Postgraduate A.A. Kozlov
Dr.Biol., Professor J.A. Povareshchenkova
National State University of Physical Culture, Sport and Health named after P.F. Lesgaft, St. Petersburg

Keywords: competitive success rates, heart rate variability, aerobic/ anaerobic indices, prefight conditioning process, boxing.

Introduction. Competitive success rating systems based on the individual current functionality analyses are rated among the most promising ones in modern physiology.

Objective of the study was to identify the physiological status indicators that could be applied for the professional boxer’s potential capacity mobilization forecasts.

Methods and structure of the study. Subject to the study was a Russian professional heavyweight boxer, the 2012-2013WBA title holder, who gave his informed consent for participation in the study as required by the relevant provisions of the Helsinki Declaration and the international laws. Data readings were taken in morning hours for the period of 196 days. Heart bioelectrical activity rates were recorded using a portable wireless single-channel amplifier under the regular conditions of the high-quality ECG recording standards. The data processing and analyses were designed as provided by the relevant internationally accepted standards [2] with account of the updated methodology offered by domestic researchers [1]. In addition, the study was designed to calculate aerobic, anaerobic and metabolic indices. Aerobic index means herein the ratio of the R-peak amplitudes to the summarized R- and S-peak ECG amplitudes preliminary filtered as provided by the relevant patented ECG filtration procedure. Anaerobic index means herein the ratio of the maximum and minimum T-peak amplitudes to the summarized R- and S-peak amplitudes on the filtered ECG diagram; and metabolic index means the adjusted average QRS-peak amplitudes with the S-peak weight in the formula being automatically reduced (the applied formulae are protected by the USA Patent # 6,572,558 В2).

Study results and discussion. The subject boxer’s aerobic indices were found to significantly (p<0.001) fall by 0.007 standard units (0.7%) per day staying within the range of 115 to 132 standard units (s.u.) as compared to 110-160 s.u. typical for healthy individuals. The relevant regression equation was the following: Aerobic index = - 0.007 * 196 + 130.3. The anaerobic indices were found to significantly (p<0.001) grow by 0.006 standard units per day staying within the range of 136 to 148 units as compared to the 132-162 typical for healthy individuals. The relevant regression equation was the following: Anaerobic index = 0.006 * 196 + 138.39. The metabolic indices were found to significantly (p<0.001) fall by 0.074 standard units per day staying within the range of 133 to 476 s.u. The metabolic index falling trend was interpreted as indicative of a significant mobilization of the muscular energy supply systems in the prefight conditioning period. The relevant regression equation was the following: Metabolic index = - 0.074*196+399.25.

The heart rate variability (HRV) values as verified by the ECG spectral indices were profiled for the whole study period. Total power of the spectrum (ТР) was found to significantly (p<0.05) fall by 0.495 ms² per day. The TP variation trend for the study period of 196 days was found indicative of the work capacity sagging pattern that is quite natural for a high-intensity training process. The relevant regression equation was the following: Total power of the spectrum = - 0.495 * 196 + 1408.35.

The LF/HF ratio was found to significantly (p<0.001) fall by 0.003 units per day. The vagosympathetic balance ratios at the onset of the study were found to be notably higher than normal as verified by the excessive activity rates of the sympathetic nervous system. The relevant regression equation was the following: Vagosympathetic balance ratio = - 0.003 * 196 + 4.272.

The LF-waves are commonly interpreted as characteristic of the cardiostimulator centre and vasoconstrictive centre activities in the medulla oblongata. The low-frequency component of the HRV characteristic of the vascular tonus regulation system status was found to significantly (p<0.001) fall by 0.491 ms² per day in the study period. The relevant regression equation was the following: LF = - 0.495 * 196 + 865.100.

The study revealed the vagal regulator mechanisms activity rates (SDNN, RMSSD, HF) sagging trend (p>0.05). A few other indices including mode amplitude, tension index, aperiodic impact index and respiratory wave amplitude dispersion index – were found to slightly grow at the same time (p>0.05).

Fights 1, 3 and 4 were victorious in the study period (see Figure 1 (a), (b), Linear Aerobic1, Aerobic4 and Aerobic3 lines, respectively), and Fight 2 ended up with defeat (see Figure 1 (b), Linear Aerobic2).

We used One Way RM ANOVA method for inter-stage comparisons of the prefight conditioning stages within the study period. Every pair comparisons of the relevant indices were performed using the Holm-Sidak method. The study found that the aerobic indices in the pre-Fight 1 versus the pre-Fight 2 conditioning stages were 3.478 units different (p<0.001); that in the pre-Fight 1 versus the pre-Fight 3 conditioning stages were 4.967 units different (p<0.001); that in the pre-Fight 1 versus the pre-Fight 4 conditioning stages were 4.023 units different (p<0,001); and that in the pre-Fight 2 versus the pre-Fight 3 conditioning stages were 1.489 units different (p<0.006). The differences of these indices for the prefight conditioning stages 3 versus 4 and 2 versus 4 were found insignificant.

Figure 1. Aerobic index variations at prefight conditioning stages, standard unis (s.u.)

The anaerobic index variation trends for the pre-Fight 1, 3 and 4 conditioning stages may be described as one-way trends, in contrast to the pre-Fight 2 conditioning stage. The anaerobic indices in the pre-Fight 1 versus the pre-Fight 3 conditioning stages were 2.284 units different (p<0.001); that in the pre-Fight 1 versus the pre-Fight 4 conditioning stages were 3.544 units different (p<0.001); that in the pre-Fight 2 versus the pre-Fight 4 conditioning stages were 2.587 units different (p<0.001); whilst that in the prefight conditioning stages1 versus 4; 3 versus 4; and 2 versus 3 were found insignificant.

Conclusion. An athlete’s functional state monitoring system may be used not only to rate the athlete’s health, “costs” of adaptation progress under physical loads and the training process efficiency, but to forecast the physiological state contribution to the competitive success rate. Since a regression analysis of a whole yearly preparatory training cycle can unlikely provide a clear picture of the relevant index variation trends to rate the athlete’s functional status, it will be beneficial to break the study period into stages relating to the focused prefight conditioning cycles. The physiological data profiles versus the actual competitive success rates of the fights give good grounds to consider the aerobic and anaerobic indices as the most informative criteria for the professional boxer’s functional capacity mobilization and competitive success forecasts. The study demonstrated the grown aerobic indices and lowered anaerobic ones at the prefight conditioning stages being indicative of a high competitive fitness level of the athlete. 

References

1. Baevskiy R.M. Adaptatsionny potentsial sistemy krovoobrashcheniya i voprosy donozologicheskoy diagnostiki (Adaptive capability of circulatory system and issues of preclinical diagnostics) / R.M. Baevskiy // Problemy adaptatsii detskogo i vzroslogo organizma: Ed. by prof. R.R. Shiryaev. – Moscow: Meditsina, 1990. – 367 p.
2. Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of The European Society of Cardiology and The North American. Society of Pacing and Electrophysiology // European Heart Journal.1996; 17: 354-381.

Corresponding author: p_j_a@mail.ru

Abstract
Today top priority is being given in sport science to the most informative indicators that could be used as the individual competitive success rate predictors. The study offers a set of aerobic/ anaerobic indices that may be beneficial for use in professional boxing sport. For the index calculation purposes, a prior bioelectric data profiling analysis was performed using the Omegawave Team+ V4.5 (Finland-made) software toolkit. An amplitude frequency analysis was applied to process the heart bioelectrical activity profiling data obtained by the above method. Aerobic index means herein the ratio of the R-peak amplitudes to the summarized R- and S-peak amplitudes. The physiological interpretations of the aerobic index variations are based on the depolarization rates of the right and left ventricles of heart (ventriculus cordis) known to be in correlation with the aerobic workability rates of athletes. Anaerobic index means herein the ratio of the maximum and minimum T-peak amplitudes to the summarized R- and S-peak amplitudes. The study found that the aerobic and anaerobic index variations in the prefight professional boxer conditioning process show opposite trends. Furthermore, the study demonstrated that the growing aerobic indices and sagging anaerobic ones in the prefight conditioning period are beneficial as they were found to be in direct correlation with the competitive success rates. The aerobic and anaerobic indices were shown to give good grounds to forecast the professional boxer’s functional capacity mobilization rates and thereby rate the efficiency of the prefight conditioning process.