activity.
LF Peak / HF Peak
The dominant frequency within the LF or HF band.
Why it matters: Indicates breathing rate or autonomic rhythm dominance.
LF/HF Ratio
Often marketed as “autonomic balance” (between sympathetic and parasympathetic activity).
In reality: Only meaningful under tightly controlled lab conditions and often misleading in daily life.
Current consensus: Oversimplified and often misleading.
Why many researchers avoid it: Physiology does not support a clean “sympathovagal balance” interpretation.
Reference: Billman, 2013
LnRMSSD / LnHF
Log-transformed HRV metrics used to stabilize statistical distributions. Natural logarithm of RMSSD.
Why used:
- Normalizes skewed data
- Easier trend analysis
Common in: Athlete monitoring.
Reference: Plews et al., 2013
Long-Term HRV (24-Hour HRV)
HRV calculated from full-day ambulatory ECG recordings.
Why it matters: Considered the clinical gold standard.
Key insight: Same math, different physiology compared to short-term HRV.
Loss of Complexity
A reduction in the natural variability and adaptability of physiological systems. Seen in aging, chronic disease, and prolonged stress.
LF Power
The amount of variability in the LF band.
What it reflects: Mixed influences (baroreflex, autonomic modulation).
Common misconception: LF ≠ sympathetic activity.
Reference: Goldstein et al., 2011
M
Measurement Context
Everything surrounding how HRV is recorded: posture, breathing, time of day, movement, sensor type, and artifacts.
Context determines meaning.
Mean RR
Average time between heartbeats.
What it reflects: Average heart rate.
Note: Not an HRV metric by itself.
Measurement Noise
Random variation unrelated to real physiological change.
Examples: Poor sensor contact, irregular breathing, movement.
Why it matters: Explains many sudden HRV drops.
Measurement Non-Interchangeability
The principle that HRV values from different recording lengths cannot be directly compared.
Why it matters: Explains why your sleep HRV, morning HRV, and all-day HRV tell different stories.
Morning HRV
HRV measured shortly after waking, before daily stressors. Best single snapshot for tracking trends over time.
Why it matters: It minimizes noise from movement, food, and daily stress.
Reference: Plews et al., 2017
N
NN50
An HRV metric that counts the number of successive RR pairs differing by more than 50 ms.
What it reflects: Parasympathetic activity.
Limitation: Sensitive to heart rate and recording length.
Non-Linear HRV Metrics
Metrics that capture complexity and unpredictability rather than magnitude alone. Examples: SD1, SD2, SampEn, DFA.
Nocebo Effect
Negative outcomes caused by negative expectations.
Why it matters: Health warnings can increase perceived stress.
Reference: Barsky et al., 2002
Normal Units (nu)
Relative power of LF or HF normalized against LF+HF.
Why it matters: Allows comparison between people with different absolute HRV levels.
P
Parasympathetic Nervous System (PNS)
The branch of the ANS responsible for recovery, digestion, and calming. Acts quickly—within milliseconds.
Why it matters: Higher resting parasympathetic activity is associated with higher HRV.
Reference: Thayer et al., 2010
Parasympathetic Rebound
An increase in parasympathetic activity following intense stress or exertion. Explains high HRV during sleep after hard days.
Poincaré Plot
A visual plot of each RR interval against the previous one. Used to derive SD1 and SD2:
- SD1: Short-term variability (≈ RMSSD)
- SD2: Long-term variability
Why it matters: Visual and intuitive representation of HRV structure.
Reference: Tulppo et al., 1996
Paced Breathing
Controlled breathing used in HRV biofeedback. Can artificially inflate HRV if used during measurement.
PPG (Photoplethysmography)
Optical method used by smartwatches to estimate heart activity.
Why it matters: Convenient but more sensitive to motion artifacts than ECG.
Reference: Charlton et al., 2018
pNN50
Percentage of NN50 relative to total intervals.
Why it’s rare now: Less reliable than RMSSD for short recordings.
R
RR Interval (NN Interval)
The time (in milliseconds) between two consecutive heartbeats.
Why it matters: All HRV metrics are derived from RR intervals.
Recovery
The process of returning to baseline after stress.
Why it matters: Recovery capacity matters more than avoiding stress.
Respiratory Sinus Arrhythmia (RSA)
Heart rate speeding up during inhalation and slowing during exhalation.
Why it matters: A major contributor to short-term HRV.
Reference: Grossman & Taylor, 2007
Respiratory Rate
Often derived from the same PPG signal as HRV and used as a key component of “Recovery” or “Readiness” scores.
Why it matters: Elevated resting respiratory rate can indicate strain or illness even when HRV seems normal.
RMSSD (Root Mean Square of Successive Differences)
Square root of the mean squared differences between successive RR intervals. The most commonly used HRV metric in wearables.
What it reflects: Primarily parasympathetic (vagal) modulation. Reflects short-term variability and parasympathetic modulation.
Why it matters:
- Most robust for short recordings
- Least affected by breathing variability
- Gold standard for daily HRV tracking
Used by: Most modern HRV apps and wearables.
Reference: Shaffer & Ginsberg, 2017; Plews et al., 2017
S
Sample Entropy (SampEn)
A refined version of Approximate Entropy. Measures signal complexity with less sensitivity to noise.
Why it matters: Lower entropy = more rigid system.
Reference: Richman & Moorman, 2000
SD1 / SD2
Non-linear HRV metrics derived from the Poincaré plot.
- SD1: Short-term variability (directly related to RMSSD)
- SD2: Longer-term variability
SDNN (Standard Deviation of NN Intervals)
Standard deviation of all RR intervals in a recording.
What it reflects: Overall HRV (both sympathetic and parasympathetic influences).
Used in:
- Long recordings (≥5 min, 24h Holter)
- Clinical and epidemiological studies
Limitations:
- Strongly influenced by recording length
- Not ideal for short daily measurements
Reference: Task Force of the ESC, 1996
Short-Term HRV (ST-HRV)
HRV calculated from ~5-minute recordings, usually at rest.
Why it matters: This is what most morning readiness and stress measurements are based on.
Key insight: ST-HRV reflects parasympathetic activity and baroreflex, not “overall autonomic balance.”
SDSD
Standard deviation of successive RR differences.
What it reflects: Similar to RMSSD.
Why it’s less used: RMSSD is mathematically more stable.
Sleep Quality
A combination of duration, continuity, and structure of sleep.
Why it matters: Poor sleep strongly suppresses HRV.
Reference: Krause et al., 2017
Stress
A physiological state involving nervous, hormonal, and cardiovascular responses. The body’s response to perceived demand.
Why it matters: Stress is not inherently harmful; unresolved stress is.
Reference: McEwen, 1998
Sympathetic Nervous System (SNS)
The branch of the ANS responsible for activation, alertness, and energy mobilization.
Why it matters: Dominance of sympathetic activity is associated with lower HRV.
T
Total Power
Sum of HRV energy across frequency bands.
What it reflects: Overall autonomic activity, not readiness.
Trend
The direction of change over time.
Why it matters: Trends matter far more than daily values.
Time-Domain HRV
HRV metrics calculated directly from beat-to-beat intervals (e.g., RMSSD).
Why it matters: Most practical and reliable for daily tracking.
Reference: Task Force of the ESC, 1996
TINN
Triangular Interpolation of the NN Interval Histogram. A geometric HRV metric robust to noise.
Why it’s rare: Requires large datasets.
U
Ultra-Short-Term HRV (<5 minutes)
HRV estimated from very brief recordings (10–60 seconds). Convenient but less reliable and not interchangeable with longer measures.
Why it matters: Common in wearables and controversial.
Key insight: UST-HRV is not interchangeable with 5-min or 24-h HRV.
ULF Band
Ultra-low-frequency HRV components seen only in 24-hour recordings.
V
Vagal Modulation
Influence of the vagus nerve on heart rate patterns. HRV is a proxy for this under controlled conditions—not a direct measurement.
Vagal Tone
The influence of the vagus nerve on heart activity.
Why it matters: HRV reflects vagal modulation but is not identical to vagal tone.
Reference: Laborde et al., 2017
Vagus Nerve
A major nerve connecting the brain to the heart and organs.
Why it matters: Primary pathway for heart-brain communication, particularly for parasympathetic regulation.
VLF Band
Very-low-frequency oscillations influenced by hormones, thermoregulation, and circadian rhythms.
W
Wearables
Consumer technology that measures physiological signals. Accuracy depends on context, algorithms, and data handling.
Why it matters: Wearables provide trends, not diagnoses.
Z
Z-Scores / Normalized HRV
HRV expressed relative to personal baseline.
Why it matters: Improves interpretability across individuals.
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