Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval.
Other terms used include: "cycle length variability", "RR variability" (where R is a point corresponding to the peak of the QRS complex of the ECG wave; and RR is the interval between successive Rs), and "heart period variability".
Methods used to detect beats include: ECG, blood pressure, ballistocardiograms, and the pulse wave signal derived from a photoplethysmograph (PPG). ECG is considered superior because it provides a clear waveform, which makes it easier to exclude heartbeats not originating in the sinoatrial node. The term "NN" is used in place of RR to emphasize the fact that the processed beats are "normal" beats.
Reduced HRV has been shown to be a predictor of mortality after myocardial infarction although others have shown that the information in HRV relevant to acute myocardial infarction survival is fully contained in the mean heart rate. A range of other outcomes/conditions may also be associated with modified (usually lower) HRV, including congestive heart failure, diabetic neuropathy, depression, post-cardiac transplant, susceptibility to SIDS and poor survival in premature babies.
In the field of psychophysiology, there is interest in HRV. For example, HRV is related to emotional arousal. High-frequency (HF) activity has been found to decrease under conditions of acute time pressure and emotional strain and elevated state anxiety, presumably related to focused attention and motor inhibition. HRV has been shown to be reduced in individuals reporting a greater frequency and duration of daily worry. In individuals with post-traumatic stress disorder (PTSD), HRV and its HF component (see below) is reduced compared to controls whilst the low-frequency (LF) component is elevated. Furthermore, unlike controls, PTSD patients demonstrated no LF or HF reactivity to recalling a traumatic event.
The Polyvagal Theory derives from a psychophysiologic imputation of importance to HRV. This theory emphasizes the role of heart rate variability in understanding the magnitude and nature of vagal outflow to the heart. This theory decomposes heart rate variability based on frequency domain characteristics with an emphasis on respiratory sinus arrhythmia and its transmission by a neural pathway that is distinct from other components of HRV. There is anatomic and physiological evidence for a polyvagal control of the heart.
Variation in the beat-to-beat interval is a physiological phenomenon. The SA node receives several different inputs and the instantaneous heart rate or RR interval and its variation are the results of these inputs.
The main inputs are the sympathetic and the parasympathetic nervous system (PSNS) and humoral factors. Respiration gives rise to waves in heart rate mediated primarily via the PSNS, and it is thought that the lag in the baroreceptor feedback loop may give rise to 10 second waves in heart rate (associated with Mayer waves of blood pressure), but this remains controversial.
Factors that affect the input are the baroreflex, thermoregulation, hormones, sleep-wake cycle, meals, physical activity, and stress.
Decreased PSNS activity or increased SNS activity will result in reduced HRV. High frequency (HF) activity (0.15 to 0.40 Hz), especially, has been linked to PSNS activity. Activity in this range is associated with the respiratory sinus arrhythmia (RSA), a vagally mediated modulation of heart rate such that it increases during inspiration and decreases during expiration. Less is known about the physiological inputs of the low frequency (LF) activity (0.04 to 0.15 Hz). Though previously thought to reflect SNS activity, it is now widely accepted that it reflects a mixture of both the SNS and PSNS The most widely used methods can be grouped under time-domain and frequency-domain. Other methods have been proposed, such as non-linear methods.
These are based on the beat-to-beat or NN intervals, which are analysed to give variables such as: SDNN, the standard deviation of NN intervals. Often calculated over a 24-hour period. SDANN, the standard deviation of the average NN intervals calculated over short periods, usually 5 minutes. SDANN is therefore a measure of changes in heart rate due to cycles longer than 5 minutes. SDNN reflects all the cyclic components responsible for variability in the period of recording, therefore it represents total variability.
RMSSD ("root mean square of successive differences"), the square root of the mean of the squares of the successive differences between adjacent NNs.
SDSD ("standard deviation of successive differences"), the standard deviation of the successive differences between adjacent NNs.
NN50, the number of pairs of successive NNs that differ by more than 50 ms.
pNN50, the proportion of NN50 divided by total number of NNs.
NN20, the number of pairs of successive NNs that differ by more than 20 ms.
pNN20, the proportion of NN20 divided by total number of NNs.
EBC ("estimated breath cycle"), the range (max-min) within a moving window of a given time duration within the study period. The windows can move in a self-overlapping way or be strictly distinct (sequential) windows. EBC is often provided in data acquisition scenarios where HRV feedback in real time is a primary goal. EBC derived from PPG over 10-second and 16-second sequential and overlapping windows has been shown to correlate highly with SDNN.