Heart rate variability as important approach for assessment autonomic modulation

Abstract

Alterations in the heart rate recovery and heart rate variability have been associated with greater risk of mortality and early prognosis of cardiac diseases. Thus, strategies for assessing autonomic nervous system and its modulation to the heart are crucial for preventing cardiovascular events in healthy subjects as well as in cardiac patients. In this review, an update of studies examining heart rate variability (HRV) and its use as indicator of cardiac autonomic modulation will be discussed. It will be described the indexes and methods of analysis and its applicability and the effects of exercise training on HRV and heart rate recovery in different population.

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3Motriz, Rio Claro, v.22 n.2, p.3-8, Apr./June 2016 DOI: http://dx.doi.org/10.1590/S1980-65742016000200001
Mini Review
Heart rate variability as important approach for
assessment autonomic modulation
Maycon Jr Ferreira
Angelina Zanesco
Universidade Estadual Paulista “Julio de Mesquita Filho”, Rio Claro, SP, Brasil
Abstract––Alterations in the heart rate recovery and heart rate variability have been associated with greater risk of
mortality and early prognosis of cardiac diseases. Thus, strategies for assessing autonomic nervous system and its
modulation to the heart are crucial for preventing cardiovascular events in healthy subjects as well as in cardiac patients.
In this review, an update of studies examining heart rate variability (HRV) and its use as indicator of cardiac autonomic
modulation will be discussed. It will be described the indexes and methods of analysis and its applicability and the
effects of exercise training on HRV and heart rate recovery in different population.
Keywords: autonomic nervous system, exercise, heart rate, vagal modulation
Introduction
Cardiovascular system, autonomic nervous system and
cardiac function
The cardiovascular system is characterized by a complex
interaction of several organ and tissues including heart and blood
vessels and it is regulated by intrinsic and extrinsic mechanisms.
The autonomic nervous system (ANS) provides rapid adjust-
ments of the heart and blood vessels playing an important role
on cardiovascular system regulation (Guyton & Hall, 2006).
The heart is a muscular organ with a special excitatory and
conduction specialized system able in generating rhythmic elec-
trical impulses as well as to transmit these signals throughout the
myocardium. Under normal conditions, the conduction process
begins in a particular area of the heart, named atrial sinus node,
which electrical property can generate the action potential that
spreads quickly by specialized bers to the heart resulting in con-
traction of entire cardiac muscle (Shaffer, McCraty, & Zerr, 2014).
In addition to this intrinsic mechanism that determines the basal
cardiac rhythm, the ANS plays an important role in controlling
heart function and vascular system through the sympathetic and
parasympathetic bers to the heart and sympathetic bers to the
vessels (Hainsworth, 1998). In the heart, norepinephrine released
from autonomic sympathetic bers produces positive inotropic and
chronotropic responses acting through stimulation of β-adrenocep-
tors (Feldman, 1987). On the other hand, acetylcholine released
from parasympathetic bers produces negative inotropic and chro-
notropic responses through stimulation of muscarinic receptors
(Dörje et al., 1991). Thus, the two branches of ANS, sympathetic
and parasympathetic bers, act in an opposite way providing a ne
adjustment on the cardiac tissues in response to different stimuli
and daily activities. In blood vessels, norepinephrine released from
autonomic sympathetic bers causes vasoconstriction response by
activating α-adrenergic receptors/IP3 signaling pathway. Thus, an
unbalance between sympathetic and parasympathetic drive has
been proposed as a potential mechanism in some cardiovascular
diseases such as arterial hypertension, heart failure and myocardial
infarct. On the other hand, it has been demonstrated that exercise
training can improve the autonomic dysfunction in these patho-
logical conditions (Carter & Ray, 2015).
Adrenergic and cholinergic receptors in the heart
In the heart, the sympathetic endings are responsible for
innervation of the entire organ, while parasympathetic nerve
endings are present only in the sinoatrial node, atrial myocar-
dium and atrioventricular node (Guyton & Hall, 2006). At least
three distinct subtypes of β-adrenoceptors have been described
in cardiac tissue, namely β1, β2, and β3 (Emorine et al., 1989;
Kaumann & Molenaar, 1997). The activation of β-adrenocep-
tors stimulate Gs-protein (stimulatory G-protein), which in
turn, promotes activation of adenylyl cyclase, that catalyzes the
conversion of adenosine triphosphate (ATP) to cyclic adenosine
3´5´-monophosphate (cAMP). The increment of cAMP levels
activates protein kinase A, which phosphorylates several proteins
leading to an increase of intracellular Ca2+ concentration resulting
in positive chronotropic and inotropic responses (Birnbaumer,
1990; Rodbell, 1980).
Acetylcholine released from parasympathetic bers can
stimulate two major types of receptor named nicotinic and mus-
carinic receptors. Muscarinic receptors belong to the class of G
protein-coupled receptor and are widely distributed throughout
the periphery and the central nervous system (Cauleld, 1993).
Five subtypes of muscarinic cholinergic receptors have been
detected by molecular cloning named M1, M2, M3, M4, and M5.
In cardiac tissue, the stimulation of the subtype M2 muscarinic
receptor by acetylcholine promotes an activation of a Gi pro-
tein causing inhibition of adenylyl cyclase and/or activation of
receptor-operated K+ cha nne ls l ead ing to ne gat ive chr onot rop ic
and inotropic response (Kubo et al., 1986).

4Motriz, Rio Claro, v.22 n.2, p.3-8, Apr./June. 2016
M.J. Ferreira & A. Zanesco
Cardiovascular system, autonomic nervous system and
arterial baroreex
Arterial baroreceptors are stretch sensors that innervate
adventitia of aortic arch and carotid sinuses. Increase in arterial
blood pressure regulate arterial baroreceptors activity which,
in turn, triggers a membrane depolarization by activating ion
channels in the afferent bers transmitting to the central nervous
system. When arterial blood pressure is diminished this signaling
activation is blunted. The main site of afferent bers from arterial
baroreceptors is the nucleus of the tractus solitarius (NTS). In the
NTS, a complex neuronal network is activated (or deactivated)
and a number of cellular effector systems modulates sympa-
thetic or parasympathetic bers (Guyton & Hall, 2006). NTS is
essential for arterial baroreceptor reex function (Figure 1). It
has been well documented that arterial baroreex dysfunction
is clinically relevant, particularly, alterations in the heart rate or
its variability have been associated with greater risk of mortality
and cardiac diseases (Parati, Di Rienzo, & Mancia, 2001).
Figure 1. Overview the neural communication pathways between
baroreceptor reex and control of heart rate by autonomic nervous
system.
Heart rate variability assessment
The assessment of HRV has been considered as an important
non-invasive method able in promoting indirect information
about cardiac autonomic modulation. This method consists
in analyzing the uctuations in interval between successive
heartbeats, dened by the distance between two R waves
(R-R interval), which reect the autonomic control, through
the sympathetic and parasympathetic, inuences on the heart
(Lahiri, Kannankeril, & Goldberger, 2008) (Figure 2). It has
demonstrated that the increase in the vagal efferent modulation
is characterized by increasing in the HRV, whereas sympathet-
ic stimulation diminishes the HRV which, in turn, has been
associated with an increased risk of cardiovascular events and
death in healthy patients (Tsuji et al., 1994, 1996). Indeed,
many researchers have focused their studies on analysis of HRV
patterns obtained under different physiological conditions in
an attempt to evaluate the autonomic cardiovascular control in
healthy individuals as well as the integrity of ANS in patients
with cardiovascular diseases (Singh et al., 1998). Moreover, this
analysis has been used, in order, to examine the acute or chronic
responses promoted by physical exercise on the cardiovascular
system (Anaruma, Ferreira, Sponton, Delbin, & Zanesco, 2015;
Grant, Viljoen, Janse van Rensburg, & Wood, 2012; Jurca,
Church, Morss, Jordan, & Earnest, 2004)
Figure 2. ECG tracing in healthy individual
Cardiac rhythmicity and its relationship with the various
physiological mechanisms have been historically investigated.
During centuries, researchers sought in monitoring the patterns
of sounds and rhythms cardiac and to examine that factors such
as age, presence of diseases and physiological status would
be associated with changes in rhythmic patterns of the heart
(Berntson et al., 1997).
The rst historical accounts documented about HRV are
assigned to the nding of Hales in 1733 using a horse. He was
the rst to verify a relationship between change in blood pres-
sure levels and beat-to-beat interval with the respiratory cycle.
In the following century, through the creation of the apparatus
termed “kymograph” able to graphically record variations in
movement, Ludwig in 1847 reported what had come to be
later known as respiratory sinus arrhythmia (RSA). In their
study using dog, he found that the breathing pattern was able
to promote uctuations in amplitude and timing of the arterial
pressure waves, so that the inspiration promotes an acceleration
of the pulse while the expiration lead the opposite effect. In
addition, Donders in 1868 suggested that the activation of the
vagus nerve was responsible for the changes in the duration of
the cardiac cycle associated with breathing, fact that has been
demonstrated in the following years. Several other studies have
been conducted sought to investigate the relationship between
sympathetic and parasympathetic efferent on uctuations in
arterial pressure waves and heart rate, recognizing the HRV
as an important physiologic measure (Berntson et al., 1997).
It was in the mid 1960s that the physiological and clinical
signicance of HRV was rst demonstrated showing that fetal
distress was preceded by a reduction in the interval between
heartbeats before any signicant change in heart rate (Hon &
Lee; 1965). During the 1970s, it was demonstrated for the rst
time the association between reduced HRV and increased risk of
mortality after acute myocardial infarction (Wolf, Varigos, Hunt
& Sloman, 1978). In an early study, using the short-term changes

Motriz, Rio Claro, v.22 n.2, p.3-8, Apr./June 2016 5
Heart rate variability as important approach for assessment autonomic modulation evaluation
in R-R interval an association between autonomic neuropathy
and diabetic state was described (Ewing, Martyn, Young, &
Clarke, 1985). With the advancement of technology combined
with application of new processing techniques and analysis,
several new studies were carried out allowing a greater under-
standing of the heart rate and their interaction with the ANS.
On the other hand, the high complexity involving the direct
measurement techniques of cardiac autonomic activity, mainly
because the assessment of vagal activity not be performed in
humans (Tan, 2013) further contributed to the assessment of
HRV was considered an important variable in clinical practice
(Shaffer et al., 2014).
Methods and techniques for HRV analysis
The HRV has been considered as a variable that allows
estimation of cardiac autonomic modulation. Fluctuations in
the R-R intervals may be quantied by numerous techniques
evaluation capable of providing indices that reect the ANS
modulation into the heart. With the objective to standardize the
terms and measurement methods in both basic and in clinical
studies, members of the European Society of Cardiology and
the North American Society of Pacing and Electrophysiology
created a Task Force (Task Force, 1996).
Currently, HRV analysis can be performed using linear
methods, which are divided in the time domain and the fre-
quency domain, and also using non-linear methods. In the linear
analysis in the time domain, which is considered as the simplest
measure of the HRV, the indices are derived from the measure-
ment of intervals between normal beats (normal-to-normal) suc-
cessive in a series of continuous time that can be evaluated by
statistical or geometric patterns (Bilchick & Berger, 2006; Task
Force, 1996). The indices obtained commonly used include
the standard deviation of all normal-to-normal (NN) intervals
(SDNN), i.e., the square root of the variance, which reects the
total variability during the recorder period. Characterized as the
most widely used index in the time domain, the calculation of
SDNN requires attention because the presence of ectopic beats
and artifacts as well as the duration of registration can directly
inuence the measurements (Kleiger, Stein, & Bigger, 2005).
Besides this, other variables calculated during the registration
period include the standard deviation of the averages of NN
intervals calculated in all 5 minutes segments of the entire re-
cording (SDANN), which measures changes in the long-term,
and the mean of the standard deviation of the NN intervals for
all 5 minutes (SDNN index) and reect the average of changes
occurring at intervals within the time of 5 minutes (Task Force,
1996). The analysis in the time domain further provides other
related measures which are derived from the difference be-
tween the R-R intervals, including the square root of the mean
of the sum of the squares of differences between successive
NN intervals (RMSSD), the number of pairs pf adjacent NN
intervals with a difference of duration longer than 50 ms in the
registration period (NN50) and the percentage of successive
NN intervals with a difference of duration longer than 50 ms
(pNN50). These indices are obtained by the difference between
successive regular intervals aiming to detect high frequency
oscillations and to provide information on parasympathetic
autonomic modulation (Kleiger et al., 2005; Pumprla, Howorka,
Groves, Chester, & Nolan, 2002).
The geometric analysis method consists in further analysis
of HRV in the time domain, where in the R-R intervals are
converted graphically in geometric patterns (Task Force, 1996).
The triangular index HRV is calculated using the number of all
NN intervals divided by the maximum distribution density. The
reduction of this index has been associated with an increased
mortality (Ewing et al., 1985). Another technique is the Lorenz
plot (also known as a Poincaré plot), where each beat is plotted
in association with the next beat, providing graphical infor-
mation and dispersion of the variation in the time series. This
analysis can be performed both quantitatively and qualitatively
(Billman, 2011).
The linear method in the frequency domain (spectral analysis)
has been widely used since its introduction in the 1960s as another
technique for the investigation of HRV. Unlike the time domain,
this technique decomposes the total variability of the signal in
specic components that operate in different frequency bands,
allowing identication (Shaffer et al., 2014). The calculation of
the power of spectral density (PDS) can be done through the fast
Fourier transform techniques (FFT) or by autoregressive (AR)
model. Regardless of the technique used, as short-time records
(2–5 minutes) it is possible to obtain the components of very low
frequency (VLF) (<0.04 Hz), low frequency (LF) (0.04–0.15 Hz)
and high frequency (HF) (0.15–0.4 Hz), while in the analysis
over 24 hours a fourth peak frequency, represented as ultra low
frequency (ULF) (0.003–0.04 Hz) can also be obtained (Billman,
2011; Task Force, 1996).
The HF component has been widely emphasized as an index
that reects the vagal modulation, whereas the LF component
reects an interaction between sympathetic and parasympa-
thetic (Kleiger et al., 2005). On the other hand, experimental
data suggest that the rhythm pattern of VLF is intrinsically
generated by the heart and that its oscillation is modulated
by sympathetic nerve endings (McCraty & Shaffer, 2015). In
addition, the calculation of LF and HF (LF/HF) has been used
historically as a measure involving the sympathetic/parasym-
pathetic balance (Malliani, Pagani, Lombardi, & Cerutti, 1991;
Pagani et al., 1986). Nevertheless, recent studies suggest that
this measure can not be an accurate measure of this balance
(Billman, 2013).
The evaluation of the HRV from the linear methods can be
performed from records with duration of 2, 5 and 15 minutes
(short-time) and over 24 hours (long-time). Although it is also
used for short-term analysis, the indices obtained in the time
domain have been commonly used for long-term records to
promote a better interpretation of the results because of the the
instability of the heart rate over time. On the other hand, short
records are preferably interpreted from the frequency domain
indices (Task Force, 1996). The presence of noise, trends, ecto-
pic beats and artifacts has been considered as the main problems
found in the records of the HRV, which can directly affect the
quality of HRV analysis, requiring the signal correction (Huikuri
et al., 1999).

6Motriz, Rio Claro, v.22 n.2, p.3-8, Apr./June. 2016
M.J. Ferreira & A. Zanesco
HRV and exercise
HRV has been frequently used to assess the modulation of the
autonomic nervous system on the heart during and immediately
after exercise, as well as the adaptations induced by long-term
training (Krieger et al., 1998).
Evidence suggests that physical exercise promotes an im-
provement in the cardiac autonomic regulation, characterized
by an increase in the R-R interval and increased vagal modu-
lation (Sandercock, Bromley, & Brodie, 2005). A higher HRV
in trained individuals compared with untrained individuals has
indeed been quite evident.
In athletes, it has been largely demonstrated that the indexes
that reect the cardiac vagal modulation are markedly increased,
indicating that physical training positively affects the vagal tone
and that this could contribute to lower heart rate observed at rest
in this population (Aubert et al., 1996; Bonaduce et al., 1998;
Goldsmith, Bigger, Steinman, & Fleiss, 1992). In addition,
evidence suggests that lower heart rate at rest in athletes is also
due to intrinsic adaptations in cardiac signal conduction system
(Shin, Minamitani, Onishi, Yamazaki, & Lee, 1997).
The HRV indices have also been used to evaluate the inu-
ence of different levels of aerobic capacity on the autonomic
modulation. No differences in autonomic modulation evalu-
ated by HRV were found in healthy individuals at different
levels of aerobic capacity or physical activity (Dutra et al.,
2013; Melanson, 2000), showing no dose-dependent rela-
tionship with the aerobic capacity. Furthermore, other studies
suggest that moderate volume of aerobic exercise is sufcient
to induce benecial effects on the cardiovascular autonomic
system in healthy subjects (Earnest, Blair, & Church, 2012;
Tulppo et al., 2003).
Interestingly, contradictory results have been observed
evaluating the HRV in elderly (70 and 80 years) and mid-
dle-aged population where no changes were observed through
HRV index in the frequency domain after exercise training
(Loimaala, Huikuri, Oja, Pasanen, & Vuori, 2000; Perini, Fisher,
Veicsteinas, & Pendergast, 2002).
The HRV indices were also been used to assess autonomic
modulation in response to exercise in patients under different
pathological conditions. Regarding cardiovascular diseases,
studies have shown that physical training promotes increased in
the HRV in hypertensive (Cozza et al., 2012), diabetics (Zoppini
et al., 2007) and coronary artery disease patients (Iellamo,
Legramante, Massaro, Raimondi, & Galante, 2000).
The exercise training has also been able to change the HRV
in favor of a increase autonomic vagal modulation in postmeno-
pausal women (Earnest et al., 2012; Jurca et al., 2004).
Finally, the physiological responses of HRV after a bout of
exercise are clinically relevant and it has been used as an important
approach to detect early symptoms of autonomic dysfunction in
patients with diabetes or other cardio metabolic diseases. Indeed,
heart rate recovery measurement after exercise test is considered
crucial to examine the sympatho-vagal balance since during exer-
cise sympathetic drive is increased while a decrease in parasympa-
thetic activity is withdrawal or diminished, whereas in the recovery
period changes in autonomic tone are observed characterized by
sympathetic withdrawal and parasympathetic reactivation with
gradual return of heart rate to resting level. Thus, clinical studies
have proposed that a decrease in heart rate from peak exercise to 1
min into recovery of < 12 beats/min or less is dened as abnormal
heart rate recovery and a predictor of mortality indicating impair-
ment of the integrity of parasympathetic tone (Cole, Blackstone,
Pashkow, Snader, & Lauer, 1999). A recent study from our
laboratory showed a lower SDNN index, which indicates lower
vagal modulation, during recovery time in type 1 diabetic patients
suggesting an autonomic imbalance even though the patients did
not present an overt cardiovascular disease (Anaruma et al., 2015).
Therefore, the analysis of HRV and heart rate recovery immediately
after exercise is extremely useful providing valuable information
about the autonomic control as well as its integrity.
Final considerations
Interest in the study of HRV has increased signicantly since
the rst reports of its clinical relevance and its association with
an increased risk of mortality after acute myocardial infarction.
In an attempt to understand the role of the autonomic nervous
system on the heart rate, assessment of the sympathetic and
parasympathetic modulation is crucial in exercise science ap-
plied to sports and health. The use of spectral analysis of HRV
has not shown satisfactory results in the evaluation of changes in
autonomic regulation during exercise, however it has been a fea-
sible methodology to examine the inuence of both sympathetic
and parasympathetic nerves into the heart rate mainly during
recovery period after exercise test . Moreover, adaptations of the
autonomic nervous system induced by physical training are not
yet fully understood. Although strong evidence has shown an
improvement in autonomic modulation by increasing the HRV
after long-term training, controversial results exist.
In conclusion, the HRV has proven to be a useful method
non-invasive and practical for the quantitative assessment of
the acute and chronic effects of exercise on cardiac autonomic
modulation in humans, mainly parasympathetic tone inuence.
HRV should be a complementary measurement in cardiovascular
assessments in different populations; however, it is necessary
large scale studies to get more conclusive data.
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Autor’s note
Maycon Jr Ferreira and Angelina Zanesco are afliated to the Labo-
ratory of Cardiovascular Physiology and Exercise Science, Institute
of Biosciences, UNESP, Rio Claro, SP, Brazil.
Corresponding author
Angelina Zanesco, Professor in Physiology, Institute of Biosciences,
UNESP
Av. 24A, 1515, Bela Vista, Rio Claro, SP, Brazil.
Email: azanesco@rc.unesp.br; lina.co@hotmail.com
Manuscript received on February 16, 2016
Manuscript accepted on March 17, 2016
Motriz. The Journal of Physical Education. UNESP. Rio Claro, SP, Brazil
- eISSN: 1980-6574 – under a license Creative Commons - Version 3.0