Athletes Preparation based on a Complex Assessment of

Functional State

Zinaida Kuznetsova

, Aleksander Kuznetsov

, Ilsiyar Mutaeva

, Gazinur Khalikov

and Anna Zakharova

Naberezhnye Chelny Institution of Educational Technologies and Resourses,

Nizametdinova street, Naberezhnye Chelny, Russia

Institute of Physical Education, Sport and Youth Policy, Ural Federal University, Mira Street, Ekaterinburg, Russia

Keywords: Middle Distance Runners, a Functional State, Physical Working Capacity, a Psychofunctional State, Heart

Rate Variability, the Correlation Analysis, the Factorial Analysis.

Abstract: Modern training of middle distance runners is characterized by significant increase in loading intensity

owing to strengthening of the sports competition. Absence of the athletes’ functional state complex

diagnostics complicates the process of training and competitive loadings planning which can lead to failure

in adaptation. Middle distance runners functional state assessment is considered in the article. Methods of

functional diagnostics: polymyography, HR variability with active orthostatic test, research of physical

working capacity (PWC170 test), the express -diagnostics of a functional state by Dushanin's method and

the "Reaction to Moving Object" (RMO test). Research material. Physical working capacity is estimated by

means of the PWC170 test, a psychofunctional state by the "RMO" test, an assessment of neuromuscular

system by "Rehabilitation and diagnostic RDK-2 complex", an assessment of HR variability was done with

active orthostatic test. Results. Complex diagnostics of the runners’ functional state and its further complex

assessment by means of the received indices were carried out. The runners’ functional state improvement in

the experimental group from the 1st to the 3rd investigation phase is observed. The correlation and factorial

analysis of the indices is carried out, the model scale of a functional state assessment is developed.

1 INTRODUCTION

Training is recognized as a process which prepares

an athlete for the highest possible level of

performance. Training of elite athletes is a versatile

and multi-factorial process of effective use of the

whole combination of factors, including selection of

means, methods and conditions, innovation

technologies, ensuring proper adaptation effect on an

athlete and the appropriative means for control of

the level of their readiness for sport activity.

As the sport training attempts to lead the athletes

to their genetics upper limits it must provide an

appropriate stimulus for adaptation. The analysis of

scientific-methodological and specialized literature

revealed that middle-distance running is

characterized by the significant growth of the

volume and intensification of training loads. Their

further increase can result in failure of adaptation,

overtraining and pathological changes of the body

functional systems (Konovalov, 1999; Wilmore,

Costill, 2001; Makarova, 2002). The above-stated

promotes the conclusion that management of

athletes training lacks information on the integrated

assessment of body's functional state.

In this regard, complex assessment problem of

sportsmen functional state is very interesting.

Control and assessment of functional readiness as a

multifactor system has to be carried out in a complex

of making main components (motor, the energy, the

neural dynamic and mental).

Thus, we determined the purpose of our research

– development and experimental justification of

track and field runners method on middle distance

on the basis of the functional state complex

assessment.

Research Organization. The research was

conducted on the basis of Povolzhskaya State

Academy of Physical Culture, Sport and Tourism

laboratory. Middle distance runners total of 30

people (15 athletes in the control group and 15 in the

experimental group) took part in this research.

The research was conducted in 3 stages.

156

Kuznetsova, Z., Kuznetsov, A., Mutaeva, I., Khalikov, G. and Zakharova, A..

Athletes Preparation based on a Complex Assessment of Functional State.

In Proceedings of the 3rd International Congress on Sport Sciences Research and Technology Support (icSPORTS 2015), pages 156-160

ISBN: 978-989-758-159-5

2 METHODS

For definition the functional state of the athletes we

used several methods and means (hardware and

software systems (HSS)):

- for definition of physical working capacity we

used the Test PWC170.The investigated exponents:

absolute maximal oxygen consumption (VO2),

relative maximal oxygen consumption (relative

VO2), index PWC170, PWC170 relative (PWC170

rel.), assessment of the recovery period;

- for definition of psychofunctional state we used

the test «Reaction to a moving object» (RMO) on

device “Activatsiometr AC-9K”, created by U.A.

Tsagarelly (Russia). The parameters: accuracy of

RMO, tendency of RMO to lag (ten. RMO to lag),

tendency of RMO to advance (ten. of RMO to adv.),

variation range;

- for definition of the heart rate variability (HRV)

indicators with an active orthostatic test (AOT) we

used electrocardiograph Poly-Spektrum-8/EX and

software Poly-Spectrum-Rhythm. Determined: heart

rate at rest (HR), indicators of spectral analysis(ТР –

total power, %VLF – very low frequency, %LF –

low frequency, %HF – high frequency),stress index

(SI), coefficient K30:15.

- the level of athletes functional state with the

help of device «D&K-Test» by S.A. Dushanin’s

method. Indicators of: anaerobic metabolic capacity

(ANMC), aerobic metabolic capacity (AMC),

overall metabolic capacity (OMC), power of

creatinephosphate source of energy supply, power of

glycolytic source of energy supply (PGL), power of

aerobic source of energy supply (PASES), HR on

the threshold level of anaerobic metabolism (HR

TLAM) were determined.

- for definition of the neuromuscular system

(NMS) functional state we used HSS “Rehabilitation

and diagnostic system RDK-2” and the method of

polymyografiya, which was created by Y.V.

Visochin (Russia). Indicators were defined: speed

arbitrary intension of relative (SAIr), coefficient of

maximum of relative arbitrary power (CMVPr),

speed of arbitrary relaxation (SAR), integrated

parameters: the functional state of the muscles

(FSm), the functional state of the neuromuscular

system (FSnms), the functional state of the central

nervous system (FStcns).

We conducted mathematical and statistical

analysis of the data.

3 RESULTS

The complex diagnostics functional state of the

middle and long distance runners has been

conducted in the first stage of our research. At the

first stage of the study PWC170 tests with physical

load were fulfilled in order to determine the level of

physical working capacity. There were no significant

differences in physical working capacity between

two groups. In the control group (CG) PWC170

equaled 1397,6±30,27 kgm/min, and relative

PWC170 was 20,25±0.29 kgm/min/kg; in the

experimental group (EG) they equalled 1376±30,27

kgm/min and 20,32±0.42 kgm/min/kg respectively

(the differences were insignificant: р=0,658,

р=0,889). VO2 max values in both of the groups

were similar. In the CG VO2 max and relative VO2

max were 3,67±0,07 l/min and 53,85±0,43 ml/

(kg*min), in the EG – 3,59±0,07 l/min and

53,63±0,68 ml/ (kg*min), respectively (р=0,429;

р=0,786).

The rate of recovery is a principal and almost

absolute index to estimate adaptation to load and

fitness level. The recovery dynamics during a 5

minute period was determined. In both of the groups

recovery processes were similar, and difference was

insignificant (р>0,05). The heart rate (HR) in the CG

recovered as follows: 1st minute – 118,27±1,42

bpm; 2nd min – 101,07±1,58 bpm; 3rd min –

92,93±0,83 bpm; 4th min – 92,80±0,73 bpm; 5th

min – 88,27±0,44 bpm. In the EG HR changed as:

1st min – 117,93±1,49 bpm; 2nd min – 100,53±1,35

bpm; 3rd min – 94,93±1,0 bpm; 4th min –

91,60±0,92 bpm; 5th min – 88,00±0,98 bpm.

The athletes’ psychofunctional state was

determined by the RMO test (Table 1). In the CG the

accuracy of RMO amounted to 18,95±0,87 ms; the

tendency of RMO to lag – 22,11±0,80 ms; the

tendency of RMO to advance – 19,24±1,1 ms; the

variation range – 68,67±3,22 ms. In the EG these

RMO values were 17,03±0,86 ms; 22,89±0,97 ms;

21,06±0,83 ms; 69,33±3,16 ms, respectively (the

differences were insignificant, р>0,05).

The heart rate variability (HRV) technique is

applied to estimate regulation of physiologic

functions, of general activity of the regulation

mechanisms, of heart neurohumoral regulation, and

of the relation between sympathetic and

parasympathetic systems of involuntary nervous

system. In our study a modification of this technique

with active orthostatic test (AOT) was applied. In

the CG the HR value in rest equaled 62,13±2,10

bpm; the results of HRV spectral analysis were the

Athletes Preparation based on a Complex Assessment of Functional State

157

Table 1: The test «Reaction to a moving object» indicators.

Indicator



±σ

CG EG

Accuracy of RMO, ms 18,95±0,87 17,03±0,86

The tendency of RMO to

lag, ms

22,11±0,80 22,89±0,97

The tendency of RMO to

advance, ms

19,24±1,1 21,06±0,83

The variation range, ms 68,67±3,22 69,33±3,16

following (Table 2): total spectral power (TP, ms

) –

3144,07±138,36 ms

, percentage of variations in

very low frequency in the total power (%VLF) –

33,86±1,54%, percentage of variations in low

frequency in the total power (%LF) – 26,18±1,02,

percentage of variations in high frequency in the

total power (%HF) – 36,83±1,42, stress index (SI) –

83,86±3,80 c.u., current FS – 10,47±0,47 points. In

the EG these values equaled 61,47±1.81,

3286,73±167,27 ms2, 35.82±0.98%, 28,13±1,42%,

37,47±1,19%, 84,24±2,87 c.u., 10,07±0,41 points,

respectively. The differences in all these values

between two groups were insignificant (p>0,05).

At the first stage of HRV with AOS all values

were uniform (р> 0,05): HR was 81,20±1,98 bpm;

the results of HRV spectral analysis: TP –

3107,33±111,90 ms2, %VLF – 43,26±1,53%, %LF

– 38,03±1,63, %HF – 19,66±0,91; К30:15 –

1,14±0,03 c.u.. In the EG these values were:

78,87±2,49; 3100,80±131,33 ms2, 42,73±1,50%,

37,33±1,91%, 18,02±0,59%.

Thus, at the first stage of the study differences

between the CG and the EG were statistically

insignificant, and both groups were uniform.

Table 2: Heart rate variability at rest.

Indicator



±σ

CG EG

HR, bpm 62,13±2,10 61,47±1.81

TP, ms

3144,07±138,36 3286,73±167,27

VLF,% 33,86±1,54 35.82±0.98

LF, % 26,18±1,02 28,13±1,42

HF, % 36,83±1,42 37,47±1,19

SI, c.u 83,86±3,80 84,24±2,87

The FS level and athlete’s body reserve (Table 3)

were determined by S.A. Dushanin’s technique

which enables to estimate the FS without invasive

methods, and to get an approximate representation

of the main parameters of aerobic and energetic

metabolism.

The results at the first stage were uniform for

both groups (р>0,05). In the CG we obtained:

anaerobic metabolic capacity (ANAMC) –

85,22±4,53%, aerobic metabolic capacity (AMC) –

241,17±6,93%, overall metabolic capacity (OMC) –

322,45±8,99%, power of creatinephosphate source

of energy supply (PCSES) – 31,99±0,97%, power of

glycolytic source of energy supply (PGSES) –

30,73±0,64%, power of aerobic source of energy

supply (PASES) – 68,96±1,23%, HR on the

threshold level of anaerobic metabolism (HR

TLAM), that characterizes the energy supply of

muscles by ATP aerobic synthesis, – 168,98±1,65

bpm; FS parameters: integral – 29±0,67 points,

current – 28,29±0,73 points, operational –

19,87±0,34 points. In the EG the results were as

follows: ANAMC – 85,59±4,35%, AMC –

240,84±6,09%, OMC – 323,77±6,63%, PCSES –

32,03±1,55%, PGSES – 30,53±0,84%, PASES –

69,40±1,38%, HR TLAM – 169,31±1,65 bpm, FS

parameters: integral – 29,13±0,32 points, current –

28,93±0,40 points, operational – 20,07±1,03 points.

Table 3: Functional state level and athlete’s body reserve

(S.A. Dushanin’s technique).

Indicator



±σ

CG EG

ANAMC, % 85,22±4,53 85,59±4,35

AMC, % 241,17±6,93 240,84±6,09

OMC, % 322,45±8,99 323,77±6,63

PCSES, % 31,99±0,97 32,03±1,55

PGSES, % 30,73±0,64 30,53±0,84

PASES, % 68,96±1,23 69,40±1,38

HR TLAM, bpm 168,98±1,65 169,31±1,65

The FS of neuromuscular apparatus were determined

by the polymyography. At the first stage of study

both of the groups showed similar results (р>0,05).

In the CG the rate of relative arbitrary tension

(RATr) was 6,31±0,30 kgf/kg×s, the coefficient of

relative maximal arbitrary force (CMAFr) –

6,95±0,37 kgf/kg, the rate of arbitrary relaxation

(RAR) – 4,42±0,27 1/s, the FS of muscles (FSm) –

10,05±0,28 c.u., the FS of neuromuscular system

(FSnms) – 8.56±0,43 c.u., the FS of central nervous

system (FScns) – 4,90±0,27 c.u.. In the EG these

parameters equalled 6,58±0,25 kgf/kg×s, 7±0,54

kgf/kg, 4,3±0,22 1/s, 10±0,92 c.u., 8,51±0,75 c.u.,

4,94±0,29 c.u., respectively.

The special training level was estimated by

means of 800m and 1500m runs, ten jumps, 60m

run, standing long jump. At the first stage of the

study both of the groups showed similar results

(р>0,05). In the CG the following results were

recorded: 800m run – 2,07,5±0,01 min, 1500m run –

4,11,3±0,03 min, ten jumps – 22,26±0,86 m, 60m

run – 7,92±0,16 s, standing long jump –

246,53±5,68 m. In the EG the results were as

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follows: 800m run – 2,06,8±0,02 min, 1500m run –

4,12,1±0,03 min, ten jumps – 22,28±0,69 m, 60m

run – 7,90±0,18 s, standing long jump –

247,87±6,27 m.

Identified indicators allowed to conduct a

correlation analysis of the obtained data. Analysis

helped us to establish significant correlation between

the registered data in the research period. However,

this action represents complexity for analyze large

number of indicators. It is necessary to select the

major components, which influence studied object,

in this case, the functional state.

Multivariate statistical analysis methods (cluster,

factor, component, pattern recognition and

multidimensional scaling) allow classification of

objects on a large set of attributes to study their

structure. Methods of factor (component) analysis

decide this problem.

On the basis of factor analysis, we presented the

characteristic components. Factor analysis allowed

to select five components, which characterize the

structure of the athletes functional state. Amount of

contributions in all components was 65,29%, the

proportion of unaccounted factor was 34,71%.

The I structural component of the functional state

was interpreted as by us "functional productivity".

This component is the largest, its share in total

dispersion accounted for 19.23%. It includes some

indicators of physical working capacity (absolute

and relative indicators of PWC170), MOC,

parameter VLF and with a lower load factor

accuracy of RMO, the functional state index of the

neuromuscular system (correlation coefficient 0,52,

0,62, 0,60, respectively).

The share of the II structural component of the

functional state was 13.5% of the total variance. The

united indicators of resting heart rate (r = -0,70) and

indicators of the test "Reaction to a moving object" -

the tendency of the reaction to a moving object to

lag and variation range (r = 0,72 and 0.77,

respectively). With a smaller load factor in this

group included the index of the autonomic nervous

system parasympathetic division activity (% HF),

stress index (r = 0,51 and 0.54, respectively) and a

negative correlation - performance in run 1,500 m

and 10 jumps (r = -0,54 and -0.52, respectively).

This component can be interpreted as the

"economization of recovery processes."

The III structural component of the functional

state (weight factor 12,35%) – "the indicators of

central regulation". It united indicators in running

for 800 m (r=0,81), indicators TP (total spectral

power) (r=0,69), with a negative correlation entered

power energy supply glycolytic source (PGL), long

jump from the space and index central nervous

system functional state (r=-0,68; -0,59 и -0,52

respectively).

The IV structural component (11,14%) is

"efficiency of metabolic processes" against weak

loads factor loadings attract attention of overall

metabolic capacity (r=0,82), aerobic metabolic

capacity (r=0,61), power of creatine phosphate

source of energy supply, power of aerobic source of

energy supply (r=0,62; r=0,62 respectively), HR on

the threshold level of anaerobic metabolism

(r=0,62).

The V component of the structural functional

state was interpreted by us as "the neuromuscular

system functional state" has a share of total

dispersion 9,07%. The largest factor loadings in the

component entering indicators of speed

arbitrary intension introduce in athletes weight and

the functional state of the muscles (r=0,80; r=0,63

respectively).

Allocated components describe the significance

of physiological systems and make the largest

contribution to the change in the functional state.

Conducted factor analysis allow to estimate the

functional state in summary form, structural

indicators which are average statistical. Owing to it,

we have developed estimation scale for every

indicator, which enters into the component analysis

structure. For construction of a 10-point estimation

scale, we used the scale intervals. Proceeding from

this, it is possible to calculate the total score of

indicators group and its arithmetic meaning value,

which characterizes every component.

The model values of the group and the level of

the components athletes functional state the factual

values development in the structure are shown on

the figure 1.

Figure 1: Average group models and factual values of the

athlete functional state structure components development.

Athletes Preparation based on a Complex Assessment of Functional State

159

4 CONCLUSIONS

Technique of complex assessment includes a

comprehensive diagnosis of an athlete of functional

state, revealing its most significant components, also

the estimation of every indicator functional state

scale, which allows to value the structure of the

factorial analysis. It is allowed to compare the main

group model values and factual values of the

runner’s functional state structure development

level.

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