Heart rate variability

From Wikipedia, the free encyclopedia

This article does not cite any references or sources. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. (February 2009)

Heart rate variability (HRV) is a measure of variation in heart rate. This term has become widely accepted though in practice, one usually measures the variation in the beat-to-beat interval rather than the variation in the instantaneous heart rate.

Other terms used in the literature 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), "heart period variability", "RR variability" and "RR interval tachogram".

There are several methods for detecting beats including ECG, blood pressure, or pulse wave signal derived from a photoplethysmograph (PPG). ECG is considered superior because it provides the best waveform, which makes it easier to exclude heartbeats not originating in the SA node. NN is used in place of RR to emphasize the fact that the processed beats are "normal" beats.

Contents 1 Clinical significance 2 Variation 3 HRV analysis 3.1 Time-domain methods 3.2 Frequency-domain methods 3.3 Non-linear methods 4 Sources

[edit] Clinical significance

Reduced HRV has been shown to be a predictor of mortality after myocardial infarction ^[1][2].

A range of other outcomes/conditions have also been shown to be associated with a modified (usually lower) HRV, including congestive heart failure, diabetic neuropathy, depression post-cardiac transplant, susceptibility to SIDS and poor survival in premature babies.

[edit] Variation

Although counter-intuitive to many, 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 is the sum of these inputs. .

The main inputs are the Sympathetic nervous system and the Parasympathetic nervous system, the two branches of the Autonomic nervous system.

Other factors that affect the input are the baroreceptor reflex, thermoregulator, hormones, sleep-wake cycle, meals, stress…

[edit] 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.

Roughly speaking, time-domain methods answer the question 'how much variability is there' while frequency-domain methods answer the question 'how is variability caused?'."

[edit] 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 are a subclass of time-domain measures in which the NN intervals are converted to a geometric pattern, then analyzed. Most of these methods use a discrete scale for the NN interval length.

Measures based on geometric methods include the HRV triangular index and the triangular interpolation of NN (TINN) interval histogram.

[edit] Frequency-domain methods

Several methods are available. Power spectral density, using parametric or nonparametric methods, provides basic information of the power (variation) distribution across frequencies. One of the most commonly used PSD methods is the Fast Fourier transform.

Frequency-domain methods are preferred for short-term recordings; normally five-minute recordings are used.

Several frequency bands of interest have been defined in humans.

• High Frequency band (HF) between 0.15 and 0.4 Hz. HF is driven by respiration and appears to derive mainly from vagal activity (parasympathetic nervous system).

• Low Frequency band (LF) between 0.04 and 0.15 Hz. LF derives from both parasympathetic and sympathetic activity and has been hypothesized to reflect the delay in the baroreceptor loop.

• Very Low Frequency band (VLF) band between 0.0033 and 0.04 Hz. The origin of VLF is not well known, but it had been attributed to thermal regulation of the body's internal systems.

• Ultra Low Frequency (ULF) band between 0 and 0.0033 Hz. The major background of ULF is day–night variation and therefore is only expressed in 24-hour recordings.

• The ratio of low-to-high frequency spectra power(LF/HF) is has been proposed as an index of sympathetic to parasympathetic balance of heart rate fluctuation, but this is controversial because of the lack of understanding of the mechanisms for the LF component.

[edit] 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.

The most commonly used non-linear method of analysing heart rate variability is the Poincaré plot. Each data point represents a pair 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 ^[3]. For example, after fitting an ellipse and plotting 2 axes (perpendicular to each other), one can calculate the standard deviation of the distance of the points from each axis. The SD1 value reflects short-term variability while SD2 reflects long-term variability.

[edit] Sources

• Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology. Heart Rate Variability Standards of Measurement, Physiological Interpretation, and Clinical Use . Circulation. 1996:1043-1065.

• Malik M, Camm A. Heart Rate Variability. Futura Publishing Company, 1995.