Heart rate variability
Encyclopedia
Heart rate variability (HRV) is a physiological phenomenon where the time interval between heart beats varies. 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".
See also Heart rate turbulence
, Sinus rhythm
.
Methods used to detect beats include: ECG, blood pressure, 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.
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.
HRV studies have also been used to examine autonomic function in the context of bodily pain. Studies of patients with Fybromyalgic Syndrome (FMS) demonstrate reduced general Autonomic Nervous System (ANS) activity and markedly reduced nocturnal ANS activity, increased baseline Sympathetic Nervous System (SNS) activity, and impaired SNS reactivity to stimuli including orthostatic and mental stress.
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. However, there is no anatomic or physiologic evidence for a polyvagal control of the heart.
receives several different inputs and the instantaneous heart rate or RR interval and its variation is the results of these inputs.
The main inputs are the sympathetic
and the parasympathetic nervous system
(PSNS) and humoral factor
s. Respiration gives rise to waves in heart rate mediated primarily via the PSNS, and it is thought that the lag in the baroceptor 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
.
Under normal conditions the RR interval trace of cardiac activity demonstrates variability that is moderated by the PSNS. Decreased PSNS activity or increased SNS activity will result in reduced HRV. High frequency (HF) activity (0.4 to 0.15 Hz), especially, has been linked to PSNS activity. Activity in this range is associated with the respiratory sinus arrhythmia (RSA), a vagally-mediated moderation 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 recent consensus suggests it is influenced either by the SNS or a mixture of both the SNS and PSNS . Because both frequency components may be influenced by the PSNS, SNS activity may be inferred by the ratio of LF to HF activity.
The most commonly encountered artifact in R-wave detection is motion artifact. Other forms of artifact include electrode movement with respect to the skin interface (disrupting electrochemical equilibrium); muscle contraction resulting in unwanted electromyographic contamination that may share the desired signal frequency band; vocalizations; temperature changes; sensor-cross-talk; optical path length changes and electromagnetic induction.
Some HRV Analysis software offers advanced artifact management techniques that include:
1. a basic measurement of the geometric pattern (for example, the width of the distribution histogram at the specified level) is converted into the measure of HRV
2. the geometric pattern is interpolated by a mathematically defined shape (for example, approximation of the distribution histogram by a triangle or approximation of the differential histogram by an exponential curve) and then the parameters of this mathematical shape are used
3. the geometric shape is classified into several pattern-based categories that represent different classes of HRV (for example, elliptic, linear, and triangular shapes of Lorenz plots). Most geometric methods require the RR (or NN) interval sequence to be measured on or converted to a discrete scale that is not too fine or too coarse and permits the construction of smoothed histograms. Most experience has been obtained with the length of the bins of approximately 8 ms (precisely 7.8125 ms=1/128 seconds), which corresponds to the precision of current commercial equipment.
The HRV triangular index measurement is the integral of the density distribution (that is, the number of all NN intervals) divided by the maximum of the density distribution. Using a measurement of NN intervals on a discrete scale, the measure is approximated by the value (total number of NN intervals)/(number of NN intervals in the modal bin), which is dependent on the length of the bin, that is, on the precision of the discrete scale of measurement. Thus, if the discrete approximation of the measure is used with NN interval measurement on a scale different from the most frequent sampling of 128 Hz, the size of the bins should be quoted. The triangular interpolation of NN interval histogram (TINN) is the baseline width of the distribution measured as a base of a triangle approximating the NN interval distribution (the minimum square difference is used to find such a triangle). Both these measures express overall HRV measured over 24 hours and are more influenced by the lower than by the higher frequencies.Other geometric methods are still in the phase of exploration and explanation.
The major advantage of the geometric methods lies in their relative insensitivity to the analytical quality of the series of NN intervals. The major disadvantage of the geometric methods is the need for a reasonable number of NN intervals to construct the geometric pattern. In practice, recordings of at least 20 minutes (but preferably 24 hours) should be used to ensure the correct performance of the geometric methods; that is, the current geometric methods are inappropriate to assess short-term changes in HRV.
some measures are:
.
Methods for the calculation of PSD may be generally classified as nonparametric and parametric. In most instances, both methods provide comparable results. The advantages of the nonparametric methods are (1) the simplicity of the algorithm used (fast Fourier transform [FFT] in most of the cases) and (2) the high processing speed, while the advantages of parametric methods are (1) smoother spectral components that can be distinguished independent of preselected frequency bands, (2) easy postprocessing of the spectrum with an automatic calculation of low- and high-frequency power components with an easy identification of the central frequency of each component, and (3) an accurate estimation of PSD even on a small number of samples on which the signal is supposed to maintain stationarity. The basic disadvantage of parametric methods is the need of verification of the suitability of the chosen model and of its complexity (that is, the order of the model).
Spectral Components
Short-term recordings. Three main spectral components are distinguished in a spectrum calculated from short-term recordings of 2 to 5 minutes: VLF, LF, and HF components. The distribution of the power and the central frequency of LF and HF are not fixed but may vary in relation to changes in autonomic modulations of heart period.The physiological explanation of the VLF component is much less defined, and the existence of a specific physiological process attributable to these heart period changes might even be questioned. The nonharmonic component, which does not have coherent properties and is affected by algorithms of baseline or trend removal, is commonly accepted as a major constituent of VLF. Thus, VLF assessed from short-term recordings (5 minutes) is a dubious measure and should be avoided when the PSD of short-term ECGs is interpreted.
Long-term recordings. Spectral analysis also may be used to analyze the sequence of NN intervals of the entire 24-hour period. The result then includes a ULF component, in addition to VLF, LF, and HF components. The slope of the 24-hour spectrum also can be assessed on a log-log scale by linear fitting the spectral values.
Analysis of Short-term Recordings (5 min)
Analysis of Entire 24 Hours
. Each data point represents a pair of successive beats, the x-axis is the current RR interval, while the y-axis is the previous RR interval. HRV is quantified by fitting mathematically defined geometric shapes to the data. Other methods used are the correlation dimension
, nonlinear predictability, pointwise correlation dimension and approximate entropy.
Frequency domain methods should be preferred to the time domain methods when short-term recordings are investigated. The recording should last for at least 10 times the wavelength of the lower frequency bound of the investigated component, and, in order to ensure the stability of the signal, should not be substantially extended. Thus, recording of approximately 1 minute is needed to assess the HF components of HRV, while approximately 2 minutes are needed to address the LF component. To standardize different studies investigating short-term HRV, 5-minute recordings of a stationary system are preferred unless the nature of the study dictates another design.
Averaging of spectral components obtained from sequential periods of time is able to minimize the error imposed by the analysis of very short segments. Nevertheless, if the nature and degree of physiological heart period modulations changes from one short segment of the recording to another, the physiological interpretation of such averaged spectral components suffers from the same intrinsic problems as that of the spectral analysis of long-term recordings and warrants further elucidation. A display of stacked series of sequential power spectra (for example, over 20 minutes) may help confirm steady state conditions for a given physiological state.
Although the time domain methods, especially the SDNN and RMSSD methods, can be used to investigate recordings of short durations, the frequency methods are usually able to provide results that are more easily interpretable in terms of physiological regulations. In general, the time domain methods are ideal for the analysis of long-term recordings (the lower stability of heart rate modulations during long-term recordings makes the results of frequency methods less easily interpretable). The experience shows that a substantial part of the long-term HRV value is contributed by the day-night differences. Thus, the long-term recording analyzed by the time domain methods should contain at least 18 hours of analyzable ECG data that include the whole night.
Little is known about the effects of the environment (type and nature of physical activity and emotional circumstances) during long-term ECG recordings. For some experimental designs, environmental variables should be controlled and in each study, the character of the environment should always be described. The design of investigations also should ensure that the recording environment of individual subjects is similar. In physiological studies comparing HRV in different well-defined groups, the differences between underlying heart rate also should be properly acknowledged.
The sympathetic influence on heart rate is mediated by release of epinephrine and norepinephrine. Activation of ß-adrenergic receptors results in cAMP-mediated phosphorylation of membrane proteins and increases in ICaL and in If the end result is an acceleration of the slow diastolic depolarization.
Under resting conditions, vagal tone prevails and variations in heart period are largely dependent on vagal modulation. The vagal and sympathetic activity constantly interact. Because the sinus node is rich in acetylcholinesterase, the effect of any vagal impulse is brief because the acetylcholine is rapidly hydrolyzed. Parasympathetic influences exceed sympathetic effects probably through two independent mechanisms: (1) a cholinergically induced reduction of norepinephrine released in response to sympathetic activity and (2) a cholinergic attenuation of the response to a adrenergic stimulus.
An understanding of the modulatory effects of neural mechanisms on the sinus node has been enhanced by spectral analysis of HRV. The efferent vagal activity is a major contributor to the HF component, as seen in clinical and experimental observations of autonomic maneuvers such as electrical vagal stimulation, muscarinic receptor blockade, and vagotomy. More controversial is the interpretation of the LF component, which is considered by some as a marker of sympathetic modulation (especially when expressed in normalized units) and by others as a parameter that includes both sympathetic and vagal influences. This discrepancy is due to the fact that in some conditions associated with sympathetic excitation, a decrease in the absolute power of the LF component is observed. It is important to recall that during sympathetic activation the resulting tachycardia is usually accompanied by a marked reduction in total power, whereas the reverse occurs during vagal activation. When the spectral components are expressed in absolute units (milliseconds squared), the changes in total power influence LF and HF in the same direction and prevent the appreciation of the fractional distribution of the energy. This explains why in supine subjects under controlled respiration, atropine reduces both LF and HF and why during exercise LF is markedly reduced. Because of the reduction in total power, LF appears as unchanged if considered in absolute units. However, after normalization an increase in LF becomes evident. Similar results apply to the LF/HF ratio.
Spectral analysis of 24-hour recordings24 25 shows that in normal subjects, LF and HF expressed in normalized units exhibit a circadian pattern and reciprocal fluctuations, with higher values of LF in the daytime and of HF at night. These patterns become undetectable when a single spectrum of the entire 24-hour period is used or when spectra of subsequent shorter segments are averaged. In long-term recordings, the HF and LF components account for only approximately 5% of total power. Although the ULF and VLF components account for the remaining 95% of total power, their physiological correlates are still unknown.
LF and HF can increase under different conditions. An increased LF (expressed in normalized units) is observed during 90° tilt, standing, mental stress, and moderate exercise in healthy subjects, and during moderate hypotension, physical activity, and occlusion of a coronary artery or common carotid arteries in conscious dogs.Conversely, an increase in HF is induced by controlled respiration, cold stimulation of the face, and rotational stimuli.
Disagreement exists in respect to the LF component. Some studies suggest that LF, when expressed in normalized units, is a quantitative marker of sympathetic modulations; other studies view LF as reflecting both sympathetic activity and vagal activity. Consequently, the LF/HF ratio is considered by some investigators to mirror sympathovagal balance or to reflect the sympathetic modulations.
Physiological interpretation of lower-frequency components of HRV (that is, of the VLF and ULF components) warrants further elucidation.
It is important to note that HRV measures fluctuations in autonomic inputs to the heart rather than the mean level of autonomic inputs. Thus, both autonomic withdrawal and saturatingly high level of sympathetic input lead to diminished HRV.
The mechanism by which HRV is transiently reduced after MI and by which a depressed HRV is predictive of the neural response to acute MI is not yet defined, but it is likely to involve derangements in the neural activity of cardiac origin. One hypothesis85 involves cardiocardiac sympathosympathetic and sympathovagal reflexes and suggests that the changes in the geometry of a beating heart due to necrotic and noncontracting segments may abnormally increase the firing of sympathetic afferent fibers by mechanical distortion of the sensory endings. This sympathetic excitation attenuates the activity of vagal fibers directed to the sinus node. Another explanation, especially applicable to marked reduction of HRV, is the reduced responsiveness of sinus nodal cells to neural modulations.
Spectral analysis of HRV in patients surviving an acute MI revealed a reduction in total and in the individual power of spectral components.89 However, when the power of LF and HF was calculated in normalized units, an increased LF and a diminished HF were observed during both resting controlled conditions and 24-hour recordings analyzed over multiple 5-minute periods. These changes may indicate a shift of sympathovagal balance toward a sympathetic predominance and a reduced vagal tone. Similar conclusions were obtained by considering the changes in LF/HF ratio. The presence of an alteration in neural control mechanisms was also reflected by the blunting of the day-night variations of RR interval91 and LF and HF spectral components present in a period ranging from days to a few weeks after the acute event. In post-MI patients with a very depressed HRV, most of the residual energy is distributed in the VLF frequency range below 0.03 Hz, with only a small respiration-related These characteristics of the spectral profile are similar to those observed in an advanced cardiac failure or after cardiac transplant and are likely to reflect either a diminished responsiveness of the target organ to neural modulatory inputs82 or a saturating influence on the sinus node of a persistently high sympathetic tone.
Time Domain Analysis of Nominal 24 hours
Other terms used include: "cycle length variability", "RR variability" (where R is a point corresponding to the peak of the QRS complex
QRS complex
The QRS complex is a name for the combination of three of the graphical deflections seen on a typical electrocardiogram . It is usually the central and most visually obvious part of the tracing. It corresponds to the depolarization of the right and left ventricles of the human heart...
of the ECG wave; and RR is the interval between successive Rs), and "heart period variability".
See also Heart rate turbulence
Heart rate turbulence
Heart rate turbulence is the return to equilibrium of heart rate after a premature ventricular contraction . It consists of a brief speed-up in heart rate, followed by a slow decrease back to the baseline rate...
, Sinus rhythm
Sinus rhythm
In medicine, sinus rhythm is the normal beating of the heart, as measured by an electrocardiogram . It has certain generic features that serve as hallmarks for comparison with normal ECGs.- ECG structure :...
.
Methods used to detect beats include: ECG, blood pressure, and the pulse wave signal derived from a photoplethysmograph
Photoplethysmograph
A photoplethysmogram is an optically obtained plethysmogram, a volumetric measurement of an organ. A PPG is often obtained by using a pulse oximeter which illuminates the skin and measures changes in light absorption...
(PPG). ECG is considered superior because it provides a clear waveform, which makes it easier to exclude heartbeats not originating in the sinoatrial node
Sinoatrial node
The sinoatrial node is the impulse-generating tissue located in the right atrium of the heart, and thus the generator of normal sinus rhythm. It is a group of cells positioned on the wall of the right atrium, near the entrance of the superior vena cava...
. The term "NN" is used in place of RR to emphasize the fact that the processed beats are "normal" beats.
Clinical significance
Reduced HRV has been shown to be a predictor of mortality after myocardial infarctionMyocardial infarction
Myocardial infarction or acute myocardial infarction , commonly known as a heart attack, results from the interruption of blood supply to a part of the heart, causing heart cells to die...
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
Congestive heart failure
Heart failure often called congestive heart failure is generally defined as the inability of the heart to supply sufficient blood flow to meet the needs of the body. Heart failure can cause a number of symptoms including shortness of breath, leg swelling, and exercise intolerance. The condition...
, diabetic neuropathy
Diabetic neuropathy
Diabetic neuropathies are neuropathic disorders that are associated with diabetes mellitus. These conditions are thought to result from diabetic microvascular injury involving small blood vessels that supply nerves in addition to macrovascular conditions that can culminate in diabetic neuropathy...
, depression post-cardiac transplant, susceptibility to SIDS
Sudden infant death syndrome
Sudden infant death syndrome is marked by the sudden death of an infant that is unexpected by medical history, and remains unexplained after a thorough forensic autopsy and a detailed death scene investigation. An infant is at the highest risk for SIDS during sleep, which is why it is sometimes...
and poor survival in premature babies.
HRV studies have also been used to examine autonomic function in the context of bodily pain. Studies of patients with Fybromyalgic Syndrome (FMS) demonstrate reduced general Autonomic Nervous System (ANS) activity and markedly reduced nocturnal ANS activity, increased baseline Sympathetic Nervous System (SNS) activity, and impaired SNS reactivity to stimuli including orthostatic and mental stress.
Mental and social aspects
In the field of psychophysiology, there is great 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
Post-traumatic stress disorder
Posttraumaticstress disorder is a severe anxiety disorder that can develop after exposure to any event that results in psychological trauma. This event may involve the threat of death to oneself or to someone else, or to one's own or someone else's physical, sexual, or psychological integrity,...
(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. However, there is no anatomic or physiologic evidence for a polyvagal control of the heart.
Variation
Variation in the beat-to-beat interval is a physiological phenomenon. The SA nodeSinoatrial node
The sinoatrial node is the impulse-generating tissue located in the right atrium of the heart, and thus the generator of normal sinus rhythm. It is a group of cells positioned on the wall of the right atrium, near the entrance of the superior vena cava...
receives several different inputs and the instantaneous heart rate or RR interval and its variation is the results of these inputs.
The main inputs are the sympathetic
Sympathetic nervous system
The sympathetic nervous system is one of the three parts of the autonomic nervous system, along with the enteric and parasympathetic systems. Its general action is to mobilize the body's nervous system fight-or-flight response...
and the parasympathetic nervous system
Parasympathetic nervous system
The parasympathetic nervous system is one of the two main divisions of the autonomic nervous system . The ANS is responsible for regulation of internal organs and glands, which occurs unconsciously...
(PSNS) and humoral factor
Humoral factor
Humoral factors are factors that are transported by the circulatory system, that is, in blood, and include:* Humoral immunity factors in the immune system* Hormones in the endocrine system...
s. Respiration gives rise to waves in heart rate mediated primarily via the PSNS, and it is thought that the lag in the baroceptor feedback loop may give rise to 10 second waves in heart rate (associated with Mayer waves
Mayer waves
Mayer waves are waves in arterial blood pressure brought about by oscillations in baroreceptor and chemoreceptor reflex control systems. The waves are seen both in the ECG and in blood pressure curves and have a frequency about 0.1 Hz...
of blood pressure), but this remains controversial.
Factors that affect the input are the baroreflex
Baroreflex
The baroreflex or baroreceptor reflex is one of the body's homeostatic mechanisms for maintaining blood pressure. It provides a negative feedback loop in which an elevated blood pressure reflexively causes heart rate to decrease therefore causing blood pressure to decrease; likewise, decreased...
, thermoregulation
Thermoregulation
Thermoregulation is the ability of an organism to keep its body temperature within certain boundaries, even when the surrounding temperature is very different...
, hormones, sleep-wake cycle, meals, physical activity, and stress
Stress (biology)
Stress is a term in psychology and biology, borrowed from physics and engineering and first used in the biological context in the 1930s, which has in more recent decades become commonly used in popular parlance...
.
Under normal conditions the RR interval trace of cardiac activity demonstrates variability that is moderated by the PSNS. Decreased PSNS activity or increased SNS activity will result in reduced HRV. High frequency (HF) activity (0.4 to 0.15 Hz), especially, has been linked to PSNS activity. Activity in this range is associated with the respiratory sinus arrhythmia (RSA), a vagally-mediated moderation 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 recent consensus suggests it is influenced either by the SNS or a mixture of both the SNS and PSNS . Because both frequency components may be influenced by the PSNS, SNS activity may be inferred by the ratio of LF to HF activity.
Heart rate variability phenomena
There are three primary fluctuations:- Respiratory arrhythmia (or Respiratory sinus arrhythmiaRespiratory sinus arrhythmiaRespiratory sinus arrhythmia is a naturally occurring variation in heart rate that occurs during a breathing cycle. RSA is also a measure of parasympathetic nervous system activity - which denotes "rest and digest" behaviours.-Overview:...
). This heart rate variation is associated with respiration and faithfully tracks the respiratory rate across a range of frequencies. - Low-frequency oscillations. This heart rate variation is associated with Mayer wavesMayer wavesMayer waves are waves in arterial blood pressure brought about by oscillations in baroreceptor and chemoreceptor reflex control systems. The waves are seen both in the ECG and in blood pressure curves and have a frequency about 0.1 Hz...
(Traube–Hering–Mayer waves) of blood pressure and is usually at a frequency of 0.1 HzHertzThe hertz is the SI unit of frequency defined as the number of cycles per second of a periodic phenomenon. One of its most common uses is the description of the sine wave, particularly those used in radio and audio applications....
or a 6-second period.
HRV artifact
Errors in the location of the instantaneous heart beat will result in errors in the calculation of the HRV. HRV is highly sensitive to artifact and errors in as low as even 2% of the data will result in unwanted biases in HRV calculations. To ensure accurate results therefore it is critical to manage artifact and R-R errors appropriately prior to performing any HRV analyses.Causes of artifact
There are several possible sources of artifact that may arise depending on the specific sensor used to generate the R-R series. Artifact will contaminate the raw measured signal which may in turn result in erroneous detection of R-waves or corresponding instantaneous heart rate. If the underlying raw data is contaminated it will not be possible to accurately measure each heart beat and the HRV analysis will be erroneous.The most commonly encountered artifact in R-wave detection is motion artifact. Other forms of artifact include electrode movement with respect to the skin interface (disrupting electrochemical equilibrium); muscle contraction resulting in unwanted electromyographic contamination that may share the desired signal frequency band; vocalizations; temperature changes; sensor-cross-talk; optical path length changes and electromagnetic induction.
Managing artifact
Different sensors have varying degrees of sensitivity to each type of artifact. Some forms of artifact may be eliminated through the use of advanced filtering techniques and design considerations such as shielded cables. Despite this however, artifact may still occur when measuring R-R data series.Some HRV Analysis software offers advanced artifact management techniques that include:
- Deleting automatically and incorrectly identified RWave markings and inserting markings manually after review.
- Interpolating over R-R intervals that have been affected by artifact. Interpolation is often used to account for ectopic beats in the Ecg signal.
- Excluding artifact affected regions.
HRV analysis
The most widely used methods can be grouped under time-domain and frequency-domain. Other methods have been proposed, such as non-linear methods.Time-domain 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.
- RMSSD, the square root of the mean squared difference of successive 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.
Geometric methods
The series of NN intervals also can be converted into a geometric pattern such as the sample density distribution of NN interval durations, sample density distribution of differences between adjacent NN intervals, Lorenz plot of NN or RR intervals, and so forth, and a simple formula is used that judges the variability on the basis of the geometric and/or graphics properties of the resulting pattern. Three general approaches are used in geometric methods:1. a basic measurement of the geometric pattern (for example, the width of the distribution histogram at the specified level) is converted into the measure of HRV
2. the geometric pattern is interpolated by a mathematically defined shape (for example, approximation of the distribution histogram by a triangle or approximation of the differential histogram by an exponential curve) and then the parameters of this mathematical shape are used
3. the geometric shape is classified into several pattern-based categories that represent different classes of HRV (for example, elliptic, linear, and triangular shapes of Lorenz plots). Most geometric methods require the RR (or NN) interval sequence to be measured on or converted to a discrete scale that is not too fine or too coarse and permits the construction of smoothed histograms. Most experience has been obtained with the length of the bins of approximately 8 ms (precisely 7.8125 ms=1/128 seconds), which corresponds to the precision of current commercial equipment.
The HRV triangular index measurement is the integral of the density distribution (that is, the number of all NN intervals) divided by the maximum of the density distribution. Using a measurement of NN intervals on a discrete scale, the measure is approximated by the value (total number of NN intervals)/(number of NN intervals in the modal bin), which is dependent on the length of the bin, that is, on the precision of the discrete scale of measurement. Thus, if the discrete approximation of the measure is used with NN interval measurement on a scale different from the most frequent sampling of 128 Hz, the size of the bins should be quoted. The triangular interpolation of NN interval histogram (TINN) is the baseline width of the distribution measured as a base of a triangle approximating the NN interval distribution (the minimum square difference is used to find such a triangle). Both these measures express overall HRV measured over 24 hours and are more influenced by the lower than by the higher frequencies.Other geometric methods are still in the phase of exploration and explanation.
The major advantage of the geometric methods lies in their relative insensitivity to the analytical quality of the series of NN intervals. The major disadvantage of the geometric methods is the need for a reasonable number of NN intervals to construct the geometric pattern. In practice, recordings of at least 20 minutes (but preferably 24 hours) should be used to ensure the correct performance of the geometric methods; that is, the current geometric methods are inappropriate to assess short-term changes in HRV.
some measures are:
- HRV triangular index: Total number of all NN intervals divided by the height of the histogram of all NN intervals measured on a discrete scale with bins of 7.8125 ms (1/128 seconds)
- TINN: Baseline width of the minimum square difference triangular interpolation of the highest peak of the histogram of all NN intervals
- Differential index: Difference between the widths of the histogram of differences between adjacent NN intervals measured at selected heights (eg, at the levels of 1000 and 10 000 samples)
- Logarithmic index: Coefficient of the negative exponential curve k · e-t, which is the best approximation of the histogram of absolute differences between adjacent NN intervals
Frequency-domain methods
Several methods are available. Power spectral density (PSD), using parametric or nonparametric methods, provides basic information on the power distribution across frequencies. One of the most commonly used PSD methods is the discrete Fourier transformDiscrete Fourier transform
In mathematics, the discrete Fourier transform is a specific kind of discrete transform, used in Fourier analysis. It transforms one function into another, which is called the frequency domain representation, or simply the DFT, of the original function...
.
Methods for the calculation of PSD may be generally classified as nonparametric and parametric. In most instances, both methods provide comparable results. The advantages of the nonparametric methods are (1) the simplicity of the algorithm used (fast Fourier transform [FFT] in most of the cases) and (2) the high processing speed, while the advantages of parametric methods are (1) smoother spectral components that can be distinguished independent of preselected frequency bands, (2) easy postprocessing of the spectrum with an automatic calculation of low- and high-frequency power components with an easy identification of the central frequency of each component, and (3) an accurate estimation of PSD even on a small number of samples on which the signal is supposed to maintain stationarity. The basic disadvantage of parametric methods is the need of verification of the suitability of the chosen model and of its complexity (that is, the order of the model).
Spectral Components
Short-term recordings. Three main spectral components are distinguished in a spectrum calculated from short-term recordings of 2 to 5 minutes: VLF, LF, and HF components. The distribution of the power and the central frequency of LF and HF are not fixed but may vary in relation to changes in autonomic modulations of heart period.The physiological explanation of the VLF component is much less defined, and the existence of a specific physiological process attributable to these heart period changes might even be questioned. The nonharmonic component, which does not have coherent properties and is affected by algorithms of baseline or trend removal, is commonly accepted as a major constituent of VLF. Thus, VLF assessed from short-term recordings (5 minutes) is a dubious measure and should be avoided when the PSD of short-term ECGs is interpreted.
Long-term recordings. Spectral analysis also may be used to analyze the sequence of NN intervals of the entire 24-hour period. The result then includes a ULF component, in addition to VLF, LF, and HF components. The slope of the 24-hour spectrum also can be assessed on a log-log scale by linear fitting the spectral values.
- Selected Frequency Domain Measures of HRV
- Variable, Units, Description, Frequency Range
Analysis of Short-term Recordings (5 min)
- 5-min total power ms2 The variance of NN intervals over the temporal segment 0.4 Hz
- VLF ms2 Power in VLF range 0.04 Hz
- LF ms2 Power in LF range 0.04–0.15 Hz
- LF norm nu LF power in normalized units LF/(total power-VLF)x100
- HF ms2 Power in HF range 0.15-0.4 Hz
- HF norm nu HF power in normalized units HF/(total power-VLF)x100
- LF/HF Ratio LF [ms2]/HF[ms2]
Analysis of Entire 24 Hours
- Total power ms2 Variance of all NN intervals 0.4 Hz
- ULF ms2 Power in the ULF range 0.003 Hz
- VLF ms2 Power in the VLF range 0.003-0.04 Hz
- LF ms2 Power in the LF range 0.04-0.15 Hz
- HF ms2 Power in the HF range 0.15-0.4 Hz
- alpha Slope of the linear interpolation of the spectrum in a log-log scale 0.04 Hz
Non-linear methods
Given the complexity of the mechanisms regulating heart rate, it is reasonable to assume that applying HRV analysis based on methods of non-linear dynamics will yield valuable information. Although chaotic behavior has been assumed, more rigorous testing has shown that heart rate variability cannot be described as a chaotic process . The most commonly used non-linear method of analysing heart rate variability is the Poincaré plotPoincaré plot
A Poincaré plot, named after Henri Poincaré, is used to quantify self-similarity in processes, usually periodic functions. It is also known as a return map.Given a time series of the form...
. Each data point represents a pair of successive beats, the x-axis is the current RR interval, while the y-axis is the previous RR interval. HRV is quantified by fitting mathematically defined geometric shapes to the data. Other methods used are the correlation dimension
Correlation dimension
In chaos theory, the correlation dimension is a measure of the dimensionality of the space occupied by a set of random points, often referred to as a type of fractal dimension....
, nonlinear predictability, pointwise correlation dimension and approximate entropy.
Long term correlations
Sequences of RR intervals have been found to have long-term correlations. For subjects with severe heart disease the long term correlations disappear. Also, during deep sleep the long term correlations do not appear.Analysis software
Numerous software packages exist to analyze heart rate variability. These include:- VivoSense
- Kubios
- Nevrokard
- Acqknowledge
- Mindware
- Kardia
- HRV toolkit for MatLab
- Firstbeat
- LabChart
- R-HRV package for R environment
Duration and circumstances of ECG recording
In studies researching HRV, the duration of recording is dictated by the nature of each investigation. Standardization is needed particularly in studies investigating the physiological and clinical potential of HRV.Frequency domain methods should be preferred to the time domain methods when short-term recordings are investigated. The recording should last for at least 10 times the wavelength of the lower frequency bound of the investigated component, and, in order to ensure the stability of the signal, should not be substantially extended. Thus, recording of approximately 1 minute is needed to assess the HF components of HRV, while approximately 2 minutes are needed to address the LF component. To standardize different studies investigating short-term HRV, 5-minute recordings of a stationary system are preferred unless the nature of the study dictates another design.
Averaging of spectral components obtained from sequential periods of time is able to minimize the error imposed by the analysis of very short segments. Nevertheless, if the nature and degree of physiological heart period modulations changes from one short segment of the recording to another, the physiological interpretation of such averaged spectral components suffers from the same intrinsic problems as that of the spectral analysis of long-term recordings and warrants further elucidation. A display of stacked series of sequential power spectra (for example, over 20 minutes) may help confirm steady state conditions for a given physiological state.
Although the time domain methods, especially the SDNN and RMSSD methods, can be used to investigate recordings of short durations, the frequency methods are usually able to provide results that are more easily interpretable in terms of physiological regulations. In general, the time domain methods are ideal for the analysis of long-term recordings (the lower stability of heart rate modulations during long-term recordings makes the results of frequency methods less easily interpretable). The experience shows that a substantial part of the long-term HRV value is contributed by the day-night differences. Thus, the long-term recording analyzed by the time domain methods should contain at least 18 hours of analyzable ECG data that include the whole night.
Little is known about the effects of the environment (type and nature of physical activity and emotional circumstances) during long-term ECG recordings. For some experimental designs, environmental variables should be controlled and in each study, the character of the environment should always be described. The design of investigations also should ensure that the recording environment of individual subjects is similar. In physiological studies comparing HRV in different well-defined groups, the differences between underlying heart rate also should be properly acknowledged.
Autonomic influences of heart rate
Although cardiac automaticity is intrinsic to various pacemaker tissues, heart rate and rhythm are largely under the control of the autonomic nervous system. The parasympathetic influence on heart rate is mediated via release of acetylcholine by the vagus nerve. Muscarinic acetylcholine receptors respond to this release mostly by an increase in cell membrane K+ conductance.Acetylcholine also inhibits the hyperpolarization-activated "pacemaker" current If the "Ik decay" hypothesis65 proposes that pacemaker depolarization results from slow deactivation of the delayed rectifier current, Ik, which, due to a time-independent background inward current, causes diastolic depolarization. Conversely, the "If activation" hypothesis suggests that after action potential termination, If provides a slowly activating inward current predominating over decaying Ik, thus initiating slow diastolic depolarization.The sympathetic influence on heart rate is mediated by release of epinephrine and norepinephrine. Activation of ß-adrenergic receptors results in cAMP-mediated phosphorylation of membrane proteins and increases in ICaL and in If the end result is an acceleration of the slow diastolic depolarization.
Under resting conditions, vagal tone prevails and variations in heart period are largely dependent on vagal modulation. The vagal and sympathetic activity constantly interact. Because the sinus node is rich in acetylcholinesterase, the effect of any vagal impulse is brief because the acetylcholine is rapidly hydrolyzed. Parasympathetic influences exceed sympathetic effects probably through two independent mechanisms: (1) a cholinergically induced reduction of norepinephrine released in response to sympathetic activity and (2) a cholinergic attenuation of the response to a adrenergic stimulus.
Components of HRV
The RR interval variations present during resting conditions represent a fine tuning of the beat-to-beat control mechanisms.Vagal afferent stimulation leads to reflex excitation of vagal efferent activity and inhibition of sympathetic efferent activity. The opposite reflex effects are mediated by the stimulation of sympathetic afferent activity. Efferent vagal activity also appears to be under "tonic" restraint by cardiac afferent sympathetic activity. Efferent sympathetic and vagal activities directed to the sinus node are characterized by discharge largely synchronous with each cardiac cycle that can be modulated by central (vasomotor and respiratory centers) and peripheral (oscillation in arterial pressure and respiratory movements) oscillators. These oscillators generate rhythmic fluctuations in efferent neural discharge that manifest as short- and long-term oscillation in the heart period. Analysis of these rhythms may permit inferences on the state and function of (a) the central oscillators, (b) the sympathetic and vagal efferent activity, (c) humoral factors, and (d) the sinus node.An understanding of the modulatory effects of neural mechanisms on the sinus node has been enhanced by spectral analysis of HRV. The efferent vagal activity is a major contributor to the HF component, as seen in clinical and experimental observations of autonomic maneuvers such as electrical vagal stimulation, muscarinic receptor blockade, and vagotomy. More controversial is the interpretation of the LF component, which is considered by some as a marker of sympathetic modulation (especially when expressed in normalized units) and by others as a parameter that includes both sympathetic and vagal influences. This discrepancy is due to the fact that in some conditions associated with sympathetic excitation, a decrease in the absolute power of the LF component is observed. It is important to recall that during sympathetic activation the resulting tachycardia is usually accompanied by a marked reduction in total power, whereas the reverse occurs during vagal activation. When the spectral components are expressed in absolute units (milliseconds squared), the changes in total power influence LF and HF in the same direction and prevent the appreciation of the fractional distribution of the energy. This explains why in supine subjects under controlled respiration, atropine reduces both LF and HF and why during exercise LF is markedly reduced. Because of the reduction in total power, LF appears as unchanged if considered in absolute units. However, after normalization an increase in LF becomes evident. Similar results apply to the LF/HF ratio.
Spectral analysis of 24-hour recordings24 25 shows that in normal subjects, LF and HF expressed in normalized units exhibit a circadian pattern and reciprocal fluctuations, with higher values of LF in the daytime and of HF at night. These patterns become undetectable when a single spectrum of the entire 24-hour period is used or when spectra of subsequent shorter segments are averaged. In long-term recordings, the HF and LF components account for only approximately 5% of total power. Although the ULF and VLF components account for the remaining 95% of total power, their physiological correlates are still unknown.
LF and HF can increase under different conditions. An increased LF (expressed in normalized units) is observed during 90° tilt, standing, mental stress, and moderate exercise in healthy subjects, and during moderate hypotension, physical activity, and occlusion of a coronary artery or common carotid arteries in conscious dogs.Conversely, an increase in HF is induced by controlled respiration, cold stimulation of the face, and rotational stimuli.
Summary and recommendations for interpretation of HRV components
Vagal activity is the major contributor to the HF component.Disagreement exists in respect to the LF component. Some studies suggest that LF, when expressed in normalized units, is a quantitative marker of sympathetic modulations; other studies view LF as reflecting both sympathetic activity and vagal activity. Consequently, the LF/HF ratio is considered by some investigators to mirror sympathovagal balance or to reflect the sympathetic modulations.
Physiological interpretation of lower-frequency components of HRV (that is, of the VLF and ULF components) warrants further elucidation.
It is important to note that HRV measures fluctuations in autonomic inputs to the heart rather than the mean level of autonomic inputs. Thus, both autonomic withdrawal and saturatingly high level of sympathetic input lead to diminished HRV.
Changes of HRV related to specific pathologies
A reduction of HRV has been reported in several cardiological and noncardiological diseases.Myocardial infarction
Depressed HRV after MI may reflect a decrease in vagal activity directed to the heart, which leads to prevalence of sympathetic mechanisms and to cardiac electrical instability. In the acute phase of MI, the reduction in 24-hour SDNN is significantly related to left ventricular dysfunction, peak creatine kinase, and Killip class.The mechanism by which HRV is transiently reduced after MI and by which a depressed HRV is predictive of the neural response to acute MI is not yet defined, but it is likely to involve derangements in the neural activity of cardiac origin. One hypothesis85 involves cardiocardiac sympathosympathetic and sympathovagal reflexes and suggests that the changes in the geometry of a beating heart due to necrotic and noncontracting segments may abnormally increase the firing of sympathetic afferent fibers by mechanical distortion of the sensory endings. This sympathetic excitation attenuates the activity of vagal fibers directed to the sinus node. Another explanation, especially applicable to marked reduction of HRV, is the reduced responsiveness of sinus nodal cells to neural modulations.
Spectral analysis of HRV in patients surviving an acute MI revealed a reduction in total and in the individual power of spectral components.89 However, when the power of LF and HF was calculated in normalized units, an increased LF and a diminished HF were observed during both resting controlled conditions and 24-hour recordings analyzed over multiple 5-minute periods. These changes may indicate a shift of sympathovagal balance toward a sympathetic predominance and a reduced vagal tone. Similar conclusions were obtained by considering the changes in LF/HF ratio. The presence of an alteration in neural control mechanisms was also reflected by the blunting of the day-night variations of RR interval91 and LF and HF spectral components present in a period ranging from days to a few weeks after the acute event. In post-MI patients with a very depressed HRV, most of the residual energy is distributed in the VLF frequency range below 0.03 Hz, with only a small respiration-related These characteristics of the spectral profile are similar to those observed in an advanced cardiac failure or after cardiac transplant and are likely to reflect either a diminished responsiveness of the target organ to neural modulatory inputs82 or a saturating influence on the sinus node of a persistently high sympathetic tone.
Diabetic neuropathy
In neuropathy associated with diabetes mellitus characterized by alteration of small nerve fibers, a reduction in time domain parameters of HRV seems not only to carry negative prognostic value but also to precede the clinical expression of autonomic neuropathy. In diabetic patients without evidence of autonomic neuropathy, reduction of the absolute power of LF and HF during controlled conditions was also reported. However, when the LF/HF ratio was considered or when LF and HF were analyzed in normalized units, no significant difference in comparison to normal subjects was present. Thus, the initial manifestation of this neuropathy is likely to involve both efferent limbs of the autonomic nervous system.Cardiac transplantation
A very reduced HRV with no definite spectral components was reported in patients with a recent heart transplant. The appearance of discrete spectral components in a few patients is considered to reflect cardiac reinnervation. This reinnervation may occur as early as 1 to 2 years after transplantation and is usually of sympathetic origin. Indeed, the correlation between the respiratory rate and the HF component of HRV observed in some transplanted patients also indicates that a nonneural mechanism may contribute to generate a respiration-related rhythmic oscillation.100 The initial observation of identifying patients developing an allograft rejection according to changes in HRV could be of clinical interest but needs further confirmation.Myocardial dysfunction
A reduced HRV has been observed consistently in patients with cardiac failure.In this condition characterized by signs of sympathetic activation such as faster heart rates and high levels of circulating catecholamines, a relation between changes in HRV and the extent of left ventricular dysfunction was reported. In fact, whereas the reduction in time domain measures of HRV seemed to parallel the severity of the disease, the relationship between spectral components and indices of ventricular dysfunction appears to be more complex. In particular, in most patients with a very advanced phase of the disease and with a drastic reduction in HRV, an LF component could not be detected despite the clinical signs of sympathetic activation. Thus, in conditions characterized by a marked and unopposed persistent sympathetic excitation, the sinus node seems to drastically diminish its responsiveness to neural inputs.Tetraplegia
Patients with chronic complete high cervical spinal cord lesions have intact efferent vagal and sympathetic neural pathways directed to the sinus node. However, spinal sympathetic neurons are deprived of modulatory control and in particular of baroreflex supraspinal inhibitory inputs. For this reason, these patients represent a unique clinical model to evaluate the contribution of supraspinal mechanisms in determining the sympathetic activity responsible for LF oscillations of HRV. It has been reported that no LF could be detected in tetraplegic patients, thus suggesting the critical role of supraspinal mechanisms in determining the 0.1 Hz rhythm. Two recent studies, however, have indicated that an LF component also can be detected in HRV and arterial pressure variabilities of some tetraplegic patients. While Koh et al108 attributed the LF component of HRV to vagal modulations, Guzzetti et al109 attributed the same component to sympathetic activity because of the delay with which the LF component appeared after spinal section, suggesting an emerging spinal rhythmicity capable of modulating sympathetic discharge.Modifications of HRV by specific interventions
The rationale for trying to modify HRV after MI stems from the multiple observations indicating that cardiac mortality is higher among those post-MI patients who have a more depressed HRV. The inference is that interventions that augment HRV may be protective against cardiac mortality and sudden cardiac death. Although the rationale for changing HRV is sound, it also contains the inherent danger of leading to the unwarranted assumption that modification of HRV translates directly into cardiac protection, which may not be the case. The target is the improvement of cardiac electrical stability, and HRV is just a marker of autonomic activity. Despite the growing consensus that increases in vagal activity can be beneficial, it is not as yet known how much vagal activity (or its markers) has to increase in order to provide adequate protection.ß-Adrenergic blockade and HRV
The data on the effect of ß-blockers on HRV in post-MI patients are surprisingly scant. Despite the observation of statistically significant increases, the actual changes are very modest. However, it is of note that ß-blockade prevents the rise in the LF component observed in the morning hours. In conscious post-MI dogs, ß-blockers do not modify HRV. The unexpected observation that before MI, ß-blockade increases HRV only in the animals destined to be at low risk for lethal arrhythmias after MI may suggest novel approaches to post-MI risk stratification.Antiarrhythmic drugs and HRV
Data exist for several antiarrhythmic drugs. Flecainide and propafenone but not amiodarone were reported to decrease time domain measures of HRV in patients with chronic ventricular arrhythmia. In another study,propafenone reduced HRV and decreased LF much more than HF, resulting in a significantly smaller LF/HF ratio. A larger study confirmed that flecainide, also encainide and moricizine, decreased HRV in post-MI patients but found no correlation between the change in HRV and mortality during follow-up. Thus, some antiarrhythmic drugs associated with increased mortality can reduce HRV. However, it is not known whether these changes in HRV have any direct prognostic significance.Scopolamine and HRV
Low-dose muscarinic receptor blockers, such as atropine and scopolamine, may produce a paradoxical increase in vagal efferent activity, as suggested by a decrease in heart rate. Different studies examined the effects of transdermal scopolamine on indices of vagal activity in patients with a recent MI and with congestive heart failure. Scopolamine markedly increases HRV, which indicates that pharmacological modulation of neural activity with scopolamine may effectively increase vagal activity. However, the efficacy during long-term treatment has not been assessed. Furthermore, low-dose scopolamine does not prevent ventricular fibrillation caused by acute myocardial ischemia in post-MI dogs.Thrombolysis and HRV
The effect of thrombolysis on HRV (assessed by pNN50) was reported in 95 patients with acute MI. HRV was higher 90 minutes after thrombolysis in the patients with patency of the infarct-related artery. However, this difference was no longer evident when the entire 24 hours were analyzed.Exercise training and HRV
Exercise training may decrease cardiovascular mortality and sudden cardiac death. Regular exercise training is also thought capable of modifying the autonomic balance. A recent experimental study designed to assess the effects of exercise training on markers of vagal activity has simultaneously provided information on changes in cardiac electrical stability. Conscious dogs documented to be at high risk by the previous occurrence of ventricular fibrillation during acute myocardial ischemia were randomly assigned to 6 weeks of either daily exercise training or cage rest followed by exercise training. After training, HRV (SDNN) increased by 74%, and all animals survived a new ischemic test. Exercise training can also accelerate recovery of the physiological sympathovagal interaction, as shown in post-MI patients.Normal values of standard measures of HRV
Variable Units Normal values (mean ± SD)Time Domain Analysis of Nominal 24 hours
- SDNN ms 141 ± 39
- SDANN ms 127 ± 35
- RMSSD ms 27 ± 12
- HRV triangular index 37 ± 15
- Spectral analysis of stationary supine 5-min recording
- Total power ms2 3466 ± 1018
- LF ms2 1170 ± 416
- HF ms2 975 ± 203
- LF nu 54 ± 4
- HF nu 29 ± 3
- LF/HF ratio 1.5–2.0
Sources
- Malik M, Camm A. Heart Rate Variability. Futura Publishing Company, 1995.
External links
- review article on the mechanisms of cardiovascular variability in the Journal of Physiology
- Kardia Open software for HRV analysis
- Specialist of variability Firstbeat Technologie
- French specialist of variability Puls@care
- Online software for Heart Rate Variability Televasc