Heart Rate Variability (HRV)

Heart Rate Variability (HRV) evaluates the balancing act between the sympathetic nervous system (fight and flight) and the parasympathetic nervous system (rest and digest). An imbalance in HRV is the #1 risk factor for sudden cardiac death. The simple hand electro-sensor test shows you a report on the balance between your heart and nervous system in minutes.


Heart Rate VariabilityHeart Rate Variability analysis has acquired exceptional popularity over the last few years as one of the most effective predictors of nonspecific health risk. Scientific and clinical studies have established its usefulness in almost all branches of medicine. Level 1 Diagnostics QHRV is a noninvasive, fully automated computer-based system that provides Heart Rate Variability (HRV) and Pulse Wave Velocity (PWV) analysis for a quantitative assessment of the Autonomic Nervous System (ANS) and autonomic balance (sympathetic and parasympathetic).

Heart rate variability (HRV), or the beat-to-beat alterations in heart rate, is an accurate and reliable reflection of the many physiological factors modulating the normal rhythm of the heart. In fact, HRV provides a powerful means of observing the interplay between the sympathetic and parasympathetic Autonomic Nervous Systems (ANS).

The Autonomic Nervous System (ANS) plays an important role, not only in physiological situations, but also in various pathological settings such as diabetic neuropathy, myocardial infarction (MI) and congestive heart failure (CHF). HRV has a high association with the risk for sudden cardiac death, and arrhythmic complications.

 The QHRV test also offers the possibility of Accumulative Physical and Mental Stress Assessment.  Chronic physical stress and accumulative mental stress are conventional health risk factors, triggering the development of life threatening specific diseases. The Mental Stress Index represents the body’s adaptability to internal and external stressors that are placed on the body every day.  Mental Stress Index indicates the function of the ANS.  This represents the level of stress the body is experiencing at the present time. If the stress resistance is low it can lead to physical problems and disease.  The Physical Stress Index represents the fatigue or activity level of the body from a cellular level.

The HRV Process

The HRV test consists of two main components: a small EKG sensor with a pulse wave sensor and the accompanying analysis software.  A five-minute recording of HRV is all that is necessary to quickly create an accurate assessment of the status
of the sympathetic and parasympathetic branches of the Autonomic Nervous System.

The sensor transmits the collected data to the PC for processing. The software uses advanced technology of recording and interpreting HRV signals in order to derive heart rate data. This heart rate data is used to ascertain the current state of inner balance and self-regulatory activity.

The software and analyses are intuitive, easy-to-use and designed for success in the hands of a healthcare practitioner. Simple hardware and standard computer requirements ensure the QHRV test transitions seamlessly into virtually every health practice.


  • FDA cleared
  • Designed by a unique team of scientists and medical doctors with software engineering skills, the QHRV testing is of great value as a preventive healthcare tool.
  • The easy to understand report was developed and written by Dr. Steven Helschien, an expert in this field.
  • Quick and reliable.
  • Measurements of HRV are noninvasive and highly reproducible.
  • Detects arteriosclerosis (hardening of the arteries), or loss of arterial elasticity, blood circulation status, the relative age (biological age) of blood vessels, and disturbances in the smaller blood vessels not found when measuring blood pressure with a cuff.
  • Assesses cardiovascular health, management of disease progression, and the effects of medication, therapies, lifestyle changes and dietary habits.


Dantest is the global leader in the development, manufacturing and marketing of Heart Rate Variability / Pulse Wave Velocity / Autonomic Nervous System products and the manufacturer of Level 1 Diagnostics QHRV test equipment. Dantest develops biomedical software and hardware products designed to monitor physiology for research and educational purposes.

The Simple Explanation

HRV evaluates the balancing act between the sympathetic nervous system (fight and flight) and the parasympathetic nervous system (rest and digest). An imbalance in HRV is the #1 risk factor for sudden cardiac death.

Heart Rate Variability (HRV), as monitored from an individual’s heart rhythm, is the most powerful indicator of both cardiovascular health and general well-being*.

HRV testing is a prognostic (predictive) indicator of cardiac condition, fitness, stress levels, aging, health risk levels, chronic disease condition and more. HRV training can result in enhanced health and wellness, as well as an increase in attention, concentration and short term/working memory.

*The 1994 Framingham Heart Study identified increased Heart Rate Variability (HRV) as the only common factor that was found in all healthy individuals.

The Detailed Explanation

Heart rate variability (HRV) is defined as changes in the duration of consecutive cardiac cycles (heartbeats). Cardiac cycles may be measured by electrocardiography or electrocardiogram (ECG or EKG). On the ECG, the pattern of a cardiac cycle has four major parts: a P wave (which represents the electrical vector spreading from the right atrium to the left atrium during atrial depolarization), a QRS complex (which represents depolarization of the right and left ventricles), a T wave (which represents repolarization of the ventricles), and a U wave (which represents repolarization of the papillary muscles). HRV is measured as the variation in duration between the R peaks on the QRS complexes between consecutive cardiac cycles. Other names for HRV include RR variability, RR period, cycle length variability, and heart period variability.

The autonomic nervous system (ANS) controls heart rate, HRV, and involuntary functions such as breathing. HRV reflects the complex autonomic controls of heart rate. Thus, HRV measurements contain more information than measurements of heart rate alone.

HRV was first described in 1847, when respiration (breathing) was noted to affect HRV by increasing heart rate during inspiration (breathing in) and decreasing during expiration (breathing out). The clinical significance of HRV was realized in 1963, when researchers showed that just before fetal death, changes in beat-to-beat length were detectable before changes in the heart rate itself.

In 1987, HRV was reported to have prognostic value when decreased HRV was found to correlate with decreased survival (increased mortality) in myocardial infarction (MI or heart attack) patients. Because numerous studies have demonstrated a link between HRV and poor prognosis after MI, HRV measurements are widely accepted for predicting risk of future cardiac events in heart attack survivors.

HRV is also strongly associated with arrhythmias (abnormal heart rate), sudden cardiac death, and all-cause mortality in cardiovascular diseases in general. Sudden cardiac death due to ventricular arrhythmia is a leading cause of mortality in the United States, accounting for up to 500,000 deaths each year. Because measures of HRV are easily obtained non-invasively, HRV is gaining favor as a method of assessing autonomic function in routine clinical practice.

HRV has been used to screen candidates for implantable cardioverter-defibrillator (ICD) devices that may help control arrhythmias and prevent sudden cardiac death. However, the usefulness of HRV in screening ICD candidates has not been shown conclusively.  Though most of the findings thus far are promising, additional evidence is needed to support the use of HRV (alone or with other cardiac risk measurements) in predicting sudden cardiac death in various cardiac conditions, including non-ischemic cardiomyopathy. HRV may also be altered in numerous non-cardiovascular conditions and neuropathies. Thus, HRV has been suggested as a plausible indicator in risk assessment for a number of cardiovascular and neurological diseases. Improving the diagnostic and prognostic value of HRV may require further optimizing its measurement techniques for specific conditions.

Contributing Factors

  • Heart rate variability (HRV) is controlled by the autonomic nervous system (ANS), also known as the visceral nervous system. The ANS is part of the peripheral nervous system (PNS). The nerves in the PNS connect various organ systems to the central nervous system (CNS), which includes the brain and spinal cord. The ANS functions at the subconscious level. In addition to controlling heart rate, it controls bodily functions such as sweating, digestion, and breathing. Because the autonomic control of heart rate can reveal abnormal changes in physiological functions, HRV may be very useful in making diagnostic, prognostic, and therapeutic determinations.
  • In addition to pathological (disease) conditions, there are a number of physiological factors in healthy individuals that may affect heart rate variability (HRV). While some of these factors (such as age and genetic makeup) cannot be controlled by individuals, other factors such as lifestyle choices (such as physical activity, smoking, and other lifestyle choices) are modifiable. Therefore, many  lifestyle choices may affect HRV and its role in disease outcome.

Physiological Factors:

  • Breathing: Respiration (breathing) was the first physiological factor noted to affect HRV. While it is not entirely clear exactly how breathing affects HRV, evidence from research conducted in canines suggests that an autonomous pulmonary reflex  known as the Bainbridge reflex may be involved. Cardiac reflexes, as well as respiratory activities (such as rib cage movement) controlled by central nervous system (CNS), may also contribute to HRV.
  • Circadian rhythm: The circadian profile of HRV has been studied in healthy men and women, and was demonstrated to have a distinct day-night pattern that peaked at night and plateaued during the day.
  • Posture: In healthy subjects, rising from a supine (lying down) position to the upright (standing up) position increases resting heart rate and decreases the frequency of HRV. In the European Project on Genes in Hypertension (EPOGH) study, HRV was found to consistently vary according to posture, independently of other factors.

Non-modifiable factors:

  • Age: While it remains unclear whether resting heart rate varies with increasing age, it has been firmly established that maximal heart rate becomes lower as individuals grow older. Age is known to affect autonomic control of the cardiovascular system, and is a primary factor that may affect HRV. In the European Project on Genes in Hypertension (EPOGH) study, HRV was found to consistently vary with age.
  • Gender: Females, under age 30, tend to have lower HRV than age-matched males. Gender differences in HRV begin to disappear at age 30 and disappear by age 50. This may be because sympathetic activity tends to decline more slowly with age in males than females.
  • Genetics: Genomic evidence from the Framingham Heart Study (a large multigenerational cohort study that began in 1948) strongly suggests that heart rate and HRV characteristics may be inherited and shared over multiple generations. The genes that appear to be involved include those that control the ANS and certain neural responses (such as those mediated by the cholinergic system).

Modifiable lifestyle factors:

  • Physical activity: The ANS is known to control heart rate changes due to physical activity. Regular physical activity decreases heart rate during both rest and exercise in humans. It is still not exactly clear how regular physical training affects HRV. However, in several studies conducted in canines, endurance training (treadmill running) increased HRV and lowered risk for sudden cardiac death due to arrhythmia.
  • Smoking: Smoking is known to adversely affect the cardiovascular system in part by increasing heart rate and reducing HRV. This effect has also  been demonstrated in humans and animals exposed to second-hand tobacco smoke, as well as in infants of smoking mothers.

Other factors

  • Medications: Various medications, particularly those with anticholinergic effects (including tricyclic antidepressants and antispasmodics), are known to reduce HRV. Moreover, stimulants (such as caffeine and nicotine) increase heart rate and decrease HRV. Atenolol (a beta-antagonistic drug) has been shown to reduce HRV while losartan (angiotensin II receptor antagonist) increases HRV.
  • Pollution: Small-particulate air pollution and second-hand cigarette smoke have both been shown to either directly or indirectly affect the ANS. This is supported by studies in animals and humans that have associated increased heart rate and decreased HRV with an increased risk of cardiovascular disease and related deaths.


  • Unlike simple heart rate, which does not need sophisticated technology or significant time to measure, heart rate variability (HRV) measurements involve special devices, statistical analysis, and continuous monitoring (often 24 hours or longer).
  • HRV is generally measured using electrocardiography (ECG or EKG). The electrocardiogram represents the cardiac cycle as a wave with four major parts: a P wave, a QRS complex, a T wave, and a U wave. HRV is measured as the variation in duration between the R peaks on the QRS complexes over consecutive cardiac cycles. The variability of the RR interval may be measured in various ways, usually using time or frequency domain methods. Newer methods of analysis have also been developed.
  • Time domain methods: The simplest measures of HRV are based on time domain methods, which determine the intervals of cardiac cycles. On an ECG recording, this is usually measured as the normal-to-normal (NN) interval between QRS complexes. The instantaneous heart rate may also be determined. Variation is then calculated as the difference in NN intervals (cycle length) or heart rate. These differences may then be calculated statistically as the standard deviation of NN intervals (SDNN). Typical recording times for statistical analysis are 24 hours, but short-term recordings of five minutes may also be used. The NN intervals may also be analyzed using geometric or fractal techniques by converting them into geometric patterns. Compared to statistical analysis, geometric analysis is more accurate if NN interval measurements are of low quality. However, because many NN intervals are needed for conversion into geometric patterns, fractal or geometric methods are not appropriate for analyzing shorter recordings (less than 20 minutes) and usually require recording times of 24 hours or more.
  • Frequency domain methods: HRV may be studied in the frequency domain by converting heart rate (time domain) to a power spectrum (frequency domain) using a mathematical algorithm called the Fourier transformation. High frequencies (over 0.15 Hz) indicate respiratory sinus arrhythmia, while lower frequencies reflect autonomic (sympathetic and parasympathetic) factors. Reductions in frequency occur in patients with autonomic dysfunction, such as diabetic neuropathy. Frequency domain measures of HRV are more difficult to perform than time domain analyses. However, for continuous recordings of longer duration (such as 24 hours), time and frequency domain measurements are highly correlated.Heart rate variability with deep breathing: Deep breathing amplifies HRV, and combining HRV with deep breathing (HRVdb) is a very sensitive method of measuring ANS function. HRVdb methods correlate HRV with respiratory cycles,and usually measure the mean heart rate range (MHRR) and the expiratory-to-inspiratory ratio (E:I).  HRVdb has been used reliably in autonomic function tests in various autonomic disorders, including neuropathies, neurodegenerative disorders, and autonomic failure.
  • Deceleration capacity: A relatively new method of analyzing heart rate dynamics measures HRV associated with decreasing (decelerating) but not increasing (accelerating) heart rate. This method is thought to specifically measure cardiac vagal tone, which comprises vagus nerve impulses that inhibit heartbeat. In a blind multicenter clinical study, altered deceleration capacity was shown to be a more powerful and accurate predictor of death after myocardial infarction. Photoplethysmography (PPG): The plethysmogram waveform represents pulsatile peripheral blood flow, which reflects both peripheral and central hemodynamics. PPG uses infrared light transmitted through the skin to noninvasively measure hemodynamic parameters, and is thus a useful measure of vascular dysfunction and heart rate variability. The accuracy of fingertip PPG for measuring HRV has been shown to be comparable to ECG, at least at rest.


  • There is a large body of evidence linking altered heart rate variability (HRV) with mortality, particularly in deaths due to arrhythmia. Numerous studies have demonstrated a link between HRV and poor prognosis after myocardial infarction (MI or heart attack). Therefore, HRV measurementsare widely accepted in for predicting future complications and mortality in MI survivors.
  • A landmark study in 1987 tested the hypothesis that HRV may predict long-term survival after MI, and found that decreased HRV was strongly correlated with mortality after acute MI. Data reported in 1996 from the Framingham Heart Study found that in this large community-based study population, decreased HRV correlated significantly with increased risk of major cardiac events at a mean follow-up of 2.5 years, even after adjusting for other known cardiovascular risk factors. Subsequently, both the TRAndolapril Cardiac Evaluation (TRACE) study and the Autonomic Tone and Reflexes After Myocardial Infarction (ATRAMI) study provided additional evidence that decreased HRV is linked with increased mortality after MI.
  • For non-ischemic cardiomyopathies, there are conflicting reports of association between reduced HRV and poor prognosis.However, in valvular heart diseases (such as chronic mitral regurgitation), lower HRV appears to predict future cardiac events. There is also evidence that reduced HRV may predict postoperative cardiac complications, which account for over half of postoperative sudden cardiac deaths (cardiac arrests).
  • There are indications that decreased HRV reflects autonomic disturbances, which may in turn predispose patients to ventricular fibrillation. Decreased HRV has also been shown to correlate with increased inflammatory markers, such as interleukin-6 (IL-6) and C-reactive protein (CRP), which are associated with increased risk of adverse cardiac events. In a prospective cohort study, autonomic dysfunction (indicated by reduced HRV) and increased inflammation preceded sudden cardiac death in chronic heart failure patients.
  • In a study involving 202 patients with severe chronic heart failure, short-term HRV was found to be a strong predictor of sudden cardiac death. This correlation has also been demonstrated in a random sample of 325 elderly subjects, in which fractal analysis of HRV strongly predicted cardiac death over a period of 10 years.
  • The prognostic value of HRV for sudden cardiac death may be improved by combining HRV measure with other parameters, such as heart rate turbulence and neurohormonal activation.
  • HRV is also altered in a number of non-cardiac diseases, including brain damage, depression, diabetes, diabetic neuropathy, end-stage renal disease, epilepsy, Guillain-Barré syndrome, schizophrenia, and uremic neuropathy. Many of these diseases carry an increased risk of sudden cardiac death. Therefore, monitoring HRV has been considered for the prevention of sudden cardiac death in these conditions.


  • Heart rate variability (HRV) is strongly correlated with fatal arrhythmias and sudden cardiac death. Therefore, it has been used to screen candidates for implantable cardioverter-defibrillator (ICD) placement. Although HRV measurements are non-invasive and may provide useful prognostic information, it may not be safe to select patients for therapy based on HRV measurements alone.
  • In the Defibrillator in Acute Myocardial Infarction Trial (DINAMIT), altered HRV was used to select candidates for ICD placement in survivors of acute myocardial infarction (MI or heart attack). Although there were fewer deaths among ICD patients than in non-ICD patients, this decreased mortality was offset by more deaths from nonarrhythmic causes. In the AzimiLide post Infarct surVival Evaluation (ALIVE) trial, stratifying (ranking) patients according to HRV also did not affect mortality in patients treated with azimilide (an antiarrhythmic drug). This may be because HRV has not yet been optimized for predicting mortality from non-arrhythmic effects of drugs.

Author Information

  • This information was compiled and reviewed by Dr. Steven M. Helschien and then was edited and peer-reviewed by contributors to the Natural Standard Research Collaboration (www.naturalstandard.com).

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