Heart rate variability in exercise and various ...

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New Insight into Cardiovascular Apparatus During Exercise. Physiological and Physio-pathological Aspects, 2007: ISBN: 81-308-0148-5 Editors: Antonio Crisafulli and Alberto Concu

Heart rate variability in exercise and various physiological conditions Roberta Forte and Giuseppe De Vito Istituto Universitario di Scienze Motorie (IUSM) of Rome, Italy

Abstract The assessment of heart rate variability (HRV), because of its prognostic capability, has become very popular in the last 20 years. However, despite its popularity the physiological interpretation of HRV is still debated. The present article focussed on the evaluation of HRV in different physiological conditions associated to exercise. The distinct relationships between HRV, training load, overtraining and fatigue are analysed. Although it is recognised that, during dynamic exercise, the heart rate increase is the result Correspondence/Reprint request: Prof. Giuseppe De Vito, Department of Human Movement and Sport Science, IUSM. Piazzale L. De Bosis, 15 00194 Rome, Italy. E-mail: [email protected]

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result of both a parasympathetic withdrawal and an augmented sympathetic activity, the exact contribution of these two mechanisms is still uncertain. Moreover the assessment of HRV during exercise is additionally complicated by the fact that the recorded signal is non-stationary. In conclusion it can be underlined the need for the standardization of the methods of HRV assessment during exercise. Future studies should be performed ideally on large populations and adopting randomized controlled trials in order to ameliorate the assessment of HRV in exercise, to monitor the training and to augment its capability as a tool for the prevention of the overtraining syndrome and to monitor physical fatigue during periods of intensive training.

Introduction Heart rate variability (HRV) is the term indicating the variation in time between successive heart beats [1,2]. In fact, even if the HR of a healthy individual at rest appears to have a regular beat, by the exam of an ECG it is possible to observe that the QRS complexes show periodic variations in the length of the R-R intervals. Respiratory sinus arrhythmia is a typical example of HRV where the temporal variations are dictated by the phases of respiration: a predominant vagal activity to the sinus node decelerates the heart beat with expiration and a very reduced or absent one accelerates it with inspiration. The control of heart rate (HR) is mainly under the influence of the autonomic nervous system through the activity of its sympathetic and parasympathetic branches [3]. HRV reflects the continuous interaction of both the sympathetic and the parasympathetic components of the autonomic nervous system as observed under different physiological or pathological conditions for which the predominance of one tone or the other is known. In fact, HRV depression, for increased sympathetic or reduced parasympathetic activity, is considered as a marker of reduced vagal activity as observed with vagotomy [4] or in conditions such as coronary heart disease, hypertension and heart failure [5]. In figure 1, two examples of HRV recording (R-R intervals), one in a healthy subjects and the other in a patient affected by congestive heart failure (CHF) are presented. It is apparent the dramatic reduction in HRV observable in the CHF patient. For these reasons and for its relative simplicity of assessment and inexpensiveness, since its introduction in the 80’s, HRV assessment has become a widely used non-invasive method for the study of the autonomic influence on the heart [1]. This widespread interest in HRV has produced an enormous amount of research on the topic especially following the findings that low levels of HRV are a strong independent predictors of mortality after myocardial infarction [1,6] and of all cause mortality [7]. Among the physiological conditions under which HRV has been investigated, both the acute and long term effects of exercise represent a significant section.

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Figure 1. Two examples of R-R variability recorded in supine resting conditions in one healthy subjects [top graph] and in one individual suffering from congestive heart failure [bottom graph; CHF].

Before introducing the topic it seems useful to describe the methods of HRV assessment and its physiological interpretations. Moreover, for the sake of conciseness, it was decided to consider only some of the most relevant studies, to our opinion, on HRV and to limit the discussion to the studies which adopted linear method of HRV analysis in normal physiologic conditions unless otherwise stated.

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HRV assessment The assessment of HRV requires the measurements of continuous ECG from just a few minutes to many hours (up to 24 hours and more) depending on the objective of the study [1,2,8]. In order to ensure stable recordings, it is recommended, for short term measurements, not to exceed 10 minutes, and a 5 minute duration is indicated as sufficient to give results easily interpretable from the physiological point of view. HRV can be then quantified adopting either a time or frequency domain analysis, the former being best recommended for long term and the latter for short term measurements [1]. In addition, the following factors must be considered when studying HRV: a) ageing; older individuals demonstrate lower HRV values compared to young subjects [9,10]; b) gender-related differences [11,12]; pre-menopausal women show lower HRV values than males of similar age (with the exception of the HF component); c) HRV has been shown to change during the various phases of menstrual cycle [13]; hence it is suggested in pre-menopausal women to record HRV at a specific temporal point during the menstrual cycle [8]. However, a recent study did not found differences in HRV during the menstrual cycle in young women [14].

Time domain analysis In the time domain analysis the NN intervals (normal-to-normal, or all the intervals between QRS complexes) in milliseconds, or the instantaneous HR, are plotted against time. The main obtainable variables include: The average of all NN intervals, the standard deviation (SD) of the NN intervals, or the square root of the variance (SDNN); the standard deviation of the mean NN interval obtained from successive 5 minutes periods (SDANN); the difference between two successive NN intervals or the square root of the mean of the squared differences of successive NN intervals (RMSSD); the number of successive intervals differing more than 50 ms, expressed as a percentage of all intervals (pNN50). From long ECG recordings more complex statistical calculations can be performed and more information can be derived, such as the differences in HRV between night and day, between rest and activities of various type.

Frequency domain analysis Mathematical manipulations (i.e. the application of fast Fourier transformation, autoregressive model or Wavelet decomposition) of the ECG allow the measurement of frequency domain parameters through the analysis of the power spectral density which plots power as a function of frequency. One of the main, unsolved, difficulties associated with spectral analysis is represented by the lack of stationarity especially when a long term recording is performed [1]. For this reason the spectral analysis of long duration segments,

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typically of 24 hours, is in general performed from shorter epochs (2-5 min) that are then averaged over the entire considered period. This procedure, however, although able to lessen the problem, has the disadvantage of masking any detail concerning the short-term autonomic modulation. Another procedure consists in identifying the presence of a time trend in the R-R sequence that can be then removed before calculating the corresponding power spectrum. Three main frequency bands can be observed in the power spectrum of recordings from which the variables are derived: the very low frequency < 0.004Hz (VLF), the low frequency 0.004-0.15Hz (LF), and the high frequency from 0.15 to 0.4Hz (HF). A further variable that can be derived is the ratio between LF and HF (LF/HF). VLF, LF and HF are measured in millisecond squared. Pagani et al [15] suggested to report the frequency parameter data in normalised units [(Lf or HF value / total power)- VLF] in order to represent the relative value of each component proportionally to the total power (TP) minus the VLF. This procedure should be used when a change in the TP of the power density spectrum is expected and especially to compare the effect of training or of a pharmacological intervention [1]. Another sort of normalisation is obtained by presenting the two main frequency components as the ratio HF/TP and LF/TP.

Interpretations of HRV parameters For what concerns the physiological interpretations, the variables which seem to better differentiate the activity of the two branches are those derived from the frequency domain analysis possibly because more information exists on interpreting those with respect to the time domain ones. In fact, the time domain parameters although giving a general quantification of the level of HRV, do not reflect the prevalence of one or the other branch. Having said that, vagal dominance is shown by a long NN interval and a large variance of the same and furthermore, the pNN50 and the RMSSD, obtained both from short and long term measurements, are reported to provide the same data as the HF since highly correlated with each others especially at rest [1,16]. For the frequency domain parameters researchers agree in considering the HF as an expression of the vagal efferent activity as demonstrated by manipulations of the vagal outflow such as electrical vagal stimulation, muscarinic receptor blockade and vagotomy or simply by a cold stimulation of the face, or with a rotational stimulus. Moreover, since the HF component is strongly affected by the respiratory activity both in terms of breathing frequency and tidal volume [17,18], many authors suggest that HRV must be recorded also in controlled breathing conditions. The interpretation of the LF is more controversial, some consider it the reflection of both the sympathetic and parasympathetic influence, and others, when normalised, an index of sympathetic influence.

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In fact, LF normalised (LFnu) is usually found increased during 90° tilt, posture change from lying to standing, mental stress and light exercise [1]. The LF/HF ratio is considered by some as a balanced expression of the modulation of both branches of the autonomic nervous system [15], with high values suggesting a sympathetic prevalence, although some authors remain sceptic about its validity [19].

HRV during exercise Although still far from being completely understood HRV is regularly used as a marker of sympathovagal balance. In the attempt to gain a better insight on the modulation of the cardiac adaptations during exercise, it has also been employed as a tool to quantify the neural contributions of the two branches of the nervous system, although results are not always concordant with what expected. It is well known that under resting conditions the vagal tone prevails through the inhibition of the sympathetic outflow and that just before the beginning and during exercise, a series of adjustments are put in place in order to respond to the stress of exercise. At cardiac level the autonomic nervous system allows the very rapid increase in HR through the progressive withdrawal of parasympathetic nerve activity and the increase in sympathetic outflow [8,20]. The relative influence of these two aspects varies depending on the exercise intensity and also partially on the environmental condition such as during heat exposure [21]. Table 1 and 2 report a summary of the main studies exploring the HRV response during steady state (table 1) and incremental exercise (table 2). Aerobic exercise is the form of exercise mainly studied and the research generally reports that during exercise the increase in HR is coupled with a general decline in HRV exponential to the intensity of the exercise [21-25]. For time domain variables it is well documented a decrease in R-R interval, SDNN, RMSSD [23,24,26-28] reflecting the reduced influence of the parasympathetic branch, both when the exercise is performed standing or supine, and already present at low exercise intensities [21,29]. Perini et al. [22] report 25-30% of V O2max as the upper limit of vagal influence to HR increase, intensities at which both the LF and HF are reported to remain unchanged. This point underlines the importance of considering the intensity of the performed exercise when investigating HRV. Regarding the frequency domain variables, in fact, results show a decrease in total power related to exercise intensity [20,21, 28,30-33] and in HF power [16,20,23,28,30,31,34,35], with a levelling off for higher intensities [24]. The LF power is reported either to remain constant [36] and to decrease [16,22-25;30,31,34; 35,37,38]. Brenner et al. [21] who reviewed a number of studies on HRV and exercise report, in

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Table 1. Main heart rate variability parameters obtained during steady-state exercise in different studies. The comparisons are made with respect to the resting values and for the studies adopting a pharmacological blockade only the placebo condition results are reported. LF and HF are in absolute values unless otherwise specified in the table.

Table 2. Main heart rate variability parameters obtained in different studies adopting an incremental protocol. The comparisons are made with respect to the resting values and for the studies adopting a pharmacological blockade only the placebo condition results are reported.

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general, a decrease in total power and in HF and LF as exercise proceeds up to about the 50% of V O2max with a subsequent levelling off for the higher intensities. All these findings are in contrast to what could be anticipated. In fact if HF was really a reflection of vagal influence it should be progressively decreasing when changing from rest to low intensity exercise, when HR increase is mainly caused by vagal withdrawal. Some authors suggest that reasons other than the neural control could be responsible for the HR increase during exercise [31] and that during exercise HRV spectral analysis does not seem to be an adequate method to assess sympathetic and parasympathetic influence [24;29,39]. It must be also emphasised that at high or near maximal exercise intensities the estimation of spectral components is affected by the dramatic reduction in total power induced by exercise [29]. The notion that HRV spectral variables do not properly reflect sympatho-vagal modulation during exercise has been confirmed even after normalisation of the power spectral variables. In fact, during exercise, HFnu is reported to decrease by some authors [37,38], but not by others suggesting an unlikely prevalence of the parasympathetic tone during exercise or the influence of other factors [24,30,34,40]. LFnu is reported to remain unchanged or increased at low intensities of exercise and to significantly decrease when intensity increases [23,24,26,30,38,41]. The LF/HF ratio has been found unmodified at low exercise intensity [23,30] and decreased at higher intensities [22,25,41] although some authors found it increased [21,26,31,37,38]. A peculiar behaviour was that reported by Yamamoto et al [23] who showed that LF/HF ratio, measured during an incremental exercise, exhibited an initial increase at low exercise intensity followed by a decrease and a further progressive increase up to a peak when the exercise intensities exceeded 60% of ventilatory threshold (Tvent) work-load. It is clear from what reported above that results are not always consistent possibly for methodological differences mainly linked to the different intensity of exercise used [i.e. steady state, incremental etc.] and methods of assessment between different studies.

Effects of training and fitness level Effects of fitness level The effects of long term practice of aerobic training regarding the HR control concern especially the reduction in resting HR and the reduced HR at submaximal exercise intensities [8,42]. The exact causes of this exercise induced bradycardia are not completely understood, but several possible factors involved have been identified: a reduced intrinsic HR [43], an enhanced vagal tone to the sinus node [26] and possibly a decreased sympathetic outflow [44], although this is still being debated.

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Concerning healthy subjects, the most documented in the literature are the effects on HRV of aerobic training and results are generally coherent. There is large evidence that trained individuals display higher HRV values than untrained subjects so that aerobic training has been indicated as a useful intervention in many pathological conditions including post myocardial infarction patients [1,45,46]. Endurance trained subjects exhibit, for the time domain variables, higher NN intervals, SDNN, pNN50 and RMMSD [47-52] and for the frequency domain variables results though less consistent, are usually converging to the same conclusions, especially for what concerns HF and with some exception for the LF. In general total power, HF, LF are found to be higher [48,53,54], similar [37,51,52] and in one case reduced [49] in trained with respect to sedentary subjects. When expressed in normalised units, HFnu [37,42] has been found to be higher in trained compared to untrained subjects whereas LFnu has been found lower [26] and higher [55] in trained than untrained subjects. Furlan et al [55] explained this result with the fact that sympathetic activation, caused by physical exertion, can persist up to 24 hours after the end of exercise therefore causing the paradoxical phenomenon of a bradycardia coexisting with an augmented sympathetic activation. Janssen et al [47] who compared resting HRV in endurance athletes and controls found that differences in HRV between trained and untrained subjects were present in supine but not in standing position. Although the differences between trained and sedentary subjects might seem to suggest that training improves HRV and that aerobic training may represent an alternative to other form of therapy for cardiovascular disease, the direct evidence is still unavailable.

Effects of training Many studies have investigated the effects of training periods of various length, exercise mode and intensity and, for this reason, obtained not always constant and easily comparable results. The evidence seems to indicate that the duration, the frequency and the intensity of the exercise are key factors in determining the effects on HRV. For instance short term aerobic training of 8 weeks duration conducted 3 times a week produced no effects on HRV in older [33] and middle aged [56] subjects. By contrast, significant improvements in HRV has been reported in young subjects, adopting either 6 or 8 weeks of training but performing the training on a daily basis [57,58]. Considering longer training durations ranging from 16 [59] to 32 weeks [60-64] in most cases except one [65], training exercise has been reported to positively influence HRV irrespectively of the age of participants, although on this latter point the literature is not consistent. In fact, what is shown is that while in young individuals short-term aerobic training of as little as 6-12 weeks is sufficient to induce some changes in HRV, in middle-aged and elderly subjects

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positive effects of aerobic training on HRV are reported only following 24 [61,62], 30 [60] and 36 weeks [63], but not following 8 [33,56] or 20 weeks [65]. The fact that these studies elicited a significant increase in V O2max and/or a significant reduction in resting HR could indicate that the adjustments induced by training were more peripheral and not centrally mediated, hence not necessarily associated to changes in HRV and vagal outflow. This could suggest that, in older/middle aged individuals, positive effects of training on HRV are observed only following training periods above 5 months or adopting a more demanding training scheme, for instance by using daily sessions and/or increasing the training intensity. Regarding the effects of other forms of exercise the literature reports that aerobically trained athletes present higher values of HRV with respect to either their anaerobically/power trained or sedentary counterparts, possibly due to the above aerobically induced bradycardia [8,26,37,42,48-50,52,55]. Real comparisons between the effects on HRV of aerobic, anaerobic or strength training are, however, difficult to make due to the paucity of investigations regarding forms of training different from the aerobic one. In fact, only a few studies have investigated the effects of strength training and of power training reporting no effects on both time or frequency domain parameters both in young [66, 67] and in elderly subjects [68].

HRV, overtraining and fatigue It is worthwhile for the completeness of this article to briefly discuss the relationship between HRV, overtraining (OT) syndrome and fatigue. The condition defined as OT results from the imbalance between training load and the ability of the subject to recover. It has been demonstrated that OT causes a hormonal imbalance possibly arising from the attempt of the subject to cope with the excessive training load and leading to autonomic imbalance [69]. For this reason and based on the symptoms observed, Israel [70] defined two forms of OT: sympathetic, and parasympathetic. The former (Basedowian) being characterized by hyper function of the thyroid and increased sympathetic activity at rest and the latter (Addisonian) by increased vagal activity at rest and during exercise, both leading to reduced exercise performance. More recent studies, however, demonstrated that this original division appears to be too simplistic since the OT syndrome is now considered as due to multiple factors and not involving only an autonomic imbalance. Bearing in mind these limitations it would be consequential to think that HRV could represent a marker for the detection of OT syndrome. Despite this, research has not been able yet to identify changes in HRV due to OT and it is not clear if the autonomic imbalance caused by it is detectable through HRV assessment. The literature reports increased HF in an overtrained athlete [71] suggesting increased

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parasympathetic influence, while increased LF was found by Uusitalo et al. [72] on purposely overtrained athletes, but no modifications in time domain parameters were observed. In a short-term OT period no HRV modifications could be detected [73]. Interestingly a recent study reported no differences in HRV parameters between OT athletes and controls during night sleep but a significant reduction after awakening in the parasympathetic modulation [74]. From the available evidence it is not possible to draw definite conclusions since the research is still scarce especially for the difficulty in reproducing OT symptoms for experimental purposes. An alternative application to the OT studies is that concerning the use of HRV recording to monitor physical fatigue during periods of intensive training. In this regard, Pichot et al [75] demonstrated that HRV parameters, recorded during the nocturnal hours, were significantly modified during periods of intensive training in middle distance runners. They investigated a cycle composed by 3 weeks of intensive training followed by one week of reduced training. A global and progressive reduction in HRV both in time and frequency domain was observed during the 3 initial intensive training weeks, with a significant reduction in HF and HFnu and an increase in LFnu. By contrast, during the 4th week a dramatic augmentation in HRV was observed which paralleled the reduction in the training loads. Another study, however, involving high level cyclists did not produce similar results [51]. The athletes were tested before and after 5 months of intensive pre-competition training and although a significant increase in V O2max and a significant reduction in resting HR were observed, all the HRV indicators did not display any change.

Conclusions The importance of HRV as an important tool to discriminate between many cardiovascular diseases or different pathological conditions is well recognised. It is important, however, to be aware of the limitations when applied for other purposes since its definite physiological understanding appears far from complete. In particular, the assessment and interpretation of HRV during exercise remain still poorly standardized. The idea of assessing the sympathovagal balance during exercise merely via spectral analysis seems, on the base of the current research, to be unrealistic. Indeed, HRV during exercise is likely the result of the interplay of several cardio-respiratory influences to the heart and not just the autonomic nervous system. Another important confounding factor, which can significantly affect HRV, is represented by the different alterations in the hormonal balance present in subjects undergoing periods of intensive training, alterations also demonstrating peculiar gender-related characteristics. In conclusion, it can be suggested that further investigations will be necessary in order to establish the criteria for the determination of HRV during

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exercise and to monitor the effects of training and physical fatigue, before better standards can be set for future clinical and sport related applications.

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