INTRODUCTION

The processes of adaptation to physical loads that require endurance are influenced by the volume and intensity of training sessions; however, the nature of this influence from a physiological point of view was studied insufficiently [1, 2].

In view of above, the goal of this study was to assess by means of cardiointervalography (CIG) the nature of changes in the regulation of heart activity in an elite skier over three periods of the ski season (preparatory, competition, and transition) depending on the volume and intensity of the training load.

The method for assessing the state of the autonomic nervous system (ANS) by the heart rate variability (HRV) is widely used in clinical practice, and the interpretation of its main parameters has been described in detail in the literature [3–7].

In recent years, of the more than 30 HRV parameters, much attention has been paid to the spectral parameters of CIG [3–5, 7]. The latter include (1) the total power (TP) of the spectrum, reflecting the power of rhythm oscillations in the frequency range from 0.003 to 0.5 Hz, i.e., the total effect of the sympathetic (SP) and parasympathetic (PP) parts of the ANS and a number of biologically active substances (BAS); (2) the power of high-frequency (HF) waves, i.e., the power of oscillations with a frequency of 0.15 to 0.40 Hz, reflecting the influence of the PP of the ANS on the heart; (3) the power of slow (low-frequency, LF) waves, i.e., the power of oscillations with a frequency of 0.04 to 0.15 Hz, reflecting the effect of the SP of the ANS on the heart, which is modulated by the baroreflex; and (4) the power of very slow (very low-frequency, VLF) waves, ie., the power of oscillations with a frequency of 0.003 to 0.04 Hz, which probably reflects the complex effect of SO and PO of the ANS, as well as a number of BAS, on the heart. It is believed that the relative power of HF-, LF-, and VLF-waves, expressed as a percentage of TP (i.e., HF%, LF%, and VLF%), reflects the specific contribution of the corresponding parts of the ANS and BAS to the regulation of the activity of the heart.

CIG has been widely used in sports practice to assess the state of an athlete at training camps and competitions [8–11]. However, little attention has been paid to the dependence of HRV parameters in endurance athletes on the periods of annual training cycle (preparatory, competition, and transition) and the volume of training loads. In view of this, the goal of this study was formulated. Due to the fact that the transition period is usually implemented at home, CIG was performed in all three periods of the annual cycle on one elite skier K.D. (the first author of this article), taking into account the volume of his training loads in all three periods.

Before describing the methods and main results of this study, a number of important points should be noted.

It was noted [3, 9, 12, 13] that data on the dynamics of the absolute power of HF-, LF-, and VLF-waves, as well as the dynamics of the relative power of these waves expressed as a percentage of TP (i.e., HF%, LF%, and VLF%), for skiers during the annual cycle are scarce and ambiguous. For the TP value, it is shown that it varies from 1515 to 14486 ms2 and increases with the improvement of sportsmanship. Very little is known about the dependence of TP values on the period of the sports season and on the volume and power of the training load of athletes, although indirect data from a number of authors indicate that, in the preparatory period (i.e., at high training volumes), the activity of the PP of the ANS in elite skiers continues to increase [9, 14, 15]. This is consistent with the idea that endurance training increases the activity of the PP of the ANS [3, 9, 14, 15]. However, the issue of the specific mechanisms of vagotonia formation during endurance training requires a detailed study. From this standpoint, it is of great interest to analyze HRV parameters in elite athletes throughout all three periods of their next annual cycle (season) taking into account the volume and power of training, which was the main goal of this study.

It is important to note that the volume and intensity of training loads are expressed in different ways. Foreign authors [11, 16–19] estimate the load volume by the duration of training (min/day; h/day), whereas Russian authors [20, 21] estimate it by the length of the training path (km/day). The intensity or power of load is estimated by the “working pulse” value [11, 17, 21, 22]. It is generally accepted [23, 24] that the working pulse values can reflect five intensity zones, the first three of which (50–80% of HRmax) are regarded as low-intensity zones, and zones 4 and 5 (i.e., higher than 80% of HRmax) are regarded as high-intensity zones. The annual volume of training loads of elite skiers is huge: it varies from 700 to 937 h [17, 18] or from 9150 to 9493 km [21, 22]. The training load volume for each elite cross-country skier is individual, because it depends on the level of training, rate and quality of recovery processes, and other factors [24, 25]. The goal of the coach and athlete is to come to the crucial (prestigious) start with the maximum level of readiness [24].

MATERIALS AND METHODS

The study involved a 27-year-old cross-country skier (K.D.), master of sports of Russia, member of the Tatarstan cross-country skiing team, multiple champion and prize-winner of all-Russian and international ski racing competitions among juniors and youths. K.D. has 17 years of experience in cross-country skiing. The studies were performed from March 2019 to June 2020.

The physical performance of K.D. was tested in a sports dispensary in Kazan on a Concept2 SkiErg ski simulator (United States), which simulates the movements of a simultaneous stepless skiing. It was found (Table 1) that, when exhaustive muscular work in a stepwise increasing manner until “failure” was performed at the beginning of the preparatory period (June 2019), the maximum oxygen consumption (MOC) was 64.5 mL/kg or 4418 mL; the aerobic threshold (AeT), i.e., the heart rate (HR) at which there is still no rise in lactate during muscle exercise, was 113 bpm; the anaerobic threshold (AnT), i.e., the HR at which lactate concentration began to rise was 171 bpm; the maximum heart rate (HRmax), which is achieved when performing work of maximum power (when load increases every 2 min by 20 W), was 185 bpm; the maximum operating power (Nmax) reached 290 W, and the maximum rise in the lactate concentration (Lmax) was 8.52 mM. A similar test performed at the end of the summer–autumn training, i.e., before “enrolling” (October 2019) showed (Table 1) that the MOC was 69.3 mL/kg or 4845 mL, AeP was 111 bpm, Anp was 164 bpm, HRmax was 185 bpm, Nmax was 310 W, and Lmax was 10.7 mM. Tests on a treadmill with a track slope of 10° at stepwise increasing loads (every 2 min) until “failure” showed (Table 1) that, at the beginning of the preparatory period (June 2019), the MOC was 65.8 mL/kg or 4740 mL, AeP was 154 bpm, Anp was 170 bpm, HRmax was 188 bpm, the maximum running speed for 2 min was 12 km/h, and Lmax was 9 mM. At the end of the summer–autumn preparatory period (October 2019), the MOC was 74 mL/kg or 5173 mL, AeP was 142 bpm, Anp was 170 bpm, HRmax was 192 bpm, the maximum running speed for 2 min was 13.5 km/h, and Lmax was 9.48 mM. Thus, tests of the physical performance of athlete K.D. on the Concept2 SkiErg ski simulator and on the treadmill showed similar results, which give grounds to postulate that (1) athlete K.D., indeed, belongs to the group of elite ski racers and (2) during the preparatory period, his performance increases.

Table 1.   Assessment of the level of physical performance and functional state of the key energy supply systems of athlete K.D. during implementation of exhaustive muscular work of a stepwise increasing nature to “failure” (on the Concept2 SkiErg ski simulator and treadmill, according to the data of the sports dispensary (Kazan))
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According to the literature, the absolute MOC values in six Swedish elite cross-country skiers were 5.1 ± 0.1 L/min [26–28].

Importantly, the training camps (TCs) and competitions were held in different regions of Russia and abroad, including the plains and mountains (Table 2). During these trainings, the first author of this article (i.e., athlete K.D.) recorded the volume and power of his training loads and performed self-recording of CIG.

Table 2.   Schedule and places of training camps (TCs) and competitions of athlete K.D. in 2018–2019 and 2019–2020 seasons
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The volume of training loads (Vkm, Vmin) of athlete K.D. for each day that preceded the morning CIG recording, was evaluated by summing up the time spent on all workouts and morning exercises, which was expressed in min/day (Vmin), as well as in kilometers of cross-country skiing, roller skiing, or cross-country running (Vkm). The intensity or power (NHR) of the training loads was assessed by the mean HRwork recorded during each training session with a POLAR 430 heart rate monitor equipped with a GPS sensor (POLAR, Finland). According to the POLAR programs, the HRwork value made it possible to attribute the load intensity to one of the five training zones specified above [23, 24].

It should be noted that 5-min CIG self-recording was performed in the subjects in the supine position after night sleep (before breakfast) in comfortable conditions using a VNS-Micro system (Neurosoft, Russia), and CIG analysis was performed using the Poly-spectrum software (Neurosoft, Russia). Along with other parameters, we evaluated the following HRV parameters: the total power of the spectrum (TP, ms2); the absolute power of HF-, LF-, and VLF-waves (ms2), as well as the relative power of these waves expressed as a percentage of TP (i.e., HF%, LF%, and VLF%). The assessment of these parameters was formed by summing up the results of individual studies conducted in each month of the corresponding period, which made it possible to evaluate statistically significant differences between the values of the parameters recorded in one month (period) from those recorded in another month (period). In total, athlete K.D. performed 217 CIG self-recordings, of which 84 were performed during the preparatory period, 74 during the competition period, and 59 during the transition period. All these HRV parameters, as well as Vmin, Vkm, and NHR were calculated for each month of the annual cycle and in general for each of the three periods (preparatory, competition, and transition) of the annual cycle. They were expressed as the median and 25 and 75 percentiles [29]. Differences were assessed using the Mann–Whitney test and considered statistically significant at p < 0.05 [29]. Calculations, including the calculations of Spearman correlation coefficient [29], were performed using the BioStat2009 Professional ver. 5.9.8 software (AnalystSoft, United States).

RESULTS

The main results of the study are summarized in Table 3 and in Figs. 1, 2.

Table 3.   Median, 25th and 75th percentiles (bottom row) of the volume (Vkm, Vmin) and intensity (NHR) of training loads of elite skier K.D. by months, as well as TP (ms2), absolute power of HF-, LF-, and VLF-waves (ms2), and relative (in % of TP) power of these waves (according to cardiointervalography data under clinostasis conditions)
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Fig. 1.
figure 1

Dynamics of the values of the total power of the wave spectrum (TP, ms2, columns) and the values of the volume (Vkm) of the training load (linear plot) of the elite skier K.D. The numbers in the columns reflect the months (top) from which this month (bottom) differs statistically significantly in TP values (according to Mann–Whitney test, p < 0.05), according to the results of cardiointervalography performed under clinostasis conditions.

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Fig. 2.
figure 2

Dynamics of the values of the median total power TP (ms2), the absolute power of HF-, VLF-, and LF-waves, and the relative power of these waves expressed as a percentage of TP (i.e., HF%, VLF%, and LF%) of elite skier K.D. in the preparatory (1), competition (2), and transition (3) periods (the 1st, 2nd, and 3rd columns, respectively), according to the results of cardiointervalography performed under clinostasis conditions. Asterisks above the columns mean that the differences with the competition (*) and/or transition (**) periods are statistically significant according to Mann–Whitney test.

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It was established (Table 3, Fig. 1) that the volume of training loads of athlete K.D., expressed in km of the path (Vkm), in the preparatory period was significantly higher (p < 0.05) than that in the competition period (median, 21 vs 19 km/day) and higher than in the transition period (18 km/day, p > 0.05). However, the load volume, expressed as Vmin, was approximately the same in all periods (judging by the fact that the differences between the periods of the annual cycle were statistically nonsignificant), although it had a wave-like dynamics (in the preparatory, competition, and transition periods, the median was 106, 82, and 105 min/day, respectively). In general, the annual (from June 2019 to May 2020) load volume of athlete K.D. amounted to 622 h. Thus, the training load volume of athlete K.D. in all study periods was relatively low as compared to the load volume of famous elite cross-country skiers [11, 17, 18, 20, 21], which is associated with the coach’s recommendations to reduce the load due to the coronavirus pandemic (from March to June 2020).

The training load intensity, judging by the values of the working heart rate (NHR) in all periods of the annual cycle, was relatively constant: the median HRwork in the preparatory, competition, and transition periods was 121, 121, and 120 bpm, respectively. Taking into account the division to five zones of load intensity [22, 23], 41.4% of training sessions were attributed to zone 1 (97–116 bpm); 37.0% to zone 2 (117–135 bpm), 15.1% to zone 3 (136–154 bpm), 4.8% to zone 4 (155–174 bpm), and 1.7% to zone 5 (175 bpm).

When analyzing the values of TP, as well as the absolute and relative power of the HF-, LF-, and VLF-waves of athlete K.D., recorded under clinostasis conditions, the following general patterns were established: (1) the values of these parameters depend on the period of the annual cycle, with each parameter being characterized by its own dynamics; (2) within each period, the values of the parameter periodically (from month to month) change (sometimes increase and sometimes decrease); i.e., their dynamics is oscillatory (Table 3, Fig. 1).

The analysis of the dynamics of the median TP in athlete K.D. (Table 3, Fig. 2) showed that, in the preparatory (9473 ms2) and competition (8047 ms2) periods, it was higher than in the transition period (6961 ms2; p < 0.05), whereas the differences between the preparatory and competition periods were statistically nonsignificant. Within the preparatory and transition periods, the TP values changed from month to month, but in the competition period they were relatively stable (Fig. 1). In each of the three periods, there was no statistically significant dependence of TP values on the volume and intensity of training loads. However, over the entire annual cycle in general, a significant (p < 0.05) dependence of TP on the training load volume (Vkm) and load intensity (NHR) was found (the Spearman coefficient was +0.18 and +0.17, respectively). This suggests that, as the volume of training loads (Vkm) and their intensity (NHR) increase, the median TP recorded under clinostasis conditions increases. The identified TP dynamics, taking into account literature data on the nature of TP [3, 7, 16] and our data on the median absolute and relative power of HF-waves in athlete K.D. (similarly to other members of the Tatarstan national ski team), indicates that the activity of the PP of the ANS in elite skiers during the sports season is very high. However, it undergoes certain changes: increases in the preparatory period, remains at this level in the competition period, and decreases in the transition period.

It was established (Table 3, Fig. 2) that the median absolute power of HF-waves (AMHF), reflecting the effect of the PP of the ANS on the heart, was 3793 ms2 in the preparatory period, 3519 ms2 in the competition period, and 3371 ms2 in the transition period. The differences between the preparatory and transition periods were statistically significant (p < 0.05). This is consistent with the literature data, according to which, with an increase in the skill of a cross-country skier, the value of this parameter increases, which is much higher than that of athletes in team sports and martial arts [30]. We found no dependence of AMHF on the volume (Vkm, Vmin) and power (NHR) of the load, including over the entire annual cycle in general (Spearman’s coefficient was +0.12, +0.12, and +0.10, respectively). Thus, AMHF (i.e., the absolute power of HF-waves) increases in the preparatory period, remains elevated in the competition period, but decreases in the transition period, when the volume and intensity of training loads decrease. Taking into account the nature of HF-waves [3–5, 7] it can be postulated that the dynamics of the median AMHF recorded in clinostasis indirectly indicates an increase in the effect of the PP of the ANS on the activity of the heart under the influence of endurance training and a decrease in this effect with a decrease in the volume of training loads.

It was shown (Table 3, Fig. 2) that the median relative power of HF-waves (i.e., HF%) was 44.7% in the preparatory period, 41.7% in the competition period (differences between them were statistically significant, p < 0.05), and in the transition period it increased statistically significantly to 47.3% (p < 0.05). This means that, in the preparatory and especially in the competition periods, the median HF% decreases, whereas in the transition period it increases, which may be due to a decrease in the influence of the SP of the ANS on the work of the heart in the transition period. We found no statistically significant dependence of the median HF% on the volume (Vkm or Vmin) and intensity (NHR) of training loads, including for the annual cycle (Spearman’s correlation coefficient was –0.12, –0.03, and –0.09, respectively).

It was found (Table 3, Fig. 2) that the median absolute power of LF-waves (AMLF), which, in opinion of the authors of [3–5, 7], reflects the effect of the SP of the ANS on the heart, was 1962 ms2 in the preparatory period, 2032 ms2 in the competition period, and 1480 ms2 in the transition period. The differences between AMLF values in the preparatory and competition periods were nonsignificant (p > 0.05), whereas the differences between this parameter in these two periods and in the transition period were statistically significant (p < 0.05). Thus, the absolute power of LF-waves increased in the preparatory period, remained at this level in the competition period, and decreased in the transition period. We found no dependence of AMLF on the volume (Vkm, Vmin) and intensity (NHR) of the load, including for the entire annual season in general (Spearman’s coefficient was +0.11, +0.08, and +0.09, respectively). Taking into account the genesis of LF-waves [3–5, 7], it can be postulated that the dynamics of the median AMLF indirectly indicates that endurance training increases the effect of the SP of the ANS on the activity of the heart during CIG registration in clinostasis. This is due to the formation of anxiety in the preparatory and, especially, competition periods before the starts, and a decrease in this feeling in the transition period.

It was established (Table 3, Fig. 2) that the median relative power of LF-waves (LF%) was 22.5% in the preparatory period, 24.5% in the competition period (the differences between them were statistically significant, p < 0.05), and 21.7% in the transition period (differences between the preparatory and transition periods were nonsignificant). This means that the median LF% in the preparatory period remains at the same level as in the transition period, in the competition period it increases, and in the transition period it decreases again, although statistically nonsignificantly. We found no dependence of the median LF% on the volume (Vkm, Vmin) and intensity (NHR) of training loads, including the annual cycle in general (Spearman’s correlation coefficient was –0.01, +0.02, and +0.01, respectively).

We found (Table 3, Fig. 2) that the median absolute power of VLF-waves (i.e., AMVLF), which apparently reflects the effect of BAS on the heart [3–5, 7], was 2818 ms2 in the preparatory period, 2622 ms2 in the competition period, and 1874 ms2 in the transition period. The differences between the median AMVLF in the preparatory and competition periods were nonsignificant (p > 0.05); however, the differences between the values of this parameter in these two periods and in the transition period were statistically significant (p < 0.05). Thus, AMVLF (i.e., the absolute power of VLF-waves) increases in the preparatory period, remains at this level in the competition period, and statistically significantly decreases in the transition period. This dynamics in many aspects is similar to the dynamics of median TP and median AMHF. We established the dependence of the absolute power of VLF-waves on the volume (Vkm) and intensity (NHR) of the load throughout the entire annual cycle in general, whereas the dependence on the load volume expressed in minutes (Vmin) was not found (Spearman’s coefficient was +0.19, +0.14, and +0.09, respectively).

Analysis of the dynamics of the median relative power of VLF-waves (i.e., VLF%) showed (Table 3, Fig. 2) that VLF% values in athlete K.D. varied throughout the season from 24.1 to 49.1%. In the preparatory and competition periods, the contribution of VLF% to the total spectrum was equally high, i.e., higher than in the transition period (median VLF% were 32.6 and 32.8%, respectively, with no differences between them, р > 0.05) and lower in the transition period (median, –27.7%; p < 0.05). In the preparatory period, a statistically significant dependence of the median VLF% on the volume of training loads (Vkm) was revealed (Spearman’s coefficient was +0.24 (p < 0.05)). This indicates that, with an increase in the volume of training loads (Vkm), the median VLF% increases. However, for the competition and transition periods, this dependence was statistically nonsignificant (Spearman’s coefficient was +0.05 and –0.17, respectively). Probably for this reason, for the annual cycle in general, we found no dependence of VLF% on the volume of the load (Vkm or Vmin) and on its intensity (NHR) (Spearman’s coefficient was +0.12, +0.02, and +0.05, respectively).

DISCUSSION

Regarding the interpretation of the results of the study of the elite skier K.D., five important points should be noted.

(1) It can be assumed that the values of TP, the absolute power of HF- and VLF-waves, and especially the relative power of VLF-waves (i.e., VLF%) reflect the degree of influence of the PP of the ANS on the heart, because the effect of the PP of the ANS on the heart in elite skiers is significantly higher than in non-athletes or in beginner skiers [3, 9]. This statement is consistent with the generally accepted idea that endurance training significantly increases the activity of the PP of the ANS [2, 14, 15].

(2) Taking into account modern ideas about the ability of the myocardium [31–35] and other tissues [36] to synthesize acetylcholine (ACh), i.e. non-neuronal ACh, it can be assumed that vagotonia, which is characteristic of endurance athletes [2, 14, 15], is due to the fact that, during training, the effect of the PP of the ANS on the heart increases, and the myocardium acquires the ability to synthesize ACh. It is known [31–33] that synthesized ACh is a potent antioxidant that is involved in the elimination of free radicals generated during intense activation of β1-adrenergic receptors during physical load. This ultimately increases the viability of cardiomyocytes, causes physiological hypertrophy of the myocardium, and increases the performance of the heart as a pump. Evidence for the role of non-neuronal ACh in the origin of sports vagogonia is the published data [3, 37] on the increase in VLF% values with an increase in sportsmanship. We have shown that the increase in VLF% in athlete K.D. is associated primarily with an increase in the volume of training loads. This means that ACh synthesis in cardiomyocytes is probably activated during high-volume exercise. From this standpoint, the idea of some authors [3–5, 7, 38, 39] that the power of VLF-waves reflects the involvement of humoral factors in the regulation of the activity of the cardiovascular system probably most accurately reflects the nature of VLF-waves.

What underlies the appearance of the ability of cardiomyocytes to synthesize ACh? Obviously, from the standpoint of the body’s adaptation to the loads that require high endurance (i.e., high intensity of adenosine triphosphate resynthesis for a relatively long time), a high level of antioxidants and factors that prevent apoptosis is required. This property is characteristic of ACh [7, 32–34]. It is also known that the synthesis of ACh requires two initial components: choline, which is formed from membrane lipids, and acetyl, which is formed from acetylcoenzyme A, the main source of which is the Krebs cycle [40]. It is known that endurance training increases the intensity of mitochondrial biogenesis, which leads to an expansion of the mitochondrial network both in skeletal muscles and in the myocardium [41–45]. This creates conditions for the constant synthesis of ACh in cardiomyocytes, which is probably facilitated by the increase in the expression of the gene for choline acetyltransferase, which is involved in the synthesis of ACh, in cardiomyocytes [31, 33, 34, 40]. Thus, we can put forward a hypothesis that the increase in TP values and, especially, in the relative power of VLF-waves (i.e., VLF%), which is characteristic of elite skiers, reflects the formation of non-neuronal ACh synthesis in cardiomyocytes. However, this hypothesis requires more solid evidence.

(3) Our data show that, when CIG is recorded under clinostasis conditions, the greatest contribution to the total power spectrum (i.e., TP) is made by HF-waves (41.7–47.3% of TP). VLF-waves rank second (27.7–32.6%), and LF-waves rank third (21.7–24.5%). Apparently, in conditions of physical activity, this TP structure will be different, and LF-waves, which reflect the activity of the SP of the ANS modified by the baroreflex, will rank first.

(4) When recording CIG under clinostasis conditions (i.e., in conditions close to basal metabolism), the activity of the sympathetic system is naturally much lower than during physical load. Therefore, the change in the absolute and relative power of LF-waves, detected in the course of the skier’s annual cycle during clinostatic CIG recording most likely reflects the emotional state of the athlete, including the formation of emotions such as anxiety. In general, this state reaches its maximum in the competition period, which indirectly affects the dynamics of the absolute and relative power of HF-waves, but does not affect the dynamics of the absolute and relative power of VLF-waves, which reflects primarily the level of production of the non-neuronal ACh by cardiomyocytes.

(5) This point has an applied value. It can be assumed that, if an increase in TP and AMHF values without an increase in VLF% is observed on a CIG of a skier recorded during training under clinostasis conditions, this means that the effect of the PP of the ANS on the heart, indeed, increases, but the synthesis of non-neuronal ACh is not yet activated. If VLF% values increase simultaneously with an increase in TP and AMHF values, this means that the non-neuronal ACh in the myocardium of the athlete is synthesized. Of course, this assumption requires rigorous proofs, which, most likely, can only be obtained in experiments on animals.

CONCLUSIONS

(1) Multiple CIG recordings under clinostasis conditions in an elite skier K.D. throughout the annual cycle, which allows to evaluate HRV such parameters such as TP, absolute (ms2) and relative (as a percentage of TP) power of LF-, HF-, and VLF-waves, as well as fixing the volume of training loads (by the path length (Vkm) or by their duration (Vmin)) and the intensity of loads (by HRwork) showed that the volume of training loads is maximum in the preparatory period (21 km/day or 106 min/day), decreases in the competition period (19 km/day or 82 min/day), and remains at this level (18 km/day) or even increases (105 min/day) in the transition period. The intensity of the training loads in all periods of the annual cycle is uniform: in the preparatory and competition periods, the HRwork is 121 bpm, and in the transition period it is 120 bpm.

(2) In the preparatory period, simultaneously with the increase in the volume of training loads, the medians of TP, the absolute power of HF-, LF-, and VLF-waves, as well as the relative power of VLF-waves (i.e., VLF%) increase. The relative power of LF-waves (LF%) remains low, and the relative power of HF-waves (HF%) decreases. It was found for this period that VLF% values increase with an increase in the volume of training loads (Vkm).

(3) In the competition period, against the background of a consistently high volume of training loads, the medians of TP, the absolute power of HF-, LF-, and VLF-waves and the median VLF% remain at a high level, whereas the median HF% remains at a low level and the median LF% increases.

(4) In the transition period, with a decrease in the volume of loads, the medians of TP, the absolute power of HF-, LF-, and VLF-waves, as well as the medians of LF% and VLF% decrease, whereas the median HF% increases.

(5) For the annual cycle in general, we found a direct dependence of the median TP on the volume of loads, Vkm (the higher the volume, the higher the median TP), as well as a direct dependence of the median absolute power of VLF-waves on volume (Vkm) and intensity (NHR) of the load.

(6) A hypothesis was formulated that the TP, HF-, LF-, and VLF-waves, as well as VLF% values recorded under clinostasis conditions reflect the effect of the PP of the ANS on the activity of the heart, and VLF% probably reflects the intensity of synthesis of non-neuronal acetylcholine by cardiomyocytes, whereas the LF% and HF% values reflect the formation of anxiety due to the upcoming starts.