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HRV - DANTEST
Introduction
http://www.dantest.com/
Heart Rate Variability (HRV)
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).
HRV is also of great value in determining the degree of progress in many clinical diseases (for
example, diabetes, hypertension, thyreotoxicosis, leukemia, different types of oncological diseases,
etc.). For this reason, HRV has escalated in use as one of the best diagnostic instruments in
contemporary medicine. The practical application of the method, in ecological and professional
aspects, requires software and hardware facilitation. Dantest products encompass these theoretical
and clinical studies with a proven methodology for patient monitoring, tracking and assessment.
In the last 30 years, HRV has received increasing attention as a forecast indicator of health risks
related to chronic diseases, morbidity rates, mortality, and aging. Today, the medical community
largely considers HRV as one of the most reliable indicators of Nonspecific Adaptation Deficit (NAD).
The NAD Concept
The Nonspecific Adaptation Deficit (NAD) concept was created and developed by Prof. Dr. Svetoslav
Danev, Doctor of Medical Science alongside a medical team of associated doctors. According to the
concept, life-threatening diseases are preceded by certain nonspecific changes. These changes
include depletion of the capacity for adaptation to unfavorable changes in the external or internal
environment. The increased requirements and the decreased capacity for adaptation create a
vicious cycle from which the only exit is lethal disease and death. In terms of physiology, the NAD
concept is based on decreased work efficiency of the negative back connectors, which play a major
role in the regulatory activities of the centers for coordination and regulation of basic life processes.
Autonomic Nervous System (ANS)
The Autonomic nervous system is extensive and is involved in the function of every organ system.
Clinical manifestations of autonomic dysfunction are involved virtually in all diseases. The structural
pathologic process affecting brain whether infectious, degenerative, neoplastic or inherited may
result in autonomic syndrome.
In recent years, ANS/HRV has successfully been used to assess the negative influence of a wide
spectrum of stressors including environmental pollution, dietary problems, psycho-social discomfort,
and different behavioral disorders. Dantest monitoring has been developed according to the
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standards and mathematical procedures for short-term HRV Autonomic nervous system (ANS)
analysis as well as for performing and evaluating pulse flow and autonomic challenge tests.
Pulse Wave Velocity (PWV)
Pulse wave is a physiological phenomenon, observable and measurable in the arterial system during
blood circulation. During one heart systole a certain blood volume is expelled. This propagates
through the arteries due to the reciprocal transformation between kinetic energy of a segment of
the expelled blood volume and the potential energy of a stretched segment of the resilient vascular
wall. We can observe the changes in pressure, blood flow, velocity and profile throughout the whole
pulse wave. It can be used for classification of the artery elasticity.
The condition of the small and large arteries is key to prevention and diagnosis of cardio-vascular
related illness. In particular, the stiffness and augmentation of the major arteries is a strong
indication of potential health problems including heart attacks, heart failure, sclerosis, and renal
complications. PWV Analysis and arterial stiffness indexes (EEI, DDI and DEI) can suggest to
healthcare professional to begin appropriate treatment long before the symptoms or clinical signs
appear.
Age and systolic pressure strongly correlate with PWV. In fact, the most important factor
contributing to increase in PWV is age because of increased arterial stiffness caused by medial
calcification and loss of elasticity. The measurement of pulse wave velocity is useful in the study of
the effects of aging, vascular diseases, vaso-dilating and vaso-constricting agents on arteries.
Dantest Pulse Wave Velocity measurement is a convenient method of quantifying arterial stiffness
and augmentation. PWV provides invaluable insight into cardiovascular health, management of
disease progression and monitoring the effects of medication, treatments, lifestyle and dietary
habits.
ANS/HRV In Different Medical Areas
Cardiology and cardiovascular diseases
A reduction of vagal tone is found to be associated with acute myocardial infarction. HRV can be
used as a prognostic tool. HRV has a high association with the risk for sudden cardiac death, and
arrhythmic complications. Diminished vagal activity is found in patients with coronary artery disease
and essential hypertension. After heart transplantation the allograft rejection can be predicted by
decreased total spectral power.
Neurology
HRV reflects autonomic dysfunction of central origin in patients with Parkinsonism, spinocerebellar
degeneration, Shy-Drager syndrome, multiple sclerosis, chronic alcoholism, Guillan-Barre syndrome,
quadriplegia etc.
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Diabetes mellitus
Diabetic cardio-miopathy is substantially results in decreasing HRV. As this decrease is often
preceding clinical symptoms, HRV can be used for early prediction of the diabetic pathology,
especially in children.
Glomerulonephrites with renal insufficiency
Decrease of vagal tone was found in uremic patients, revealed namely by the diminution of the short
waves-associated spectral power of the HRV analysis
Pharmacological influence
Calcium channel blockers, beta-blockers, tranquilizers, relaxants, scopolamine (vagomimetic), etc.
are increasing the time as well as the frequency-domain HRV measures. Contrarily, atropine is
decreasing vagal activity. It is interesting to note, that nifidipine (Ca-blocker) has no effect upon HRV.
Toxicology
HRV analysis can reveal the severity of autonomic dysfunction caused by environmental neurotoxin
agents as organic solvents, pesticides, nitrates, organic phosphates, leads etc.
Work-related stress
Vibratory tool operations, inconvenient regimes of work and rest, dust of different kinds,
ergonomical disadvantages, overload, bad psychological micro-climate etc. can decrease HRV. This is
used for their quantitative assessment and control.
Medical ecology
Ecological hazard needs to be evaluated not only by measuring of the level of ecological noxes, but
also by the impact they have upon common functional status of the population living in ecologically
contaminated areas. This can be done by examining the chronically increased sympathetical tone by
HRV measurements.
Sports and Fitness
The status of overtraining as well as the effect of relaxation procedures and the use of forbidden
medications can be successfully controlled by HRV.
Applied psychology
By multiple step regression analysis is found that phenomena as depression, burnout, lack of social
support, uncontrolled locus of control, bad family or social relations etc. are increasing the long
waves spectral power and decreasing the total spectral power.
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Unconventional medical treatments
The effect of manual therapy, traditional Chinese therapies, aromatherapy, massages, sauna, auto
gene training, yoga, Silva method etc. is difficult to be assessed without following their impact upon
common functional status, which is reflected by HRV.
Transport, army and cosmic medicine
All these professional activities presuppose a high level of health reserves and adaptation capacities.
It was found, that the physical as well as the mental effort required in these cases can be reliably
evaluated by HRV measurement.
Health (life) insurance
Recently some attempts to use HRV as a predictor of overall health risk as a factor influencing
insurance conditions are carried out in Norway and Japan.
Heart Rate Variability Analysis
Heart rate variability (HRV) is a measure of variations in the heart rate. It is usually calculated by
analyzing the time series of beat-to-beat intervals from ECG or arterial pressure tracings.
Various measures of heart rate variability have been proposed, which can roughly be subdivided into
time domain, frequency domain and non-linear measures. HRV is regarded as an indicator of the
activity of autonomic regulation of circulatory function. It also regarded as the definitive method of
analyzing the activity of the autonomic nervous system. Alteration (mostly reduction) of HRV has
been reported to be associated with various pathologic conditions like hypertension, hemorrhagic
shock, and septic shock. It has found its role as a predictor of mortality after an acute myocardial
infarction.
TIME DOMAIN
A simple example of a time domain measure is the calculation of the standard deviation of beat-tobeat intervals. Other time domain measures include root mean square of the differences between
heart beats (rMSSD), NN50 or the number of normal to normal complexes that fall within 50
milliseconds, and pNN50 or the percentage of total number beats that fall with 50 milliseconds.
SDNN has been strongly corelated to overall variability, while rMSSD relates to the parasympathetic
nervous system activity on heart rate.
FREQUENCY DOMAIN
A common frequency domain method is the application of the discrete Fourier transform also
known as the Fast Fourier transform, to the beat-to-beat interval time series. That expresses the
amount of variation for different frequencies. Several frequency bands of interest have been defined
in humans.
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High Frequency band (HF) between 0.15 and 0.4 Hz. HF is driven by respiration and appears to
derive mainly from vagal activity or the parasympathetic nervous system.
Low Frequency band (LF) between 0.04 and 0.15 Hz. LF derives from sympathetic activity and has
been hypothesized to reflect the delay in the baroreceptor loop. This delay is attributed to the
sympathetic systems use of a second messenger system known as the cyclic AMP (cAMP) system.
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..
In the last few years HRV acquired an extreme popularity in almost all branches of contemporary
medicine, including in the area of prevention. One of the creators of this new trend is Prof. Dr.
Svetoslav Danev, who proved that the unfavorable changes in HRV could be used as a predictor of
wide range of life-threatening diseases, including carcinosis (the extensive spread of cancer
throughout the body). This was determined in the course of a long-year cohort research and
monitoring.
Since HRV reflects most directly the balance in the two branches of the Autonomic nervous system –
sympathic and parasympathic (vagus), this triggered the creation of a new important bio-constant –
the so called vegetative equilibrium. It has a wide application not only in the prevention, but also in
other branches of medicine.
From a mathematical perspective, HRV reflects the regularity of the heart beat activity - increased
regularity corresponds to decreased heart rate variability, and vice versa. The heart rate variability is
derived from the difference in time intervals elapsed between two consecutive heartbeats, called
cardiointervals (R-R intervals) and measured in milliseconds (ms). The cardiointervals are received
from the ECG signal, as it is demonstrated on the figure bellow.
ECG is electrocardiogram, the QRS complexes correspond to heartbeats, and R-R 1 and R-R 2 are
cardiointervals.
The increased sympathicus activity (tone) results in a decreased HRV, and vice versa – the increased
parasympathicus activity increases the HRV.
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Statistically important correlation has been discovered between the HRV parameters and other basic
clinical and paraclinical investigations and researches. This proved the existence of an important
relation between the results obtained by Dantest and certain clinical, laboratory, physiological, and
psychological examinations. Dantest, however, has the advantage of higher informativeness and
easier practical application and execution.
HRV does not reflect the exact diagnosis, but rather the nonspecific anterior health risk in
percentage (prior to the development of the disease process), since HRV measures the
qualitative/numerical levels of stress and training, both of which are major risk factors. Chronically
increased levels of health risk (for a time period longer than few months) can result in progress of
serious diseases. Many scientific research papers and reports have been published on the topic of
the reliability of HRV application in different branches of medicine – as described in the “HRV IN
DIFFERENT MEDICAL AREAS” section.
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). Autonomic imbalance associating increased sympathetic activity and
reduced vagal tone has been strongly implicated in the pathophysiology of arrhythmogenesis and
sudden cardiac death.
Among the different available noninvasive techniques for assessing the autonomic status heart rate
variability (HRV) has emerged as a simple, noninvasive method to evaluate the sympathovagal
balance at the sinoatrial level. It has been used in a variety of clinical situations including diabetic
neuropathy, MI, sudden death and CHF.
The standard measurements intervening in the analysis of HRV comprise time domain indices,
geometric methods and components of the frequency domain. The use of long or short-term
recordings depends on the type of study that has to be realised.
Established clinical data based on numerous studies published during the last decade consider
decreased global HRV as a strong predictor of increased all-cause cardiac and/or arrhythmic
mortality, particularly in patients at risk after MI or with CHF.
This article reviews the mechanism, the parameters and the use of HRV as a marker reflecting the
activity of the sympathetic and vagal components of the ANS on the sinus node, and as a clinical tool
for screening and identifying patients particularly at risk for cardiac mortality.
In the course of the last two decades numerous studies with both animals and human beings have
shown a significant relationship between the ANS and cardiovascular mortality, particularly in
patients with MI and CHF. Perturbations of the ANS and its imbalance consisting of either increased
sympathetic or reduced vagal activity may result in ventricular tachyarrhythmias and sudden cardiac
death, which is nowadays one of the leading causes of cardiovascular mortality. There are presently
various methods available for assessing the status of the ANS, which include cardiovascular reflex
tests, and biochemical and scintigraphic tests. Techniques giving direct access to receptors at the
cellular level or to neural traffic are not routinely available. In recent years noninvasive techniques
based on the electrocardiogram (ECG) have been used as markers of autonomic modulation of the
heart, these include HRV, baroreflex sensitivity (BRS), QT interval, and heart rate turbulence (HRT), a
new method based on fluctuations of sinus rhythm cycle length after a single premature ventricular
contraction. Among these techniques analysis of HRV has emerged as a simple, noninvasive method
to evaluate the sympatho-vagal balance at the sinoatrial level.
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The autonomic nervous system and the heart
Although automaticity is intrinsic to different cardiac tissues with pacemaker properties, the
electrical and contractile activity of the myocardium is largely modulated by the ANS. This neural
regulation is effected through the interplay of the sympathetic and vagal outflows. In most
physiological conditions the efferent sympathetic and parasympathetic branches have opposing
actions: the sympathetic system enhances automaticity, whereas the parasympathetic system
inhibits it. While the effect of vagal stimulation on the cardiac pacemaker cells is to cause
hyperpolarisation and to reduce the rate of depolarisation, sympathetic stimulation causes
chronotropic effects by increasing the rate of pacemaker depolarisation. Both branches of the ANS
influence ion channel activity implicated in the regulation of depolarisation of the cardiac pacemaker
cells.
Abnormalities of the ANS have been demonstrated in diverse conditions such as diabetic neuropathy
and coronary heart disease, particularly in the context of MI. A dysregulation in the autonomic
nervous control of the cardiovascular system associating increased sympathetic and reduced
parasympathetic tone plays an important role in coronary artery disease and in the genesis of lifethreatening ventricular arrhythmias. The occurrence of ischemia and/or myocardial necrosis may
induce a mechanical distortion of the afferent and efferent fibers of the ANS due to changes in the
geometry related to necrotic and noncontracting segments of the heart. A newly recognised
phenomenon is the electrical remodeling due to local nerve growth and degeneration at the level of
the myocardial cell in the setting of ischemia and/or myocardial necrosis. Taken as a whole, in
patients with coronary artery disease and a history of MI, cardiac autonomic function associating
increased sympathetic and decreased vagal tone are conditions favourable to the complex
phenomenon of life threatening arrhythmias because they modulate cardiac automaticity,
conduction and importantly haemodynamic variables.
Definition and mechanisms of heart rate variability
Heart rate variability is a noninvasive electrocardiographic marker reflecting the activity of the
sympathetic and vagal components of the ANS on the sinus node of the heart. It expresses the total
amount of variations of both instantaneous HR and RR intervals (intervals between QRS complexes
of normal sinus depolarisations). Thus, HRV analyses the tonic baseline autonomic function. In a
normal heart with an integer ANS, there will be continuous physiological variations of the sinus
cycles reflecting a balanced sympthovagal state and normal HRV. In a damaged heart that has
suffered from myocardial necrosis, the changes in activity in the afferent and efferent fibers of the
ANS and in the local neural regulation will contribute to the resulting sympathovagal imbalance,
reflected by a diminished HRV.
Measurements of heart rate variability
Analysis of HRV consists of a series of measurements of successive RR interval variations of sinus
origin which provide information about autonomic tone. Different physiological factors may
influence HRV, such as gender, age, circadian rhythm, respiration and body position. Measurements
of HRV are noninvasive and highly reproducible. Most Holter apparatus manufacturers nowadays
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recommend HRV analysis programs which are incorporated into their instrument systems. Although
computer analysis of tape recordings has improved, human intervention is required in most
measurements of HRV parameters in order to detect erroneous beats, artifacts, and alterations in
tape speed that may alter timing intervals.
In 1996 a Task Force of the European Society of Cardiology (ESC) and the North American Society of
Pacing and Electrophysiology (NASPE) defined and established standards of measurement,
physiological interpretation and clinical use of HRV. Time domain indices, geometric measures and
frequency domain indices nowadays constitute the standard clinically used parameters.
Time domain analysis
Time domain analysis measures the changes in heart rate over time or the intervals between
successive normal cardiac cycles. In a continuous ECG recording, each QRS complex is detected and
the normal RR intervals (NN intervals), due to sinus depolarisations, or the instantaneous heart rate,
are then determined. The calculated time domain variables may be simple, such as the mean RR
interval, the mean heart rate, the difference between the longest and shortest RR interval, or the
difference between night and day heart rate; and more complex based on statistical measurements.
These statistical time domain indices are divided in two categories, including beat-to-beat intervals
or variables derived directly from the intervals themselves or the instantaneous HR and intervals
derived from the differences between adjacent NN intervals. The table below summarizes the most
frequently used parameters of the time domain. Parameters of the first category are SDNN, SDANN
and SD and those of the second category are RMSSD and pNN50.
SDNN is a global index of HRV and reflects all long-term components and circadian rhythms
responsible for variability in the recording period. SDANN is an index of the variability of the average
of 5-minute. Thus, it provides long-term information. It is a sensitive index of low frequencies like
physical activity, changes in position, circadian rhythm. SD is generally considered to reflect the
day/night changes of HRV. RMSSD and pNN50 are the most common parameters based on interval
differences. These measurements correspond to short-term HRV changes and are not dependent on
day/night variations. They reflect alterations in autonomic tone that are predominantly vagally
mediated. Compared to pNN50, RMSSD seems to be more stable and should be preferred for clinical
use.
Variable
SDNN
SDANN
Units Description
ms
standard deviation of all NN intervals
standard deviation of the averages of NN intervals in all 5-minute segments of
ms
the entire recording
SD (or
SDSD)
ms
RMSSD
ms
pnn50
%
Geometric methods
standard deviation of differences between adjacent NN intervals
square root of the mean of the sum of the squares of differences between
adjacent NN interval
percent of difference between adjacent NN intervals that are greater than 50
ms
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Geometric methods are derived and constructed from the conversion of sequences of NN intervals.
There are different geometrical forms for assessing HRV: the histogram, the HRV triangular index
and its modification, the triangular interpolation of NN interval histogram, and the method based on
Lorentz or Poincaré plots. The histogram assesses the relationship between the total number of RR
intervals detected and the RR interval variation. The triangular HRV index considers the major peak
of the histogram as a triangle with its baseline width corresponding to the amount of RR interval
variability, its height corresponds to the most frequently observed duration of RR intervals, and its
area corresponds to the total number of all RR intervals used to construct it. The triangular HRV
index is an estimate of the overall HRV.
Geometrical methods are less affected by the quality of the recorded data and may provide an
alternative to less easily obtainable statistical parameters. However, the time duration of recording
should be at least 20 minutes, which means that short-term recordings cannot be assessed by
geometric methods.
From all variety of time domain and geometric methods available, the Task Force of the ESC and the
NASPE has recommended the use of four measures for HRV assessment: SDNN, SDANN, RMSSD and
the HRV triangular index.
Frequency domain analysis
Frequency domain (power spectral density) analysis describes the periodic oscillations of the heart
rate signal decomposed at different frequencies and amplitudes; and provides information on the
amount of their relative intensity (termed variance or power) in the heart’s sinus rhythm.
Schematically, spectral analysis may be compared to the results obtained when white light passes
through a prism, resulting in different lights of different colour and wave length. Power spectral
analysis can be performed in two ways: 1) by a nonparametric method, the fast Fourier
transformation (FFT), which is characterized by discrete peaks for the several frequency
components, and 2) by a parametric method, the autoregressive model estimation, resulting in a
continuous smooth spectrum of activity. While the FFT is a simple and rapid method, the parametric
method is more complex and needs verification of the suitability of the chosen model.
When using the FFT the individual RR intervals stored in the computer are transformed into bands
with different spectral frequencies. This process is similar to decomposing the sound of a symphony
orchestra into the underlying notes. The results obtained can be transformed in Hertz (Hz) by
dividing by the mean RR interval length.
The power spectrum consists of frequency bands ranging from 0 to 0.5 Hz and can be classified into
four bands: the ultra low frequency band (ULF), the very low frequency band (VLF), the low
frequency band (LF) and the high frequency band (HF).
Variable
Units Description
Frequency range
Total power ms2 variance of all NN intervals <0.4 Hz
ULF
ms2 ultra low frequency
<0.003 Hz
VLF
ms2 very low frequency
<0.003–0.04 Hz
LF
ms2 low frequency power
0.04–0.15 Hz
HF
ms2 high frequency power
0.15–0.4 Hz
LF/HF
ratio ratio of low-high frequency power
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Short-term spectral recordings (5 to 10 minutes) are characterized by the VLF, HF and LF
components, while long-term recordings include a ULF component in addition to the three others.
The table above shows the most used frequency domain parameters. The spectral components are
evaluated in terms of frequency (Hertz) and amplitude which is assessed by the area (or power
spectral density) of each component. Thus, squared units are used for the absolute values expressed
in ms squared (ms2). Natural logarithms (ln) of the power values may be used because of the
skewness of the distributions. LF and HF powers may be expressed in absolute values (ms2) or in
normalised values (nu). The normalisation of LF and HF is performed by subtracting the VLF
component from the total power. It tends to reduce, on one hand, the effects of noise due to
artifacts and, on the other hand, to minimize the effects of the changes in total power on the LF and
HF components. It is useful when evaluating the effects of different interventions in the same
subject (graded tilting) or when comparing subjects with major differences in total power.
Normalised units are obtained as follows:
LF or HF norm (nu) = (LF or HF (ms2))*100/ (total power (ms2) – VLF (ms2))
The total power of RR interval variability is the total variance and corresponds to the sum of the four
spectral bands, LF, HF, ULF and VLF. The HF component is generally defined as a marker of vagal
modulation. This component is respiration-mediated and thus determined by the frequency of
breathing. The LF component is modulated by both the sympathetic and parasympathetic nervous
systems. In this sense, its interpretation is more controversial. Some scientists consider LF power,
particularly when expressed in normalised units, as a measure of sympathetic modulations; others
interpret it as a combination of sympathetic and parasympathetic activity. The consensus is that it
reflects a mixture of both autonomic inputs. In practical terms, an increase of the LF component (tilt,
mental and/or physical stress, sympathomimetic pharmacologic agents) has been generally
considered to be a consequence of sympathetic activity. Conversely, b-adrenergic blockade resulted
in reduction of the LF power. However, in some conditions associated with sympathetic
overexcitation, for example in patients with advanced CHF, the LF component was found to be
drastically diminished, reflecting thereby the decreased responsiveness of the sinus node to neural
inputs.
The LF/HF ratio reflects the global sympatho-vagal balance and can be used as a measure of this
balance. With an average normal adult in resting conditions, the ratio is generally between 1 and 2.
ULF and VLF are spectral components with very low oscillations. The ULF component might reflect
circadian and neuroendocrine rhythms and the VLF component long period rhythms. The VLF
component has been found to be a major determinant of physical activity and was proposed as a
marker of sympathetic activity.
Correlations between time and frequency domain indices and normal reference values
There are established correlations between time domain and frequency domain parameters: pNN50
and RMSSD correlate with themselves and with HF power (r = 0.96), SDNN and SDANN indices
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correlate significantly with total power and the ULF component. Normal reference values and values
in patients with a MI for standard measures of heart rate variability.
Limitations of standard HRV measurements
Because HRV deals with RR interval variations its measurement is limited to patients in sinus rhythm
and to those with a low number of ectopic beats. In this sense, approximately 20 to 30% of high risk
post-MI patients are excluded from any HRV analysis due to frequent ectopy or episodes of atrial
arrhythmias, particularly atrial fibrillation. The latter one may be observed in up to 15 to 30% of
patients with CHF, excluding those from any HRV analysis.
Nonlinear methods (fractal analysis) of HRV measurement
Nonlinear methods are based on the chaos theory and fractal geometry. Chaos has been defined as
the study of multivariable, nonlinear and nonperiodic systems. Chaos describes natural systems in a
different way because it can account for nature’s randomness and nonperiodicity. Perhaps the
theory of chaos may help in better understanding HR dynamics, taking into account that the healthy
heartbeat is slightly irregular and to some extent chaotic. In the near future nonlinear fractal
methods may give new insights into HR dynamics in the context of physiological changes and in high
risk situations, particularly in patients after MI or in the context of sudden death.
Recent data suggest that fractal analysis in comparison to standard HRV measurements seems to
detect abnormal patterns of RR fluctuations more efficiently.
The Modern Understanding of Stress and ANS
The central nervous system (CNS) mediates the distribution of resources to deal with internal and
external demands. Perceptions and assumed threats to survival may promote a massive withdrawal
of PNS tone and a reciprocal excitation of SNS tone. The trade-off between internal and external
needs may be used in developing definitions of stress and homeostasis. In this model stress and
homeostasis are interdependent. Homeostasis reflects the regulation of the internal organs and
stress reflects the subjugation of internal needs in response to external needs. This is why measuring
PNS tone may provide the indexing variable for defining stress and stress vulnerability.
Stress and stress vulnerability can therefore be defined in the absence of major shifts in SNS tone. In
research assessing stress in neonates in healthy children, withdrawal of PNS tone to a stressor is
paralleled by an increased expression of SNS tone. However, in severely compromised children they
may not exhibit SNS reactivity and SNS tone might be low. These children generally have low PNS
tone and very little PNS reactivity. Clinically, they would be described as chronically stressed and
physiologically unstable. Thus PNS tone withdrawal in relation to SNS tone may define stress and
high PNS tone prior to the stressor would represent low stress vulnerability, whilst low PNS tone
would represent high stress vulnerability. Individuals therefore exhibiting problems of homeostasis
will have the greatest stress vulnerability.
In many physiological systems efficient neural control is manifested as rhythmic physiological
variability, and within normal parameters the greater the amplitude of oscillation, the healthier the
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individual. The greater the amplitude of organized rhythmic physiological variability, the greater the
response potential or possible range of behavior. Individuals with attenuated physiological variability
would then exhibit a lack of physiological and behavioral flexibility in response to environmental
demands. This was the situation observed with severely ill infants.
Stimulation of other PNS afferents seems to give a reflex increase in cardiac vagal tone and therefore
the latter seems to reflect the general PNS input to the viscera.
The most readily available measure of PNS activity is derived from heart rate pattern in response to
breathing i.e. respiratory sinus arrhythmia. The heart rate increases with inspiration and decreases
during expiration under the control of efferent parasympathetic impulses along the vagus nerve.
Heart rate patterns, like behavioral processes, are dependent on the status of the nervous system
and the quality of neural feedback. Stress results in a disorganization of the rhythmic structure of
both behavior and autonomic state. Thus, measures of cardiac vagal tone provide a window into the
central processes necessary for organized behavior. If vagal tone is a sensitive index of the functional
status of the nervous system, then we would predict that individuals with greater vagal tone would
exhibit a greater range of competent behaviors.
The pattern of heart rate reflects the continuous feedback between the CNS and the peripheral
autonomic receptors. The primary source of HRV is mediated by phasic increases and decreases in
neural efferent output via the vagus nerve to the heart. The greater the range of the phasic
increases and decreases, the “healthier” the individual. An attenuation in the range of homeostatic
function is paralleled by a reduction in vagal tone.
HRV is a marker of the efficiency of neural feedback mechanisms and may index health status or the
individual’s capacity to organize physiological resources to respond appropriately. Thus, the better
the “organised” physiological variability, the greater the range of behavior. States characterized by
attenuated vagal influences should be paralleled by reduced behavioral flexibility in response to
environmental demands. So, not only the basal level of vagal tone (measurable during sleep) is
important but also the vagal responsivity during sensory and cognitive challenge. Individuals with
greater vagal responsivity as exemplified in larger heart rate acceleration also exhibited fewer signs
of distress.
Heart Rate Variability as a Marker of ANS Activities
HRV is based on the time difference between each heartbeat (R-wave) (as above), i.e. the beat-tobeat variability. Each R-wave represents a contraction of the heart and corresponds to the pulse. The
beat-to-beat variability is affected by autonomic nervous system activity.
Normally the heartbeat should vary from beat to beat under direct control of both the SNS and PNS
(the SNS speeds and the PNS slows the heart rate). HRV is the result of the interaction between
these 2 systems. It is accepted by scientists that this interaction at the heart is a reflection of ANS
balance or imbalance in the body in general. For example, SNS dominance at the heart is therefore
an indication of a general sympathetic dominance in the autonomic nervous system. This would
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indicate a system under chronic stress and a vulnerability to further stresses. An overactive ANS is an
indicator of a system under current stress, with a balanced ANS being important to effective stress
coping.
More recent research highlights how our personality and thought processes influence health and
also HRV. Sustained positive effective states lead to a clear and definable mode of physiological
function that appears to facilitate the body’s natural regenerative processes. Physiological
coherence – a sine-wave-like pattern in the heart rhythm, increased heart/brain synchronisation and
entrainment between diverse physiological systems occurs after positive thought focus, and positive
emotions can produce extended periods of this physiological entrainment.
A healthy physiological system has the following characteristics:
•
Efficient neural control
•
Rhythmic physiological variability within normal limits
•
Greater response-potential to challenge
•
Greater range of response behavior
Attenuated physiological variability is associated with a lack of psychological and behavioral
flexibility in response to environmental demand. A reduction in HRV is therefore not only an
indication of a lack of physiological variability, but also in its broad sense a reflection of reduced
psychological and behavioral flexibility.
Although our understanding of the meaning of HRV is far from complete, it seems to be a marker of
both dynamic and cumulative load. As a dynamic marker of load, HRV appears to be sensitive and
responsive to acute stress. Under laboratory conditions, mental load (including making complex
decisions, and public speech tasks) have been shown to lower HRV. As a marker of cumulative wear
and tear, HRV has also been shown to decline with the aging process. Although resting heart rate
does not change significantly with advancing age, there is a decline in HRV, which has been
attributed to a decrease in efferent vagal tone and reduced beta-adrenergic responsiveness. By
contrast, regular physical activity (which slows down the aging process) has been shown to raise
HRV, presumably by increasing vagal tone.
In short, HRV appears to be a marker of two processes, relevant to the conceptualization of allostatic
load: (1) frequent activation (short term dips in HRV in response to acute stress); and (b) inadequate
response (long-term vagal withdrawal, resulting in the over-activity of the counter-regulatory system
--in this case, the sympathetic control of cardiac rhythm).
Several studies have now suggested a link between negative emotions (such as anxiety and hostility)
and reduced HRV. Cross-sectional association between anxiety and reduced HRV (as assessed by two
time-domain measures). Lower HRV in individuals who were "highly anxious" according to the
Minnesota Multiphasic Personality Inventory.
Theoretical Justification And Practical Importance Of Dantest
The theoretical basis of Dantest underlies in a study, which brings evidence that chronically
increased sympathetic tone (distress) can facilitate cancer development. This finding is similar to
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the positive relationship we have discovered between chronic sympathetic tone and other life
threatening diseases (16). Consequently, we can conclude that the optimal equilibrium of the
autonomic balance can play an extremely important role, and that is why it should be quantitatively
controlled when cancer management is necessary. It seems that most of the complementary
medical approaches for cancer treatment are based on parasympathetic facilitation. revealed that
chemotherapy, surgery or radiotherapy are additionally increasing the sympathetic activity, which
can contribute to the insufficient efficacy they are demonstrating. The management of
malignancy is seeking for new methods decreasing cancer recurrence, relapses and assuring a
metastasis-free survival (13, 14). Those methods should provide (according to the proposed model)
periods of deep relaxation (vagotonia) as strong as possible, because it facilitates the work of the so
called “intern health promoting mechanism”. That is why the global anti-malignancy management
(or strategy) should be directed not only towards “killing cells”, but also towards improvement of
their informational management. It is not cells that are “ill” from biological point of view, but rather
the whole organism. Unfortunately, the humans are learning more how to work and less how to
ensure complete rest for their organisms.
Graphical presentation of Stress-based malignancy model
(The quality “health” needs a regular oscillation of biological activity between A and B. As higher is
the sympathetic prevalence in the day time (B), as higher is the parasympathetic prevalence in the
night time (A)).
A stands for: Night (rest); Increased parasympathetic
(vagal) tone; Information exchanging (receiving);
Deep relaxation in sleep; Paradox sleep - REM;
Trophotropic orientation of the system (open
system).
B stands for: Day (action); Increased
sympathetic tone; Information processing
(loosing); High activation in wakefulness;
Ergotropic orientation of the system (closed
system).
There are mainly three types of oscillations:
1. Normal. It was observed in young, absolutely healthy persons and in
sportsmen (not over-trained).
There exists an optimal “exchange” (receiving) of information in night time
(parasympathical (vagal) autonomic prevalence-REM) and its “processing”
in day time (sympathetic autonomic prevalence).
System does not need an intervention.
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2. Highly pathogenic. It was observed in persons with overstress and in ill
persons, including cancer patients.
The biological activity is more “B” oriented. The possibility to “exchange”
life important biological information in rest is restricted.
System needs more “A” activity.
3. Pathogenic. It was observed in aged persons as well as in persons from
younger age groups, not willing to spent “efforts”.
The biological activity is less in “A”, due to decreased “B” activity.
The possibility to “exchange” life important biological information in rest is
decreased.
System needs more “B” activity.
History
Dantest is the global leader in the development, manufacture and marketing of Heart Rate
Variability / ANS / PWV products. The company was founded in 1992 as a Research and
Development company. Specifically, Dantest develops biomedical software and hardware products
designed to monitor physiology for research and educational purposes. Currently our focus is on
developing state-of-the-art Heart Rate Variability products that fit the needs of researchers,
consumers, educational, corporate, fitness and professional services.
Dantest provides a full spectrum of Heart Rate variability products that compliment the research and
educational world’s needs. Dantest has an expert team for software and hardware development,
design and implementation. Our focus is on innovation with a commitment to excellence. Dantest is
a developer of well-known products.
The company’s current products have proven marketability and are valued by practitioners and
researchers in a variety of health care and professions throughout the world.
Our focus and goal is to continually seek strategic alliances to develop cooperative products and
concepts to bring to the market place.
Dantest is the world leader in the development of innovative cutting edge Heart Rate Variability
monitoring products. We will continue to strive to bring cutting edge physiological monitoring
technologies into the research and educational setting.
Our Mission
Our company's objective is to bring intrinsic medical knowledge and software development
experience for physiological monitoring into the market place. Our strength lies in the unique
knowledge base and skill of the team who are medical doctors with software engineering skills. The
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company vision is to create products for the general public, biomedical, research, educational and
fitness markets.
Company Profile
Dantest is a team of software and hardware development engineers, medical doctors and skilled
therapists who have over 20 years of experience in the development of physiological monitoring
systems, software and hardware for functional diagnostics, psychophysiological research, etc.
We have developed a new Windows-based physiological monitoring software platform for various
commercial products. This platform has moved Dantest into the technological forefront of software
available for aa wide variety of physiological monitoring applications and protocols.