The short-term sprints and interspersed reproduce
performance for subsequent sprints are important factors for fitness. The repeated
sprint ability (RSA) and repeated-sprint exercise (RSE) have potential
manifestation for neural mechanism. The repeated sprint ability (RSA) and time
motion analysis defies the muscle activity in the team sports (Bogdanis, 2012). Fatigue in the
muscle is the reduction of maximal power output and speed during the exercise.
Fatigue mostly develops after the first sprint, and there are the number of
reasons and factors for instance generation of motor command for the motor
cortex, neural factors, accumulation of metabolites, muscle fibers, and
inadequate motor command in the muscles (Bishop, 2012; Girard, Mendez-Villanueva, &
Bishop, 2011).
Peripheral fatigue can be defined as a reduction in the
capability of doing muscle exercise. The fatigue transpiring during the
exercise s the lack of ability to regain the initial force and power output. It
can be referred to the motor units and the process was linked to the cellular
and the mechanical changes in the muscular system (Wan, Qin, Wang, Sun, & Liu, 2017). In case of increase
in muscle fatigue, the maximum velocity and force decrease significantly, and
the force of relaxation is changed. The contraction of the muscle at the
maximum capacity results in the reversible decline of force production (Selmi, Haj, Haj, Moalla, & Elloumi, 2016).
Objective of Muscle fatigue
The aim of the present work is to examine the mechanism of
physical inactivity and activity for the modification of the muscle fatigue. The
variation in the condition of acute and chronic increase is due to physical
activity and results as structural, hormonal, metabolic, neural, and molecular
adaptation. The fatigue profile is measured for muscle during the fiber
composition, high energy metabolic storage, neuromuscular characteristic,
capillarization, and transformation of muscles during high intensity activities
(Girard, Mendez-Villanueva, & Bishop, 2011). The aim of the
present work is to find the peripheral muscle fatigue with the roles of myosin
ATPase, pH and Pi for the repeated sprint performance. The difference in the
working process is determined for the muscles at rest and maximal exercise. At
the muscle level, the limitation of the energy supply is observed for the
oxidative metabolism, phosphocreatine hydrolysis, anaerobic glycolysis, and intramuscular
accumulation of the hydrogen ions (Wan, Qin, Wang, Sun, & Liu, 2017).
Methods of Muscle fatigue
The hydrolysis of Myosin ATPase
enzymes requires the presence of the protein family to complete the process and
reaction of orthophosphate and ADP. The reaction requires a complete source of
energy for the operation and contraction of muscles (Girard, Mendez-Villanueva, & Bishop, 2011). PH is the potential
of hydrogen that is decimal logarithm for the reciprocal of the hydrogen ion
activity while on the other hand, Pi is the phosphate ion that is the empirical
formula of
and has a molar mass of
. In the case of repeated sprint performance,
the change in Pi and pH values are observed (Selmi, Haj, Haj, Moalla, & Elloumi, 2016). The higher change
is observed due to intense physical exercise that is followed by an acute
decrease in the buffer capacity of muscles. The ionic charge is higher and
consequently, the increase in non-mitochondrial adenosine triphosphate (ATP)
turnover is observed (Selmi, Haj, Haj, Moalla, & Elloumi, 2016). As a result,
accumulation of Hydrogen ion becomes higher in the muscle fibers. The higher
accumulation of Hydrogen ions is responsible for the abnormal oxidative
phosphorylation, ion regulation, and enzyme activity. The cycling exercise
causes maximum power output was used in present research for the investigation
of the repeated sprint test (Wan, Qin, Wang, Sun, & Liu, 2017). In the present
work, repeated sprints are measured for the muscle fatigue. The safe assumption
in the present is considered to collect specified data. In order to perform the
test for the evaluation of repeated sprints and muscle fatigue, eight
participants were considered under examination (Selmi, Haj, Haj, Moalla, & Elloumi, 2016). The instrument used
in the present research was Wingate testing Bike Ergometer. Monark 894E is
easy to operate and it was used to determine anaerobic demands and to evaluate
the peak power. The reliable feature of Monark 894E is to hold for the anaerobic
demands related to the self-regulating basket weight breaking system. The
appropriate calibration is required to acquire prime results (Wan, Qin, Wang, Sun, & Liu, 2017). In the present
situation release and restore the power of the basket is used in the analysis.
All the eight participants performed the test
successively for five times. The test continued for 30 seconds and change in
blood levels measurethe lactate levels
Lactate analyzer was used for testing of lactic
acid, the use of lactate analyzer is to measure the lactate levels in the
participants. Lactate is a substance that is produced in the cells of the body
and turns the food into energy in case of higher use of muscles of participants
(Wan, Qin, Wang, Sun, & Liu, 2017). Cell metabolism depends
on the value of pH present in the body in the form of lactic acid. Some of the
participants showed that neutral pH values were present in their blood in the
form of lactate (Wan, Qin, Wang, Sun, & Liu, 2017).
The normal blood lactate concentration was
measured in the patients. The effect of physical activities results in an
increase of stress as 0.5 -1 mmol/L. These patients were critically ill and participants
suffering from critical illness were having normal lactate concentration less
than 2 mmol/L (Wan, Qin, Wang, Sun, & Liu, 2017).
The higher lactate levels are due to sepsis,
anemia, severe congestive heart failure, malignancy, and diabetes. The lactate
level changes during exercise and during exercise. During exercise change in
the operation of many body parts was observed that includes conversion of
aerobic to anaerobic, recovery time, heart rate training zone, and the body
responds of an athlete (Wan, Qin, Wang, Sun, & Liu, 2017).
Statistical analysis was conducted by using
SPSS, to measure heart rate, lactic acid rate, and peak power in the body.
Results of Muscle fatigue
Peak power pairwise comparison of Muscle
fatigue
In case of peak power produced in the muscles after
repeated sprints are 539.79 for Hotelling's Trace and Roy's Largest Root while
minimum values were observed for Wilk Lambda. In the case of peak power
produced in the muscles, the standard deviation was 532.04 ± 154.28. The graph
produced in figure 1 shows a decreasing trend in peak values.
Multivariate Tests for Peak
Power
|
Effect
|
Value
|
F
|
Hypothesis
df
|
Error df
|
Sig.
|
SprintPP
|
Pillai's Trace
|
1.00
|
269.9b
|
4.00
|
2.00
|
.004
|
Wilks'
Lambda
|
.00
|
269.9b
|
4.00
|
2.00
|
.004
|
Hotelling's Trace
|
539.79
|
269.9b
|
4.00
|
2.00
|
.004
|
Roy's
Largest Root
|
539.79
|
269.9b
|
4.00
|
2.00
|
.004
|
The mean and standard deviation for
peak power of Muscle fatigue
Mean
and Standard Deviation (STD) For Peak Power
|
|
PP1
|
PP2
|
PP3
|
PP4
|
PP5
|
Mean ± STD
|
876.27 ± 149.48
|
760.80 ± 142.4
|
701.24 ± 153.22
|
583.10 ± 189.30
|
532.04 ± 154.28
|
Figure 1:
Reduction of peak power after five sprints
Lactate Acid pairwise comparison of
Muscle fatigue
Similar to the trend observed in case of peak power, the production of
lactate acid during exercise was higher for Hotelling trace and Roy's largest
root as 6990.84. while on the other hand, the minimum value was observed for
the Wilks’ Lambda. Standard deviation for the sample 1, 2, 3, 4 and 5 was 2.00
± .87, 2.52 ± 1.04, 3.28 ± .76, 5.32 ±
2.09, 7.52 ± 3.38, and 10.98 ± 4.35 respectively.
Multivariate
Tests for Lactate Acid
|
Effect
|
Value
|
F
|
Hypothesis df
|
Error df
|
Sig.
|
Sprint
LA
|
Pillai's Trace
|
1.00
|
1398.17b
|
5.00
|
1.00
|
.020
|
Wilks'
Lambda
|
.00
|
1398.17b
|
5.00
|
1.00
|
.020
|
Hotelling's Trace
|
6990.85
|
1398.17b
|
5.00
|
1.00
|
.020
|
Roy's
Largest Root
|
6990.845
|
1398.16b
|
5.000
|
1.000
|
.020
|
The mean and standard deviation
for lactic acid of Muscle fatigue
Mean
and Standard deviation (STD) of Lactate (mmol/L)
|
|
Rest
|
La 1
|
La 2
|
La 3
|
La4
|
La5
|
Mean ± STD
|
2.00 ±
.87
|
2.52 ± 1.04
|
3.28 ± .76
|
5.32 ± 2.09
|
7.52 ± 3.38
|
10.98 ± 4.35
|
Test of heart rate of Muscle
fatigue
A similar trend was observed in case of heart rate, during exercise heart
rate changes and increases with an increase in the exercise. In the results, higher
values were observed for Hotelling trace and Roy’s largest. while on the other
hand, the minimum value was observed for the Wilks' Lambda. Mean and Standard
deviation measured for the sample 1, 2, 3, 4 and 5 was 115.83 ± 14.13, 151.67 ±
22.36, 167.83 ± 13.08, 173.83 ± 9.87, 178.17 ± 7.57, and 178.50 ± 6.22 respectively.
Multivariate
Tests for Heart Rate
|
Effect
|
Value
|
F
|
Hypothesis
df
|
Error df
|
Sig.
|
Sprint
HR
|
Pillai's Trace
|
1.00
|
2746.37b
|
5.00
|
1.00
|
.014
|
Wilks'
Lambda
|
.00
|
2746.37b
|
5.00
|
1.00
|
.014
|
Hotelling's Trace
|
13731.87
|
2746.37b
|
5.00
|
1.00
|
.014
|
Roy's
Largest Root
|
13731.87
|
2746.37b
|
5.00
|
1.00
|
.014
|
The mean and standard deviation
for Heart Rate of Muscle fatigue
Mean
and Standard Deviation (STD) For Heart Rate
|
|
HrRest
|
HR1
|
HR2
|
HR3
|
HR4
|
HR5
|
Mean ± STD
|
115.83 ± 14.13
|
151.67 ± 22.36
|
167.83 ± 13.08
|
173.83 ± 9.87
|
178.17 ± 7.57
|
178.50 ± 6.22
|
Figure 2:
Multivariate Tests for Heart Rate
Figure 3:
Mean lactate level after each sprint
Discussion on Muscle fatigue
In the present analysis, factors having an influence on muscle fatigue
and repeated sprints are used to be analyzed. The muscle fatigue started after
the initial sprint and change in the performance was correlated. The results show
greater change is observed in the muscle metabolism process and after the
second sprint higher anaerobic contribution. The larger performance parameters
are measured for the anaerobic power and less reliance is implemented. The
higher fatigue resistance is observed during the intermittent sprint exercise (Selmi, Haj, Haj, Moalla, & Elloumi, 2016). The force
production in the muscles is observed that changes the anaerobic process
towards the aerobic process. The higher fatigue resistance is observed during
the metabolic process. The force generated during movement causes sprint
mechanical output and performance decrements for the muscles. The power
decrement was observed for the metabolic process for force production. In the
case of the initial sprint, mechanical output fatigue muscle contraction is
observed (Wan, Qin, Wang, Sun, & Liu, 2017). The results show
that there is higher cycling for moderate aerobically trained exercise
performance. The mechanism of fatigue production in the muscles is different on
the bases of the working process and time span for the process. In the present
running protocols, fatigue development was for the intermittent sprint exercise
(Wan, Qin, Wang, Sun, & Liu, 2017). The fatigue
resistance changes during the intermittent sprint exercise and the whole
process uses a distribution that is a number of repetitions during the process.
The generation of repeated sprints results in muscle fatigue and depends on the
recovery pattern, number of repetitions, nature of duration, intensity, and the
recovery process between sequence of sprints. The passive recovery of muscles
from fatigue depends on the higher degree of fatigue recovery (Girard, Mendez-Villanueva, & Bishop, 2011).
Conclusion on Muscle fatigue
In the present effect of repeated exercise on the muscle is measured. The
factors affecting muscle fatigue are training status, the time span of
exercise, and the influence of intermitted sprint performance. the aim of the
present research was to measure recovery time of muscles, aerobic to
anaerobic, heart rate training zone, and
the body responds of the athlete to different levels of exercise. In the
results, smaller fatigue values are associated with the aerobic training of
muscles. During the intermittent sprint exercise, the inability for body
muscles is also observed that reduces the performance of muscles. The
manifested decline is observed for the sprint speed and the mean power output
in the cycling. The extensive analysis was conducted for the study of the
failure of muscles after full activation and contracting muscles. The principal
factors proposed in the present analyses is the limitation of the energy supply
such as PCR content and oxygen consumption in the muscles and the accumulation
of different types of by-products in the metabolism process.
References of Muscle fatigue
Bishop, D. J. (2012). Fatigue during
intermittent-sprint exercise. Proceedings of the Australian Physiological
Society, 43(01), 9-15.
Bogdanis, G. C. (2012). Effects of Physical Activity
and Inactivity on Muscle Fatigue. Front Physiol, 03(142), 142-150.
Girard, O., Mendez-Villanueva, A., & Bishop, D.
(2011). Repeated-Sprint Ability – Part I. REVIEW ARTICLE, 41(08),
673-694.
Selmi, M., Haj, S. R., Haj, Y. M., Moalla, W., &
Elloumi, M. (2016). Effect of between-set recovery durations on repeated sprint
ability in young soccer players. Biol Sport, 33(02), 165-172.
Wan, J.-j., Qin, Z., Wang, P.-y., Sun, Y., & Liu,
X. (2017). Muscle fatigue: general understanding and treatment. Exp Mol Med,
49(10), 384-390.