Review articleFunctional assessment of heart rate variability: physiological basis and practical applications
Introduction
One of the most interesting non-invasive diagnostic methods increasingly used in medicine is analysis of heart rate variability (HRV). Detailed and sophisticated analysis of fluctuation in heart rate can be used to indirectly assess autonomic control of the heart [1], [2], [3], [4], [5]. Change in the HRV pattern provides an early and sensitive indicator of compromised health [6], [7], [8], [9], [10]. A high variability in heart rate is a sign of good adaptability, implying a healthy individual with well functioning autonomic control mechanisms. Conversely, lower variability is often an indicator of abnormal and insufficient adaptability of the autonomic nervous system, implying the presence of a physiological malfunction in the individual for which further investigations are required to yield a specific diagnosis. Simple analysis of variation in heart rate has been used in clinical practice since the early 1960s, with reduced foetal HRV indicating that clinically significant hypoxia may be developing [11]. In the late 1970s, a reduction in HRV was first correlated with increased mortality and arrhythmic events in survivors of myocardial infarction [12]. More recently, reduced HRV has emerged as a strong indicator of risk related to adverse events in normal subjects [7], [13] and patients with a wide range of diseases [14], [15], [16], [17], [18], [19], reflecting the vital role the autonomic nervous system plays in maintaining health. The purpose of this review is to discuss physiological and technical aspects of HRV analysis, along with an overview of the research and clinical applications of the techniques.
Section snippets
Physiological background of HRV analysis
The cardiovascular system displays features typical of self-organising systems designed to achieve dynamical stability [20]. In the case of the cardiovascular system, stability is achieved by autonomically mediated control of heart rate, blood pressure and other factors which react rapidly to a range of internal and external stimuli such as acute ischaemia, metabolic imbalance and changes in physical or mental activity. In particular, heart rate varies in a complex reactive manner to these
Assessment of HRV by cardiovascular reflex testing
Early techniques for analysis of autonomic activity were based on evaluating heart rate changes evoked by stimulation of cardiovascular reflexes. One of the most widely used early sets for investigation of cardiovascular reflexes was proposed by Ewing et al. The Ewing ‘battery’ of tests includes measurement of heart rate changes induced by deep breathing, Valsalva-manoeuvre, orthostatic load and a hand-grip test [39]. The total Ewing score based on the results of the above tests provides a
Time domain analysis of HRV
These methods use mathematically simple techniques to measure the amount of variability present in a pre-specified time period in a continuous electrocardiogram [1], [21], [22], [23], [42]. After editing to remove non-sinus beats and artefact, the remaining normal to normal R–R intervals are measured and subjected to simple statistical analysis. The most commonly used technique is to plot a histogram of R–R interval duration against the number of R–R intervals in a 24-h period and then to
Frequency domain analysis of HRV
It is difficult to obtain precise physiological data about changes in autonomic function using relatively unsophisticated time domain analysis of HRV. Because of this, investigators have invested considerable time and effort in developing alternative techniques to investigate cyclical changes in HRV. Before this type of analysis can be performed, extensive editing and review of the electrocardiogram by an experienced operator is required to remove/edit non-sinus ectopic beats, pauses, tape
Comparison of time and frequency domain techniques for analysis of HRV
Some time and frequency domain HRV measurements are closely related [42]. Indices that measure beat to beat parasympathetically mediated HRV (rMSSD, sNN50 and high frequency power) and measures of the total amount of variability present in a long-term recording, such as SDNN and total spectral power, are strongly correlated. These time and frequency domain indices can therefore be used interchangeably. The HRV technique chosen for a particular study will depend on a variety of different
New analytical techniques
In the last decade a series of complex techniques have been developed to provide additional information over and above that available from standard time and frequency domain analysis of HRV. Investigators have recently reported on new time domain techniques that provide some information on sympathetic activity [57], [58], [59]. The techniques of peak — through analysis, complex demodulation and acceleration–deceleration oscillation analysis, are closely related and based on similar principles.
Practical applications of HRV analysis
In the last two decades, analysis of HRV has been extensively applied to the investigation of normal physiology. Prior to the HRV era, investigation of autonomic physiology required the use of complex highly invasive techniques in animal models or imprecise reflex based tests in humans. The use of HRV analysis has provided a simple reproducible method of non-invasive autonomic assessment. This has helped to clarify the role of the autonomic nervous system in regulating the cardiovascular
Conclusions
The autonomic nervous system plays a major role in normal physiological function and in the pathogenesis of many medical disorders. Measurement of HRV provides an easily applied non-invasive method of assessing autonomic function. Time domain techniques are mathematically simple and easy to apply to clinical quality ambulatory electrocardiograms. Frequency domain techniques are more complex and technically demanding, but provide more physiological information. Recent advances in computing hold
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