EFFECTS OF REST INTERVALS ON NEUROMUSCULAR ACTIVITY i

EFFECTS OF REST INTERVALS ON NEUROMUSCULAR
ACTIVITY i
Running head: EFFECTS OF REST INTERVALS ON
NEUROMUSCULAR ACTIVITY
Thesis
Submitted to the School of Health and Human Performance at
Kean University in Partial
Fulfillment of the Requirement of the Degree of Master’s of
Science in Exercise Science
Richard Osolinski
Advisor: Dr. Walter Andzel
Dr. Timothy Marshall
Kean University
Union, NJ

March, 2019
Faculty
Advisor___________________________________Date_______
________
Faculty
Advisor___________________________________Date_______
________
ACTIVITY ii
Table of Content
Appendices
...............................................................................................
.....................................iii
List of Tables
...............................................................................................
................................. iv
Acknowledgements..................................................................
........................................................v
Abstract..................................................................................
.........................................................vi

1.
Introduction...............………………………………………………
……......….......................1
Hypotheses.………….....………………………………..................
......….............................10
Limitations...……………......………………………………………
…..................................11
Delimitations....……………....……………………………………
……................................11
Operational
Definitions........................……….....……………………………
……...……....12
2. Review of the
Literature..........................…………………………………………
………....13
Biological
Mechanisms.......…...………………………………………………..
...................13
Effects of Resistance
Training.………………………………………………....................
....15
Manipulation of Loads.....
…………......…………………………………….........................1
9
Manipulation of Pair
Training...........………………………………………....................
......22
Manipulation of Sets/Volume
.................……………………………………........................24
Manipulation of Training
Frequency………………………………………...........................2
6

Manipulation of Rest
Intervals..................................................................................
..............29
Summary of the Review of
Literature.…...……………………………….............................29
3.
Methods..............……………………………………………………
………..........................34
Participants……………………………………………………………
.………......................34
Instrumentation.………………………………………………………
……...........................34
Procedures……………………………………………………………
……............................35
Testing
Procedures.……………………………………………………….......
.......................36
Statistical
Analysis.………………………………………………………….......
...................37
4.
Results…………...……………………………………………….......
....................................39
Descriptive Data of
Sample………...………………………………………….................
.....39
Comparative
of..……………………………………………………………............
...............40

5.
Discussion.……………………………………………………………
……...........................54
References
...………………………………………………………………...........
.................60
ACTIVITY iii
Appendices
A. Participant Recruitment
Flyer.......................................................................................
.....71
B. Participant Consent
Form.......................................................................................
...........72
C. Participant Debriefing
Form.......................................................................................
.......76
D. PAR-
Q............................................................................................
...................................77
E. Borg Modified 10

Scale.......................................................................................
..............81
ACTIVITY iv
List of Tables and Figures
Table 1. Descriptive Statistics for 12 male
participants...............................................................40
Table 2. Right Pectoralis Mean and Maximum Neuromuscular
Activation.................................41
Table 3. Right Triceps Mean and Maximum Neuromuscular
Activation.....................................41
Table 4. Left Pectoralis Mean and Maximum Neuromuscular
Activation...................................42

Table 5. Left Triceps Mean and Maximum Neuromuscular
Activation.........................................42
Table 6. Mean Rate of Perceived
Exertion..................................................................................
.42
Table 7. Within Subjects Mauchly's Test of
Sphericity.................................................................44
Table 8. Multivariate Test for Within Subjects
Effect....................................................................45
Table 9. Univariate Test for Right Pectoralis Mean
Activation....................................................46
Table 10. Univariate Test for Right Pectoralis Max
Activation....................................................46
Table 11. Univariate Test for Right Triceps Mean
Activation.......................................................47
Table 12. Univariate Test for Right Triceps Max
Activation.........................................................48
Table 13. Univariate Test for Left Pectoralis Mean
Activation.....................................................48
Table 14. Univariate Test for Left Pectoralis Maximum
Activation..............................................49
Table 15. Univariate Test for Left Triceps Mean
Activation.........................................................50
Table 16. Univariate Test for Left Triceps Maximum

Activation..................................................50
Table 17. Univariate test for Rate of Perceived
Exertion..............................................................51
Table 18. Pair-Wise Comparison Between
Sets............................................................................52
Table 19. Friedman Test for Differences in RPE between Sets
....................................................52
Table 20. Wilxocon Signed-Rank Test for Differences in RPE
Between Sets................................52
Table 21. Wilxocon Signed-Rank Test for Differences in RPE
Between Sets Continued........... 53
Figure 1. Post hoc Power
Analysis..................................................................................
..............53
ACTIVITY v
ACKNOWLEDGEMENTS
I would first like to thank all of my participants for making this
study possible and for
devoting their time and effort throughout the course of the study
because it wouldn’t be possible
without them. I would also like to thank my professors within in
Kean University Exercise

Science Master’s program, including Dr. Walther Andzel, Dr.
Josh Palgi, Victoria Baxter M.S.,
Professor Lisa Flemings M.S, and Professor Mark Hung M.S.
for supplementing my education
with their immense knowledge in the various areas of Exercise
Science and assistance during my
time at Kean University. Further, I would like to thank Dr.
Timothy Marshall for providing me
with the proper equipment to conduct this study and for his
support through the program as well
as aiding in the formulation, structure, organization, data
analysis and completion of my Master’s
Thesis. Lastly, I would like my family, friends, and amazing
class mates for their support,
patience, and encouragement through this wonderful journey.

ACTIVITY vi
ABSTRACT
Purpose: The purpose of this study is to investigate the effects
of 1-minute rest interval on
neuromuscular activation of the pectoralis major and lateral
head of triceps brachii, and the rate
of perceived exertion (RPE) during the chest press exercise.
Previous studies investigated upper
body and lower body exercises utilizing varying rest periods
and the effects on neuromuscular
activation and ratings of perceived exertions but the research
thus far has had conflicting results.
Methods: The study consisted of 2 sessions in a week period.
The first session consisted of a
completing anthropometric measurements, and a one repetition
bench (1RM) test. The following
session consisted of a strength training protocol (5 sets of 8
repetitions), using 40% of 1RM for
the bench-press with a 1-minute rest interval.
Results: The mean and maximum neuromuscular activity for the
pectoralis major and lateral
heads of the triceps were recorded using surface

electromyography, and Borg Scale for RPE. A
repeated-measures ANOVA was used for statistical analysis
with a confidence level of p <.05 to
determine if there was significant difference in neuromuscular
activation or RPE found during
the study.
Conclusion: A repeated-measures ANOVA showed that 1-
minute rest interval caused a
significantly lower mean neuromuscular activity in the right
lateral head of triceps brachii
between sets 2 and 5, p =.003. No other significant differences
in mean of maximum
neuromuscular activity or RPE were found. Suggesting that the
decreases in neuromuscular
activity observed during 1-minute rest interval during the bench
40% 1-RM may not be caused
by changes in neuromuscular activity (neural fatigue).
ACTIVITY 1
CHAPTER 1

INTRODUCTION
Strength training is effective for improving certain fitness
goals, such as muscular
strength and power; there are numerous training variables can
be manipulated, such as %-1RM,
paired training, volume/sets, frequency and rest time which may
be the least understood in
regards to the length of rest time and the outcomes of strength
training (Freitas et al., 2015;
Ratamess et al., 2012; Tibana et al, 2011; Freitas Maia et al.,
2015). Muscular strength and
power are critical attributes for many athletes that allow them
perform at high levels of
intensities. Muscular strength is the ability of a muscle or
muscle group to generate force at
constant velocity against resistance, whereas, power refers to
one’s ability to produce force at a
higher velocity over a period of time ( Haff & Dumke, 2012;
Baechle & Earle 2008). Greater
muscular strength can enhance ability to generate power of an
individual which can then
translate to their athletic performance. Muscular strength is
strongly correlated to superior
jumping, sprinting, and sport-specific performance (Suchomel et

at. 2016). However, the amount
of power generated can only be sustained for a period of time
due to the intensity and duration of
exercise and the energy systems supporting the activity
(Beachle & Earle, 2008).
Before power is developed, a muscle must first contract;
muscle contraction may be
defined as the activation of the actomyosin complex in muscle
fibers, which will initiate the
cross-bridge cycle. When activated, a muscle will either
shorten, lengthen, or remain the same
length, which depends on the external load placed on the muscle
in order to produce the amount
of force required per given task. The ability of muscle to
respond is controlled by chemical
(neurotransmitter) stimuli, as well as Na+-K+ ATPase exchange
pump and an increased
permeability to potassium. When a muscle fiber is stimulated,
an action potential is generated,
which is the basic form of communication between neurons and
muscle fibers. The terminal
ACTIVITY 2

ends of neurons release neurotransmitters in response to the
frequency, magnitude, spatial
distribution of an action potential that ultimately determine the
recruitment of a motor unit.
Which is comprise of a motor neuron and the muscle fibers it
innervates. Electromyography
(EMG) is a tool that can be used to measure motor unit
activation and recruitment by measuring
the electrical activity inside of a muscle. EMGs can measure
both the frequency and amplitude
of a muscle’s electrical activity, providing information about
the muscle’s electrical activity
(Broosk et al, 1995).
When a muscle cell receives an action potential, cytosolic
calcium concentrations
increase; calcium will bind to troponin, exposing the myosin
binding site on tropomysium,
initiating the cross bridge cycle, and thus the sliding filament
theory of muscle contraction.
Adenosine Triphosphate (ATP) is the energy currency facilitates
the ‘power-stroke’ of the
sliding filament theory, and thus, muscle contraction. Small
quantities are readily available to

power a muscle for the first few seconds of activity. After
which, ATP must be created, which
can be done so through a few different pathways: Creatine
Phospate system, Glycolysis, and
Aerobic Oxidation (Broosk et al, 1995). All three energy
systems are active at any given time:
however, the magnitude of the contribution of each system to
overall work performance is
primarily dependent on the intensity of the activity and
secondarily to duration (Beachle & Earle
2008). The energy needed to perform short-term, high-intensity
powerful exercises (5 seconds to
60 seconds) is highly dependent on anaerobic energy
metabolism glycolysis and primarily the
creatine phosphate system (ACSM, 2104). The creatine
phosphate system transfers high-energy
phosphates from creatine phosphate to re-phosphorylated ATP
from ADP which is catalyzed by
creatine phosphate exist in large
quantities within cells and the amount ATP stored in muscles is
small, thus limiting the energy

ACTIVITY 3
available for muscle contraction. The ATP generated is
transported to muscles cells where it then
binds to the myosin-cross bridge to trigger the “power stroke”
generate muscle contraction. Once
complete ATPase breaks down the ATP into ADP and
Phosphate. This process will continue to
occur if free calcium is available and homeostasis maintained
with in the cell (Powers &
Howley, 2018). As the duration of exercise lasts longer than 45
seconds, creatine phosphate
levels decrease causing a shift to anaerobic glycolysis which
uses carbohydrates from either
glycogen from muscles or glucose and involves multiple
enzymatically catalyzed reactions
resulting in the production of pyruvate which may proceed in
one of two directions: Pyruvate can
be converted to lactate, ATP is resynthesized occurs faster but
still limited in duration known as
fast glycolysis (anaerobic), or Pyruvate can be shuttle to the
mitochondria to undergo slow
glycolysis (aerobic) which is slower but can occur for longer
durations at lower intensity
(Beachle & Earle, 2008). As the intensity decreases and the

duration increases, the emphasis
gradually shift to slow glycolysis and the oxidative energy
system. Therefore, causing, gradual
shift from carbohydrates to fats in the form of triglycerides are
also readily available for ATP
production, but their breakdown is much slower than glucose
and glycogen (ACSM,2014).
However, when conditions become unfavorable such as not
adequate resources to fuel the
process and or accumulation of byproduct which can negatively
affect the muscles ability to
generate power, resulting in fatigue.
Fatigue is a condition in which a muscle cannot continue to
produce the required energy,
which can be attributed by both a reduction in the capacity of
the central nervous system to
activate muscles, central fatigue and or impaired muscle
function termed peripheral fatigue
(ACSM, 2014). Fatigue is variable and can be influenced by
exercise intensity, duration of the
ACTIVITY 4

activity, as well as the muscle composition and fitness level of
the individual (Beachle & Earle,
2008; Gentil et al. 2017; Powers & Howley, 2018).
Central fatigue can be defined as a progressive, exercise-
induced degradation of the
muscle voluntary activation (Boyas & Guevel, 2010). When
central fatigue develops, various
biochemical processes are affected with in the nervous system
hindering or disrupting the release
of neurotransmitters, decreasing motor neuron excitation, which
effects the muscles ability to
maintain muscle activation (Taylor et. al, 2016). Therefore, a
muscle may not be able to produce
the needed or required force.
In addition to central fatigue, a muscle may also experience
peripheral fatigue, which can
be defined as the loss of contraction force or power caused by
processes anywhere between
neuromuscular junction and contractile elements of the muscle
(Ament & Verkerke, 2009).
Peripheral fatigue may be caused by a lack of energy resources
within the muscle and the
inability to remove byproducts resulting in an accumulation of
lactic acid and other metabolites

within the muscle. The accumulation waste products (H+) and
various metabolites (Mg+2, and
Pi,) cause distributions in the contractile mechanism
specifically affecting Ca+2 resulting fatigue
(Boyas & Guevel, 2011). The increase in waste products and
metabolites affect the cross-bridge
interaction and force production. Accumulation of hydrogen
ions in the sarcoplasm causing a
decrease in pH levels within the cell triggering physiological
changes such as a drop in the
contractile force due to inhibition of the cross-bridges’
interaction. This accumulation triggers
impaired reuptake of calcium by the sarcoplasmic reticulum.
thus contributing the extended
relaxation period after a fatiguing contraction. By reducing the
amount of Ca+2 entering the cells
limits the resources needed to initiate muscle contraction
(Boyas & Guevel,2011). Ca+2 is
essential in muscle contraction because it binds regulatory
proteins (eg. Tropomyosin) exposing
ACTIVITY 5

the binding site for on actin filament allowing for the formation
of actin-myosin cross bridge
resulting in muscle-shortening (Powers & Howley, 2018).
Therefore, in the absence of Ca+2
molecules will prevent interaction of actin and myosin resulting
in muscular fatigue.
Organic Pi is a byproduct of the phosphogen-creatine reaction.
The increase organic Pi
directly affects the release of Ca+2 by activating Ca+2 channels
facilitating out of the cell causing
the muscle cell to enter a tetanic state, Pi may affect ATP
driven sarcoplasm reticulum uptake of
Ca+2, and lastly forming Ca+2-Pi precipitation decreasing the
availability of free Ca+2.
(Westerblad et al. 2006). Therefore, decreasing the amount of
Ca+2 available in the cell will
negatively active the actin-myosin cross bridge binding. The
free calcium binds tropomyosin
exposing the binding site for on actin filament allowing for the
formation of actin-myosin cross
bridge resulting in muscle-shortening. So if therefore, is not
sufficient amount of Ca+2 muscle
contraction will not occur. Neuromuscular activity can be
measured by using specialized

equipment such as electromyograms to analyze the
neuromuscular activity can be valuable in
detecting abnormalities, optimal activation levels, and or motor
unit recruitment patterns that are
affected when neuromuscular fatigue occurs (Jenkin et al.,
2015). Thus, as neuromuscular
fatigue occurs, it will subsequently cause a decrease in muscle
function diminishing
performance.
In addition, the fitness level of an individual can contribute to
level of fatigue felt. Gentil
et al. (2017) investigated elbow flexor isokinetic dynamometer
peak torque and fatigue index
between men and women of different fitness levels. At the
conclusion of the study, the results
indicated that resistance trained males had significantly higher
elbow flexion torque than non-
resistance train males and bother resistance trained and non-
trained females. Also, non-resistance
ACTIVITY 6
trained male and females has significantly higher fatigue
indexes compared to their resistance

trained counterparts (Gentil et al.,2017).
Lastly, the composition and contractile mechanism of a muscle
can also play a critical
role in neuromuscular fatigue. The muscles of the human body
are composed of a mixture of
muscle fibers. There are three muscle fiber types that can be
found in the human muscular
system such as type 1 (slow twitch) fiber, and type-lla and type-
llx (fast twitch) fiber. Type 1
fibers contain large number of oxidative enzymes, surrounded
by a large number of capillaries,
increased concentration of myoglobin compared to type- fibers,
allowing them to have greater
capacity for aerobic metabolism and high resistance to fatigue
(Powers & Howley, 2018). Due to
the larger amounts of capillary surrounding them and greater
concentration of myoglobin
allowing for great amounts of nutrients to be delivered to the
muscle fibers providing them with
nutrient to perform longer duration exercise. In contrast, Type-
ll fibers contain smaller number
of mitochondria, limited capacity for aerobic oxidation, less
resistance to fatigue than Type-I

fibers but contain fibers rich in glycolytic enzymes which
provide them with larger capacity of
anaerobic capacity (Powers & Howley, 2018). Therefore, the
type of muscle fiber or composition
of a muscle will affect the level of performance. The mixture of
muscle fiber types can to
influence how muscles respond to training and affect
performance. Trappe et al. (2015)
performed a muscle biopsy on a world champion sprinter. Their
findings showed the world
champion sprinter had a significantly higher abundance of type-
llx and type-lla fibers compared
to type-1 fibers (Trappe et al.,2015). Thus signifying the higher
composition of type-ll fibers
allows for greater short bouts of explosive energy required by
the sport.
In summary, there may be several reason why a person cannot
continue muscle work, and
thus, become fatigue. General factors that continue to fatigue
include the nature of the activity
ACTIVITY 7
training status of the individual. But more specifically, fatigue

may be due to the depletion of
key metabolites, such as creatine phosphate, muscle and liver
glycogen. And blood glucose.
High levels of muscle work cannot continue without an
adequate supply of these metabolites.
Fatigue may also occur because of the accumulation of
metabolites. Research has demonstrated
that the accumulation of lactic acid, loss of Ca2+as well as the
accumulation of Ca2+, which
impacts oxidative phosphorylation, glycolysis and excitation-
contraction coupling. Fatigue may
also occur with the accumulation of H+ ions. Lastly, fatigue
will occur when the muscle no
longer responds to increase stimuli, suggesting peripheral
fatigue (Powers & Howley, 2018).
In addition, to gauge the level of fatigue an individual feel can
be measured by The Rate
of perceived exertions (RPE) scale. The RPE scale is a
frequently used quantitative measure of
perceived exertion experienced during physical activity. The
two most commonly used scales of
perceived exertion in exercise are Borg’s 6–20 scale or can be
modified using 0-10 and category
ratio scale (Dawes et al., 2005; Lgally et al., 2004; Lorente et

al., 2016).
Further, the Borg scale ranges from 6 (no exertion) to 20
(maximal exertion) or on the
modified scale 0 (no exertion) to 10 (maximal exertion). A
perceived exertion rating between 12
to 14 on the 6-20 Borg Scale, 5 to 6 on modified scale indicates
that physical activity is being
performed at a moderate level of intensity. There is strong
correlation between an individual’s
perceived exertion rating and the actual heart rate during
physical activity; so a person's exertion
rating may provide a fairly good estimate of the actual heart
rate during activity (CDC, 2105;
ACSM 2014). Therefore, properly instructing a person how to
utilize the Borg Scale can give
one an idea of how hard he or she is training and whether or not
to adjust the workout intensity to
ensure he or she is exercising at an appropriate level to reach
their training goal. To reduce the
instances and effects of fatigue, many athletes will engage in
training programs.
ACTIVITY 8

Moreover, to reduce the instances and effects of fatigue, many
athletes will engage in
training programs. Research has demonstrated strength training
is effective for improving certain
fitness goals, like muscular strength and power; numerous
variables can be manipulated, such as
%-1RM, paired-training, volume/sets, frequency and rest time
which may be the least understood
in regards length of rest time and the outcomes of strength
2015). Resistance training is
important and should implemented in an athlete’s exercise
regimen. Properly training for a
specific goal such as strength and power will allow the body to
gradually build up strength,
ultimately improving an athlete’s skill level improving
performance. However, research
regarding the optimal rest time interval and how it affects
mechanical and physiological
variables that contributing to fatigue has been inconsistent.
Therefore, the purpose of this study is
to investigate the effect of 1- minute rest interval on
neuromuscular activation, and rate of

perceived exertion during the chest press exercise performed at
40% 1RM. Improving our
understanding bout optimal rest period may allow for improved
design of power and strength
programs
ACTIVITY 9
Statement of the Problem
Optimizing different training variable such as %-1RM, paired
training,
volume/sets, training frequency and rest time during will
influence the effectiveness of a
resistance training program that is structured around improving
strength and/or power. Several
factors may be considered when developing a strength training
program, such as % of one’s 1-

reptition maximum, number of sets and repetition, frequency of
training, and rest time between
sets. Research has demonstrated that strength gains may be
optimized when a program consist of
loads between 70% and 90% of one’s 1RM, working between 3
and 5 sets with lower repetitions
(3-5 reps) and training a minimum of two times per week (Leite
et al., 2014; Mangine et al.,
2016; Arazi & Asadi, 2011; Ochi et al.,2018; Gentil et al.,
2014). Research regarding the optimal
rest time interval and how it affects mechanical and
physiological variables that contributing to
fatigue has been inconsistent (Marshall et al., 2012; Martorelli
et al., 2012; Davo et al. 2015;
Tibana et al. 2013). However, previous research has not taken
neural measurements to explore
the impact of rest time intervals on neuromuscular system.
Fatigue can alter overt performance,
such that the task is performed more slowly or clumsily or even
cannot be performed
successfully, or it can alter the neuromuscular activity required
to perform the task and this may
be evident as increased electrical activity of the muscle (Taylor,
2016.)

Therefore, the purpose of this study is to investigate the effect
of 1- minute rest interval
on neuromuscular activation, and rate of perceived exertion
during the chest press exercise
performed at 40% 1RM. Improving our understanding bout
optimal rest period may allow for
improved design of power and strength programs.
ACTIVITY 10
Hypotheses
1. Performing 5 sets of 8 repetitions at 40% 1 RM, resting 1
minute between each set will
cause a significant effect in neuromuscular activation in the
pectoralis major and triceps
brachii lateral head as measured by electromyography (EMG)
cause a significant effect on exertion as assessed by the RPE
scale

not cause a significant effect in neuromuscular activation in the
pectoralis major and
triceps brachii lateral head, as measured by electromyography
(EMG)
not cause a significant effect on exertion as assessed by the RPE
scale
Scope of the Study
There has been previous research on upper body and lower
body exercises utilizing
varying rest periods and the effects on neuromuscular activation
and ratings of perceived
exertions but the research thus far has had conflicting results.
For practical application, defining
the optimal rest period between sets can be beneficial for
developing a suitable training protocol.
Developing an effective training protocol can maximize muscle
activation sequentially
increasing one’s performance levels. Successfully gathering
information about optimal rest

period and its effects on neuromuscular response can impose
significant clinical importance.
This information can be advantageous for coaches, trainers, and
clinicians who wish to design
training strength and condition protocols or rehabilitative
programs to optimize athletic
performance.
ACTIVITY 11
Assumptions
1. All research conducted and review was done in an
appropriate and valid manner.
2. Researcher displayed professionalism and was ethical
through the duration of the study.
3. The participants were honest and accurate during any
medical history, questionnaires,
and PAR-Q information that was provided to the researcher
during the study.
Limitations
1. The sample is not representative of the entire Kean
University student athletic population.
2. The participants have varying levels of athletic

performance.
3. The participants have varying muscular strength and
endurance levels.
Delimitations
1. The participant sample population was selected from male
students at Kean University in
Union, New Jersey.
2. Resistance training was required
3. The participants was male.
4. The sample was be tested using the bench press exercise.
ACTIVITY 12
Operational Definitions
Electromyography (EMG) – Graphical recording of the

electrical activity of motor unit activity
in skeletal muscle (Haff & Dumke., 2012; ACSM, 2014).
Hypertrophy – Increased size of cells or of an entire tissue;
muscle hypertrophy is an increase in
the size of muscle fibers or of an entire muscle (ACSM, 2014).
Motor Unit – A single somatic motor neuron and the group of
muscle fibers innervated by it
(ACSM, 2014).
Muscle Fatigue – the loss of force or power out in response to
voluntary effort leading to
reduced performance (ACSM, 2104).
Muscular Endurance – The muscles ability to exert submaximal
forces repetitively to move a
certain load (Haff & Dumke., 2012).
Muscular Strength – The largest amount of force that a muscle
or group of muscle can generate
during a single contraction (Haff & Dumke., 2012).
Neurological system – encompasses all of the muscles in the
body and the nerves serving them
Rate of Perceived Exertion (RPE) – subjective measurement
used to monitor progress toward

maximal exertion (Haff & Dumke., 2012).
Resistance training – form of exercise using resistance that
improved muscular strength and
muscular endurance (Beachle & Earle, 2008).
Rest interval – amount of time between sets during exercise (
Davo et al., 2015)
ACTIVITY 13
CHAPTER 2
LITERATURE REVIEW
Strength training is effective for improving certain fitness
goals, such as muscular
strength and power; there are numerous training variables that
can be manipulated, such as %-
1RM, paired training, volume/sets, frequency and rest time
which may be the least understood in
regards to the length of rest time and the outcomes of strength
2015). Muscular strength and

power are critical attributes for many athletes that allow them
perform at high levels of
intensities. Muscular strength is the ability of a muscle or
muscle group to generate force at
constant velocity against resistance, whereas, power refers to
one’s ability to produce force at a
higher velocity over a period of time ( Haff & Dumke, 2012;
Baechle & Earle 2008). Greater
muscular strength can enhance ability to generate power of an
individual which can then
translate to their athletic performance. Muscular strength is
strongly correlated to superior
jumping, sprinting, and sport-specific performance (Suchomel et
at. 2016). However, the amount
of power generated can only be sustained for a period of time
due to the intensity and duration of
exercise and the energy systems supporting the activity
Before power is developed, a muscle must first contract;
muscle contraction may be
defined as the activation of the actomyosin complex in muscle
fibers, which will initiate the
cross-bridge cycle. When activated, a muscle will either
shorten, lengthen, or remain the same

length, which depends on the external load placed on the muscle
in order to produce the amount
of force required per given task. The ability of muscle to
respond is controlled by chemical
(neurotransmitter) stimuli, as well as Na+-K+ ATPase exchange
pump and an increased
permeability to potassium. When a muscle fiber is stimulated,
an action potential is generated,
ACTIVITY 14
which is the basic form of communication between neurons and
muscle fibers. The terminal
ends of neurons release neurotra nsmitters in response to the
frequency, magnitude, spatial
distribution of an action potential that ultimately determine the
recruitment of a motor unit.
Which is comprised of a motor neuron and the muscle fibers it
innervates. Electromyography
(EMG) is a tool that can be used to measure motor unit
activation and recruitment by measuring
the electrical activity inside of a muscle. EMGs can measure
both the frequency and amplitude

of a muscle’s electrical activity, providing information about
the muscle’s electrical activity
(Broosk et al, 1995).
When a muscle cell receives an action potential, cytosolic
calcium concentrations
increase; calcium will bind to troponin, exposing the myosin
binding site on tropomysium,
initiating the cross bridge cycle, and thus the sliding filament
theory of muscle contraction.
Adenosine Triphosphate (ATP) is the energy currency facilitates
the ‘power-stroke’ of the
sliding filament theory, and thus, muscle contraction. Small
quantities are readily available to
power a muscle for the first few seconds of activity. After
which, ATP must be created, which
can be done so through a few different pathways: Creatine
Phospate system, Glycolysis, and
Aerobic Oxidation (Broosk et al, 1995). All three energy
systems are active at any given time:
however, the magnitude of the contribution of each system to
overall work performance is
primarily dependent on the intensity of the activity and
secondarily to duration (Beachle & Earle
2008). The energy needed to perform short-term, high-intensity

powerful exercises (5 seconds to
60 seconds) is highly dependent on anaerobic energy
metabolism glycolysis and primarily the
creatine phosphate system (ACSM, 2104). The creatine
phosphate system transfers high-energy
phosphates from creatine phosphate to re-phosphorylated ATP
from ADP which is catalyzed by
creatine phosphate exist in large
ACTIVITY 15
quantities within cells and the amount ATP stored in muscles is
small, thus limiting the energy
available for muscle contraction. The ATP generated is
transported to muscles cells where it then
binds to the myosin-cross bridge to trigger the “power stroke”
generate muscle contraction. Once
complete ATPase breaks down the ATP into ADP and
Phosphate. This process will continue to
occur if free calcium is available and homeostasis maintained
with in the cell (Powers &
Howley, 2018). As the duration of exercise lasts longer than 45
seconds, creatine phosphate

levels decrease causing a shift to anaerobic glycolysis which
uses carbohydrates from either
glycogen from muscles or glucose and involves multiple
enzymatically catalyzed reactions
resulting in the production of pyruvate which may proceed in
one of two directions: Pyruvate can
be converted to lactate, ATP is resynthesized and occurs faster
but still limited in duration known
as fast glycolysis (anaerobic), or Pyruvate can be shuttled to the
mitochondria to undergo slow
glycolysis (aerobic) which is slower but can occur for longer
durations at lower intensity
(Beachle & Earle, 2008). As the intensity decreases and the
duration increases, the emphasis
gradually shift to slow glycolysis and the oxidative energy
system. Therefore, causing, gradual
shift from carbohydrates to fats in the form of triglycerides are
also readily available for ATP
production, but their breakdown is much slower than glucose
and glycogen (ACSM,2014).
However, when conditions become unfavorable such as not
adequate resources to fuel the
process and or accumulation of byproduct which can negatively
affect the muscles ability to

generate power, resulting in fatigue.
Fatigue is a condition in which a muscle cannot continue to
produce the required energy,
which can be attributed by both a reduction in the capacity of
the central nervous system to
activate muscles, central fatigue and or impaired muscle
function termed peripheral fatigue
(ACSM, 2014). Fatigue is variable and can be influenced by
exercise intensity, duration of the
ACTIVITY 16
activity, as well as the muscle composition and fitness level of
the individual (Beachle & Earle,
2008; Gentil et al. 2017; Powers & Howley, 2018).
Central fatigue can be defined as a progressive, exercise-
induced degradation of the
muscle voluntary activation (Boyas & Guevel, 2010). When
central fatigue develops, various
biochemical processes are affected with in the nervous system
hindering or disrupting the release
of neurotransmitters, decreasing motor neuron excitation, which
effects the muscles ability to

maintain muscle activation (Taylor et. al, 2016). Therefore, a
muscle may not be able to produce
the needed or required force.
In addition to central fatigue, a muscle may also experience
peripheral fatigue, which can
be defined as the loss of contraction force or power caused by
processes anywhere between
neuromuscular junction and contractile elements of the muscle
(Ament & Verkerke, 2009).
Peripheral fatigue may be caused by a lack of energy resources
within the muscle and the
inability to remove byproducts resulting in an accumulation of
lactic acid and other metabolites
within the muscle. The accumulation waste products (H+) and
various metabolites (Mg+2, and
Pi,) cause distributions in the contractile mechanism
specifically affecting Ca+2 resulting fatigue
(Boyas & Guevel, 2011). The increase in waste products and
metabolites affect the cross-bridge
interaction and force production. Accumulation of hydrogen
ions in the sarcoplasm causing a
decrease in pH levels within the cell triggering physiological
changes such as a drop in the

contractile force due to inhibition of the cross-bridges’
interaction. This accumulation triggers
impaired reuptake of calcium by the sarcoplasmic reticulum.
thus contributing the extended
relaxation period after a fatiguing contraction. By reducing the
amount of Ca+2 entering the cells
limits the resources needed to initiate muscle contraction
(Boyas & Guevel,2011). Ca+2 is
essential in muscle contraction because it binds regulatory
proteins (eg. Tropomyosin) exposing
ACTIVITY 17
the binding site for on actin filament allowing for the formation
of actin-myosin cross bridge
resulting in muscle-shortening (Powers & Howley, 2018).
Therefore, in the absence of Ca+2
molecules will prevent interaction of actin and myosin resulting
in muscular fatigue.
Organic Pi is a byproduct of the phosphogen-creatine reaction.
The increased organic Pi
directly affects the release of Ca+2 by activating Ca+2 channels
facilitating out of the cell causing
the muscle cell to enter a tetanic state, Pi may affect ATP

driven sarcoplasm reticulum uptake of
Ca+2, and lastly forming Ca+2-Pi precipitation decreasing the
availability of free Ca+2.
(Westerblad et al. 2006). Therefore, decreasing the amount of
Ca+2 available in the cell will
negatively active the actin-myosin cross bridge binding. The
free calcium binds tropomyosin
exposing the binding site on a actin filament allowing for the
formation of actin-myosin cross
bridge resulting in muscle-shortening. So if therefore, is not
sufficient amount of Ca+2 muscle
contraction will not occur. Neuromuscular activity can be
measured by using specialized
equipment such as electromyograms to analyze the
neuromuscular activity can be valuable in
detecting abnormalities, optimal activation levels, and or motor
unit recruitment patterns that are
affected when neuromuscular fatigue occurs (Jenkin et al.,
2015). Thus, as neuromuscular
fatigue occurs, it will subsequently cause a decrease in muscle
function diminishing
performance.
In addition, the fitness level of an individual can contribute to
level of fatigue felt. Gentil

et al. (2017) investigated elbow flexor isokinetic dynamometer
peak torque and fatigue index
between men and women of different fitness levels. At the
conclusion of the study, the results
indicated that resistance trained males had significantly higher
elbow flexion torque than non-
resistance train males and bother resistance trained and non-
trained females. Also, non-resistance
ACTIVITY 18
trained male and females had significantly higher fatigue
indexes compared to their resistance
trained counterparts (Gentil et al.,2017).
Lastly, the composition and contractile mechanism of a muscle
can also play a critical
role in neuromuscular fatigue. The muscles of the human body
are composed of a mixture of
muscle fibers. There are three muscle fiber types that can be
found in the human muscular
system such as type 1 (slow twitch) fiber, and type-lla and type-
llx (fast twitch) fiber. Type 1
fibers contain large number of oxidative enzymes, surrounded

by a large number of capillaries,
increased concentration of myoglobin compared to type- fibers,
allowing them to have greater
capacity for aerobic metabolism and high resistance to fatigue
(Powers & Howley, 2018). Due to
the larger amounts of capillary surrounding them and greater
concentration of myoglobin
allowing for great amounts of nutrients to be delivered to the
muscle fibers providing them with
nutrient to perform longer duration exercise. In contrast, Type-
ll fibers contain smaller number
of mitochondria, limited capacity for aerobic oxidation, less
resistance to fatigue than Type-I
fibers but contain fibers rich in glycolytic enzymes which
provide them with larger capacity of
anaerobic capacity (Powers & Howley, 2018). Therefore, the
type of muscle fiber or composition
of a muscle will affect the level of performance. The mixture of
muscle fiber types can to
influence how muscles respond to training and affect
performance. Trappe et al. (2015)
performed a muscle biopsy on a world champion sprinter. Their
findings showed the world
champion sprinter had a significantly higher abundance of type-

llx and type-lla fibers compared
to type-1 fibers (Trappe et al.,2015). Thus signifying the higher
composition of type-ll fibers
allows for greater short bouts of explosive energy required by
the sport.
In summary, there may be several reason why a person cannot
continue muscle work, and
thus, become fatigue. General factors that continue to fatigue
include the nature of the activity
ACTIVITY 19
training status of the individual. But more specifically, fatigue
may be due to the depletion of
key metabolites, such as creatine phosphate, muscle and liver
glycogen. And blood glucose.
High levels of muscle work cannot continue without an
adequate supply of these metabolites.
Fatigue may also occur because of the accumulation of
metabolites. Research has demonstrated
that the accumulation of lactic acid, loss of Ca2+as well as the
accumulation of Ca2+, which
impacts oxidative phosphorylation, glycolysis and excitation-
contraction coupling. Fatigue may

also occur with the accumulation of H+ ions. Lastly, fatigue
will occur when the muscle no
longer responds to increased stimuli, suggesting peripheral
fatigue (Powers & Howley, 2018).
To reduce the instances and effects of fatigue, many athletes
will engage in training
programs. Research has demonstrated strength training is
effective for improving certain fitness
goals, like muscular strength and power; numerous variables
can be manipulated, such as %-
1RM, paired-training, volume/sets, frequency and rest time
which may be the least understood in
regards length of rest time and the outcomes of strength training
(Freitas et al., 2015; Ratamess et
al., 2012; Tibana et al, 2011; Freitas Maia et al., 2015).
Resistance training is important and
should be implemented in an athlete’s exercise regimen. Proper
training for a specific goal such
as strength and power will allow the body to gradually build up
strength, ultimately improving an
athlete’s skill level improving performance.
One method of increasing muscular strength and power is by
manipulating the load or

weight used during resistance training. Schoenfel et al. (2014)
investigated muscular adaptations
to a manipulating the load utilizing during a hypertrophy
training program verse a strength
training type routine in well-trained subjects. Seventeen young
men were randomly assigned to
either a hypertrophy-type resistance training group that
performed 3 sets of 10 repetitions with
10 repetition maximum (RM) with 90 seconds rest or a strength-
type resistance training group
ACTIVITY 20
that performed 7 sets of 3 repetitions with 3RM with a 3-minute
rest interval. The resistance
programs both contained 3 chest press variation, wide/close-
grip lat pull down, and cable row,
and 3 lower body exercises: back squat, leg press and leg
extension). At the conclusion of the
study, the results indicated there was a significant increase in
muscular size for both training
protocols but strength training protocol had significantly higher
strength gains (Schoenfel et
al.,2014). Therefore, this study suggest that a heavier load

should be used to achieve an increase
in muscular strength.
Similarly, Schoenfel et al. (2015) examined the effects of low
load (30% - 50% 1RM)
resistance training versus high-load (70% - 80% 1RM)
resistance training on muscular
adaptations as measured by muscle thickness, muscular
endurance and upper body and lower
body 1 repetition maximum in 18 well-trained male participants.
Participants were pair matched
according to baseline strength and then randomly assigned to a
low-load resistance routine in
which 25–35 repetitions were performed to failure per exercise
or a high-load resistance routine
where 8–12 repetitions were performed per exercise (n = 12).
The protocols consisted of 3 sets of
7 exercises per session consisting of flat barbell press, barbell
military press, wide-grip lat pull-
down, seated cable row, barbell back squat, machine leg press,
and machine leg extension. At the
conclusion of the study, the results indicated that both high-load
training and low-load protocols
produced significant increases in thickness of the elbow flexors,
elbow extensors and quadriceps

femoris, with no significant differences noted between groups.
Also, the results suggested that
the improvements observed in back squat strength were
significantly greater for high-load
protocol compared to low-load and there was a greater increase
in (1RM) bench press. Upper
body muscle endurance improved to a greater extent in low -load
compared to high-load
resistance protocol. Lastly, the data showed greater strength
gains for high-load protocol
ACTIVITY 21
(Schoenfel et al., 2015) which is in agreement with the finds in
Schoendel et al., 2014. Thus
suggesting that if an individual desire to increase muscular
endurance, they would work with
lower-load in coupled with higher repetitions whereas if the
training goal is strength, they will
work with heavier loads with lower repetitions.
Likewise, Looney et. al. (2015) investigated neuromuscular
activity in vastus lateralis and
vastus medialis quadriceps and RPE during sets that differed in

resistance training utilizing 50%,
70%, or 90% 1 repetition maximum during squat performance
for ten resistance trained men.
The participants were in a randomized within-subject
experiment consisting of 2 test visits: a
drop-set day and a single-set day using only the 50% of 1RM
intensity performed to failure. At
the start of each day, subjects performed 2 submaximal
repetition sets (50% 1RM 3sets of 10
repetitions and 70% 1RM 3sets of 7 repetitions). On the drop-
set day, subjects performed 3
consecutive maximal repetition sets at 90%, 70%, and 50% 1RM
to failure with no rest periods
in between. On the single- set day, subjects performed a
maximal repetition set at 50% 1RM to
failure. The results of the study showed greater peak EMG
amplitude was significantly greater in
the maximal 90% 1RM set than all other sets performed.
However, the RPE did not differ over
the intensity range of loads (Looney et. al.,2015). The data
showing that when muscles are
subjected to higher intensity, will causing greater
neuromuscular activity resulting in increased
muscle performance.

Overall, research has demonstrated when individuals wish to
increase muscular strength
and power it is important to utilize loads between 70% and 90%
of one’s 1RM (Schoenfel et
al.,2014; Schoenfel et al.,2015; Looney et. al.,2015). This is
because the body is being stressed
recruiting and activating the larger type II muscle fibers, which
are stimulated to work when a
muscle is challenged with heavy resistance or working to
fatigue. On the other hand, when an
ACTIVITY 22
individual wish to increase muscular endurance, decreased the
load with higher repetitions
(Baechle & Earle 2008). Therefore, depending on the athletes
specific training goals whether it
be to improve muscular strength or muscular endurance,
manipulating the load to achieve the
desired goal.
In addition to manipulation the load that is being is lifting, one
may also manipulate
training technique such as paired training. Paired set training

which is characterized by
alternating exercises performed by agonist and antagonist
muscles, with or without a pre-
determined rest interval which can decrease the amount of time
required to perform a workout
while completing the same volume load and using paired
training such as “Super Sets” and
“TRI- set” has been suggested as an efficacious method of
enhancing strength (Robbins et al.
2010). Paired training can be utilized as a way to do more
exercises in a given length of time.
While your muscles are recovering from one set, you are
performing another exercise rather than
taking a break.
Freitas Maia et al. (2015), evaluated agonist and antagonist
paired set training on
maximal repetition performance, rating of perceived exertion
and neuromuscular fatigue as
measured by fatigue index. The study consisted of 2
experimental protocols which consisted of
bench press and seated row with either a 2- minute or 4-minute
rest interval between the paired
set. The paired training protocol consisted of performing the
bench press set to repetition failure

followed immediately by a seated row set to repetition failure
utilizing 8-RM loads, respectively.
The results of the study suggest when performing paired set
training, utilizing a shorter rest
interval will induce higher levels of neuromuscular fatigue as
indicated by increased fatigue
indices measured by the EMG power spectrum. However, the
participants that were subjected to
shorter rest interval were able to maintain their muscular
strength while performing as many
ACTIVITY 23
repetitions as the longer rest interval (Freitas Maia et al., 2015).
The results of this study suggest
that pair training during resistance training with little or no rest
periods between exercises will
induce greater metabolic demands causing greater muscular
fatigue. Although, paired training
may induce great neuromuscular fatigue, it has the capacity to
increase muscular performance in
a shorter amount of time.
Moreover, Robbin et al. (2009), examined the chronic effects

on strength and power of
performing complex training versus traditional set training
using loads ranging between 3RM
and 6RM over an eight-week span. Fifteen trained males were
assessed for throw height, peak
velocity, and peak power in the bench press throw and 1 RM in
the bench press and bench pull
exercises using, before and after the eight-weeks. The
traditional set group performed the pulling
before the pushing exercise sets with a 4-minute rest interval,
whereas the complex set group
alternated pulling and pushing sets, and both protocols the
exercises were performed to failure.
The result of the study indicated there were no differences in
the throw height, peak velocity
between the two conditions. However, the bench pulls and
bench press 1-RM increased
significantly for the complex protocol and peak power increased
significantly for the traditional
protocol. In addition, utilizing the complex protocol was more
time-efficient than the traditional
set with respect to development of 1-RM bench pull and bench
press, peak velocity and peak
power (Robbin et al. 2009). Thus the result suggests using

complex set training method would be
effective method of exercise in regards to efficiency and
strength development. The results are in
agreement with the findings of Freitas Maia et al. 2015,
indicating that paired training effective
method of exercise with respect to efficiency and strength
development.
Furthermore, Baker & Newton (2005), investigated the effect
of complex training
consisting of agonist and antagonist muscle exercises (bench
press throw and bench press
ACTIVITY 24
throw/bench pulls) using a standard resistance of 40kg, on
power output, as measured by
Plyometric Power System. The study consisted of twenty-four
college rugby league players
experienced in strength training. They were randomly assigned
to a control group which
performed 5 repetitions on the bench press throw with 3-minute
rest and retested on bench press
throw and an agonist and antagonist group which performed 5
repetitions on the bench press

throw and then performed 8 repetitions of the prone bench pulls
using 50% 1RM, rested 3-
minutes and were retested on the bench press throw. At the
conclusion of the study the data
indicated the power output remained unaltered for the control
group. There was significant
increase for the agonist and antagonist group suggesting
alternating agonist and antagonist
muscle exercises may acutely increase power output during
power training (Baker & Newton,
2005).
In summary, researcher suggests that paired-training may be an
effective training method
for maintaining and improving muscular strength. In addition, it
is an efficient method allowing
for greater amount of work or weight lifted in a shorter period
of time (Freitas Maia et al., 2015;
Robbin et al., 2009; Baker & Newton, 2005).
A third variable that may be manipulated in a resistance
training program with the goal of
improving muscular strength and power is the number of sets or
volume of exercises being
performed during an exercise program. Leite et al (2014)

investigate the effects of performing 1,
3 and 5-sets on measures of muscle thickness, vertical jump
ability, body composition, 5-RM of
the bench press, leg press, front lat pull down and shoulder
press and 20-RM of the bench press
and leg press over a 6-month period. Forty-eight Brazilian Navy
School of Lieutenants with
training experience, were randomly assigned to 1-set, 3- sets, 5-
sets, or control group which
performed body weight exercises such as push-ups, pull-ups,
and abdominal exercises. The
ACTIVITY 25
training program consisted of the following weight training
exercises: bench press, leg press, Lat
pull down, leg extension, Shoulder press, leg curl, biceps curl,
abdominal crunch lying on the
floor and triceps extension using 8-12RM to failure with 90
seconds -120 seconds between sets
and exercises. At the conclusion of the study, the results
showed the 3- and 5-sets groups had
significantly increased elbow flexor/extensor muscle thickness
with the 5-SETS being

significantly great than the others. All training groups decreased
percent body fat, increased fat
free mass and vertical jump ability, with no differences between
groups. The 5-set group also
showed a significantly greater increase than the 1-set and 3-set
group in 5RM for three of the
four exercises tested and no significant difference among
groups in 5RM. The bench press 20-
RM is the 5-sets group had significantly greater increased than
the 3-sets group with 1-set being
the least Lastly, the leg press 20-RM increased in all training
groups, with the 5-sets group
showing a significantly greater increase than the 1-set group
(Leite et al., 2014). The results
indicate that a dose response for the number of sets per exercise
and a superiority of multiple sets
compared to a single set per exercise for strength gains, muscle
endurance and upper arm muscle
hypertrophy.
Mangine et al. (2016) examined and compared the effect of
high-volume resistance
training versus, high-intensity resistance training on
improvements in muscle size and strength in

thirty-three resistance-trained men. The participants were
randomly assigned to either a high-
volume, moderate-intensity group which consisted of 4 sets of
10–12 repetitions with ~70% of
1RM, 1-min rest intervals or a low-volume, high-intensity group
consisting of 4 sets of 3–5
repetitions with ~90% of 1RM, 3-min rest intervals lasting 8
weeks. Pre-training and post
training assessments of lean tissue mass was assessed using dual
energy x-ray absorptiometry.
Muscle cross-sectional area and thickness of the vastus lateralis,
rectus femoris , pectoralis
ACTIVITY 26
major, and triceps brachii muscles was measured using
ultrasound images, Strength was
assessed by measuring 1RM in the back squat and bench press
exercises. Blood samples were
collected at baseline, immediately post, 30 min post, and 60 min
post exercise at week 3 and
week 10 to assess concentration of lactate, testosterone, growth
hormone, insulin-like growth
factor-1, cortisol, and insulin concentrations. The results of this

study indicated high-intensity,
low-volume resistance training utilizing long rest intervals
stimulated significantly greater 1RM
for bench press and lean arm mass gains compared to low -
intensity, high-volume program
utilizing short rest intervals in resistance-trained men. No
differences were noted in the IGF-1
and insulin responses between groups in addition to the
testosterone response but elevate lactate
concentrations were found in both protocols (Mangine et al.,
2016). The data suggests that
working with high-intensity resistance training scheme
stimulates greater improvements in
strength and hypertrophy in resistance-trained men during a
short-term training period.
In summary, research thus far shows manipulating the number
of sets or volume of
exercises being performed can cause an increase in muscular
strength and power during
resistance training. Specifically, When working with higher
intensity such as ~90%1RM,
working between 3 and 5 sets with lower repetitions (3-5 reps)
will invoke greater demands on
physiological responses, however will produce improvement in

muscle performance (Leite et al.,
2014; Mangine et al., 2016).
Furthermore, manipulating training frequency is an important
variable to consider while
training for strength development. Frequency can refer to the
number of resistance training
sessions performed in a given period of time, as well as to the
number of times a specific muscle
group is trained over a given period of time (Schoenfeld et al.
2016). It is recommended that
healthy adults train at least two to three times per week When
training a muscle group it is
ACTIVITY 27
suggested to allow at least 48 hours until training the same
muscle to allow for sufficient
recovery (ACSM 2014).
Arazi & Asadi (2011) investigated the effects of short-term
equal-volume resistance
training with different workout frequency on maximal strength,
endurance, and body
composition in thirty-nine novice lifters. Assessments of body

composition, leg and arm
circumferences by skin fold measurement, body weight.
Strength was measured by one repetition
maximum in bench and leg press and endurance as measured by
bench and leg press using 40%-
60% 1RM performed to complete exhaustion and all
measurements were determined pre and
post 8 weeks of training. The participants were divided into four
groups; total-body resistance
training (12 exercises for one session per week), total -body
resistance training (12 exercises for
two sessions per week), lower-body, upper-body, and upper-
body resistance training (12
exercises for three sessions per week), and control group.
Resistance training programs used
60%1RM to 80% 1RM with 1 set of 6-12 repetitions, and
exercise consisted of leg press, leg
curl, leg extension, calf raise, lat pull-down, lat pull-row, bench
press, pack fly, arm curl,
dumbbell arm curl, triceps push-down, and dumbbell triceps
extension. At the conclusion of the
study the data indicated significant improvements in the 1RM
bench and leg press across all
training groups. Also, body weight, body composition, and

bench and leg press endurance
improved for all groups, but the group which trained 3x week
showed greater improvements. The
group which trained 3x week group had significant improvement
in arm and thigh
circumferences where the 1x week and 2x week groups had
improvements in either other (Arazi
& Asadi, 2011). Thus, suggesting that when resistance training,
either it be whole body or a split
body weight training routine they will produce similar results
over time of training, with greater
improvements in spilt training routine.
ACTIVITY 28
In addition, Ochi et al. (2018) examined the effects of two
knee-extension training
programs using, which consisted of the same training volume
but differed in training frequency.
It looked at the changes in muscle size and strength during an
11-week training and a subsequent
6-week detraining period. During a training period of 11 weeks,
untrained subjects performed

knee-extension exercise at 67% of their estimated one-repetition
maximum either one session per
week consisting of 6 sets of 12 repetitions per session or three
sessions per week consisting of 2
sets of 12 repetitions per session. Rating of perceived exertion
and muscle stiffness were
measured as an index of muscle fatigue. Muscular size was
assessed with thigh circumference
and the quadriceps muscle thickness. Lastly, changes in muscle
strength were measured with
isometric maximum voluntary contraction torque. At the
conclusion of their study, it showed
both groups showed significant increases in thigh
circumference, muscle thickness, estimated
1RM, and maximum voluntary contraction compared with
baseline measurement, while RPE
during exercise was significantly higher in the 1x week group
than in the 3x week group. More
importantly, there was a significantly higher maximum
voluntary contraction levels for the 3x
week group compared to 1 x week group. Lastly, both groups
had significant decreases in in
thigh circumference and muscle thickness from those at the end
of training period, while no

significant effect of detraining was observed in MVC (Ochi et
al.,2018). Thus, indicating that
utilizing the three training sessions per week with two sets are
recommended for untrained
subjects to increase muscle strength while reducing fatigue
levels compared to one session per
week with a comparable work load. The results from their study
are in agreement with Arazi &
Asadi (2011), that increase in training frequency of 2x-3x a
week, will produce great muscular
improvements when compared to lower frequency, 1x a week
training protocols.
Furthermore, Gentil et al. (2014) investigated the effects of
equal-volume resistance
ACTIVITY 29
training performed once or twice a week on muscle mass and
strength of the elbow flexors in
untrained young men. Pre and post-test elbow flexors muscle
thickness were measured using
ultrasound and Peak torque was assessed by an isokinetic
dynamometer. Thirty men without
previous resistance training experience were divided into two

groups: Group 1 trained each
muscle group only once a week and group 2 trained each muscle
twice a week during 10 weeks.
Both groups performed 2 sets of 8 – 12 repetitions of the
following exercises: lat pull down,
seated row, barbell bench press, seated chest press, standing
barbell biceps curl, Scott bench
biceps curls, lying barbell triceps extensions and high pulley
triceps extension. The weight using
as adjusted from set to set allowing participants to complete the
desired repetitions range. The
data from the present study proposed that untrained men
experience similar improvements in
muscle mass as well as increases in muscular strength
regardless of the training frequency
(Gentil et al., 2014). Although not significant when examining
the data it appears that the
individuals in the 2x week training protocol showed greater
levels of improvement. Thus,
suggesting it favorable an increased training frequency for
favorable strength gains.
In summary, it is recommended that healthy adults train at
least two to three times per
week. When training muscle groups it is suggested to allow at

least 48 hours before training the
same muscle to allow for sufficient recovery (ACSM 2014).
Moreover, research has shown that
increasing resistance training frequency to 2x week or more will
impose significant increases in
muscular strength and power. (Arazi & Asadi, 2011; Ochi et
al.,2018; Gentil et al., 2014).
The last variable which may be manipulated in a resistance
training program with the
goal of improving strength and/or power is rest time, which can
be defined as the time dedicated
to recovery between sets and exercises (Grgic et al., 2017).
Marshall et al. (2012) investigated
changes in motor unit recruitment, maximal force, and rate of
force development and fatigue
ACTIVITY 30
response as measured by surface EMGs using 80% 1RM for
fourteen resistance trained male
participants. The participants were subjected to various
protocols with the difference between
inter-set rest, (A) 5 sets of 4 repetitions with 3-minute rest
interval, (B) 5 sets of 4 repetitions

with 20-second rest interval, and rest-pause technique,
repetitions performed to failure and rested
for 20s until 20 repetitions were amassed. and the effects on the
back-squat. The results indicate
the rest-pause method elicited the greatest increases in motor
unit recruitment for all muscle
measured during the squat exercise compared to protocol A, and
protocol B, and all groups
showed a decrease in power output as measured by decreases in
EMG levels. Also, the rest-
pause method showed no significant changes in EMG levels
indicating that it was no more
fatiguing post-exercise than protocol A or B which did not
include failure based repetitions
(Marshall et al., 2012). The data collected indicated the rest-
pause method as a superior method
of training which allows for greater amount of work done in less
time and facilitated an increase
in motor unit recruitment compared to protocol A and B.
Additionally, Martorelli et al. (2012) investigated rest
intervals and the effects on
neuromuscular activity as measured by surface EMG and blood
lactate concentration in the

Rectus Femoris, Vastus Medialis and Vastus Lateralis of twelve
men performing squat training.
The protocol consisted of six sets of six repetitions using
60%1RM with rest intervals of 1-
minute, 2-minutes and 3-minutes which took place 3 to 7 days
after the 1RM retest. At the
conclusion of the study, there was no significant difference
between rest intervals on power
output across rest intervals. However, although not signi ficant,
there was a decrease in peak
power and average power for all rest intervals with 2-minute
rest interval having the largest
decrease. Moreover, there was no significant difference in blood
lactate concentration across the
rest intervals but lactate concentrations were significantly
higher post-training compared to pre-
ACTIVITY 31
training levels (Martorelli et al., 2012). These findings are not
consistant with previous findings
suggesting that independent of the increase in blood lactate,
muscle power performance
remained stable. The results of this study appear to suggest that

regardless of rest interval
between sets, power output was maintained during squat
exercise throughout the exercise session
in twelve resistance-trained men.
Moreover, Tibana et al. (2013) examined the effect of rest
interval length on smith
machine bench press on performance, muscular power, total
training volume, velocity, and
ratings perceived exertion for ten recreationally trained men.
The participants performed five sets
of varying repetitions using 60% of their one-repetitions
maximum, with either a 1.5 minutes or
3-minute rest period between each set. The results indicated
there was a significantly higher
mean, relative and peak power output, as well as higher average
velocity, volume and number of
repetitions for the 3-minute rest interval compared to the 1-
minute interval. (Tibana et al., 2013).
However, the researchers did not include any metabolic or
neurological outcomes to enhance the
understanding as to why there may be a difference in muscular
power between the two rest
intervals,

More recently, Davó et al. (2016) investigated various rest
interval periods (1 minute, 2
minutes, and 3 minutes) used between bench press throw sets on
mechanical and physiological-
perceptual responses during strength training session using 40%
of one repetition maximum.
The mechanical outcome or power output and physiological
outcomes which included fatigue
and lactate concentration. Davó et al. (2016) and colleagues
found there was a significant
difference in power outputs, lactate concentration and fatigue
between the three different rest
time intervals; specifically, during the 1-minute training
interval showed a greater decrease in
power output accompanied by increased levels of blood lactate
concentrations and increased
ACTIVITY 32
levels of fatigue whereas there was no difference found when
comparing the 2-minute and 3-
minute rest interval group. However, Davó et al. (2016) noted
that a limitation of their study as
that they did not measure neuromuscular activity during the

study, which is significant because
this could provide additional insight as to if the power reduction
observed in the study was also
due to neurological factors, like fatigue. Thus, future research
is needed to investigate possible
neurological mechanisms that may contribute to the observed
decrease in power.
Optimizing different training variable such as %-1RM, paired
training, volume/sets,
training frequency and rest time during will influence the
effectiveness of a resistance training
program that is structured around improving strength and/or
power. Several factors may be
considered when developing a strength training program, such
as % of one’s 1-reptition
maximum, number of sets and repetition, frequency of training,
and rest time between sets.
Research has demonstrated that strength gains may be optimized
when a program consist of
loads between 70% and 90% of one’s 1RM, working between 3
and 5 sets with lower repetitions
(3-5 reps) and training a minimum of two times per week (Leite
et al., 2014; Mangine et al.,
2016; Arazi & Asadi, 2011; Ochi et al.,2018; Gentil et al.,

2014). Research regarding the optimal
rest time interval and how it affects mechanical and
physiological variables that contributes to
fatigue has been inconsistent (Marshall et al., 2012; Martorelli
et al., 2012; Davo et al. 2015;
Tibana et al. 2013). However, previous research has not taken
neural measurements to explore
the impact of rest time intervals on neuromuscular system.
Fatigue can alter overt performance,
such that the task is performed more slowly or clumsily or even
cannot be performed
successfully, or it can alter the neuromuscular activity required
to perform the task and this may
be evident as increased electrical activity of the muscle (Taylor,
2016.)
Therefore, the purpose of this study is to investigate the effect
of 1- minute rest interval
ACTIVITY 33
on neuromuscular activation, and rate of perceived exertion
during the chest press exercise
performed at 40% 1RM. Improving our understanding about the
optimal rest period may allow

for improved design of power and strength programs.
ACTIVITY 34
CHAPTER 3
METHODS
The purpose of this study was to explore the effects of 1-
minute rest interval on
neuromuscular activation, rate of perceived exertion and fatigue
during the chest press exercise.

Maximizing neuromuscular activation will improve the
communication between the nervous
system and musculoskeletal increasing motor unit recruit as
well as increasing neural firing
patterns. Improving the nervous system and musculoskeletal
system interaction in turn will
maximize performance. Determining the optimal rest interval
can be beneficial for coaches,
trainers, and or clinicians who wish to construct training
protocols or rehabilitative programs to
optimize athletic performance.
Participants
To be eligible, the participants had to be a male that engaged in
regular physical activity,
quantified as at least 150 minutes of moderate physical activity
for past 3 months, and was
between 18 - 30 years of age. The 150 minutes of physical
activity consisted of a combination of
aerobic and resistance exercises. The participants were recruited
from Kean University, Union,
NJ. Participants were required to complete an informed consent
form, and a Physical Activity
Readiness Questionnaire (PAR-Q) to determine if the
participants were qualified to exercise,

ensure their safety and have a low risk of having any medical
complications.
Materials
After to the completion of the informed consent form, and the
Physical Activity Readiness
Questionnaire (PAR-Q). Measurements of each participant’s
height and weight were obtained
and recorded. The height, weight, percent body fat, and body
mass index were assessed using
ACTIVITY 35
Bioelectrical impedance analysis (BIA) Tanita TBF-410GS
Body Composition Analyzer Scale.
The participants were not to eat or drink within four hours the
test, no exercise within twelve
hours of the test, urinate within 30 minutes of the test, not
taking any diuretic medications and no
alcohol consumption with 48 hour of the test (Haff & Dumke.,
2012). In addition, the
participants were instructed to remove their socks and shoes,
jewelry, and anything else that
would weight them down, in order to enable the most accurate

assessment.
Surface Electromyograms (EMG)
To record neuromuscular activity during this study, surface
electromyogram was utilized.
The surface EMG (BTS FREEEMG 1000) probes were placed on
both left and right pectoralis
major along the sternal boarder. Another set of probes were
placed on the left and right lateral
head of the triceps brachii . The probe placements were
selected because the pectoralis major
and triceps brachii were shown to have higher neuromuscular
activity and are the more dominant
muscles during the bench press (Stastny et al., 2017).
Design and Procedure
Dynamic Warm-up
Prior to assessing muscular strength and endurance, the
participants performed a 5-
minute dynamic warmup with an additional 5 minutes spent on a
treadmill with a walking speed
of 2.5 – 3.0 mph. The warmup procedure intended to prepare
the body by loosening up the
joints and targeting the muscles being utilized during the study.

1RM Bench Press Test
After the dynamic warm, the participants made their way to the
fitness room where they
were tested for their one repetition maxi mum (1RM). While
performing the bench press 1RM each
participant had a spotter to provided assistance when needed.
The participants were instructed to
ACTIVITY 36
maintain five points of contact with the floor or bench: head,
shoulders and upper back, right foot,
left foot and buttocks. The participants were instructed to lower
the bar in controlled manner to
touch his chest at approximately nipple height while
maintaining the five points of contact and
inhale. The participant pushed the bar upward until his elbows
were fully extended while
maintaining the five points of contact and exhale. The first set
was considered their warm up set
and was performed with just the bar for 15 repetitions. After the
warm up was completed, the load
was changed to 40% to 60% of their perceived maximum and
instructed to complete 5 to 10

repetitions. The load was changed to the predetermine second-
set load. Between the set the
participants were given one minute to rest. After the one-minute
rest interval, the participants
performed 3 to 5 repetitions with a load that is 60% to 80% of
perceived maximum. After
completion of set 3, the participants rested for three minutes
while the load was changed to 90%
of perceived maximum. After the three-minute rest, the
participants performed 1 repetition with
the 90% load. The participant was given a three-minute rest,
while the load was increased,
depending upon how well they performed the previous attempt.
If the previous set appeared
relatively easy, increase the load by 5kg to 10kg; if, however
the previous attempt was difficult
increase by 1kg to 5kg. The participant continued to perform
only 1 repetition until a 1 rep max
was achieved. If an attempt was unsuccessful, the load was
reduced but kept above the last
successful set and given a three-minute rest until he was
successful.
Testing procedure

The study consisted of 2 experimental sessions in a 1-week
period. The first session
consisted of a completing necessary paper work, anthropometric
measurements, and a one
repetition bench (1RM) test for bench press. The subsequent
session consisted of a strength
training protocol which included 5 sets of 8 repetitions, using
40% of 1RM for the bench-press
ACTIVITY 37
exercise, and subjected to a 1-minute rest interval. The
variables investigated during the study
were level of neuromuscular activity, rating of perceived
exertion (RPE), and fatigue. All
participants were familiarized with all equipment used for
testing and training, and a
familiarization session was performed during the one repetition
maximum test. Furthermore, in
an attempt to avoid diurnal variation in test measures, subj ects
were scheduled at approximately
the same time for each testing and training session. To limit
experimental variability, the same
qualified primary investigator conducted and supervised all

testing sessions.
The participants performed the experimental protocol in 1
session which consisted of a 1-
minute rest interval between sets. Through each set, subjects
were encouraged to press the
barbell with as much force as possible. Participants began by
laying horizontally and were
instructed to maintain five points of contact with the floor or
bench: head, shoulders and upper
back, right foot, left foot and buttocks. The participants were
instructed to lower the bar in
controlled manner to touch his chest at approximately nipple
height while maintain the five
points of contact and inhale. Lastly, participant pushed the bar
upward until his elbows were
fully extended while maintaining the five points of contact and
exhale. The repetition was not
counted if the barbell was not lowered touching the chest. Also,
no bouncing of the barbell was
allowed. Between each set, the participant was shown a Borg 10
scale and instructed to choose a
number from 0 (no effort) to 10 (Max effort).
Statistical Analyses

All data were analyzed using the statistical software package
SPSS version 22.0. A
repeated-measures ANOVA was utilized to evaluate the
influence of the one-minute rest interval
on neuromuscular activity, and rate of perceived exertion during
the bench press. A significance
ACTIVITY 38
level of p <.05 was used to determine if there was any
significant difference amongst the
variables tested. In addition, a Wilks' lambda test was used to
determine if there are differences
between the means and maximum of identified groups of
subjects on a combination of dependent
variables. Furthermore, a Mauchly’s test for Sphericity was
conducted to investigate if there
were any violations.

ACTIVITY 39
CHAPTER 4
RESULTS
Research has demonstrated the rest time intervals affect
mechanical and physiological
variables, which in turn, may reduce power output during the
bench press exercise performed at
40% of the 1 repetition maximum. However, previous research
has not taken neural
measurements to explore the impact of rest time intervals on
neuromuscular activation. The
information gathered will enhance our understanding rest
interval and the effects on
neuromuscular activation. Moreover, this will allow us to
determine if the 1-minute rest interval
provides sufficient recovery time for the neuromuscular
systems. The purpose of this study was

to investigate the effects of 1-minute rest interval on
neuromuscular activation, during the chest
press exercise.
A repeated-measures ANOVA was utilized to evaluate the
influence of the one-minute
rest interval on neuromuscular activity, and rate of perceived
exertion during the bench press. All
data gathered during this study is present below in several
tables and figures.
Descriptive Data of Sample
Twelve (N = 12) physical active males were recruited to
participate in the present study.
All data gathered during this study is present below in several
tables and figures. Table 1
displays the descriptive statistics for twelve physically activate
male participants. Displays Age,
Height, Weight, Body fat%, BMI and the result from a one
repetition maximum test performed.
The age for the 12 male participants ranged from 20 years of
age to 28 years of age with a mean
age of 23.67 ± 2.67. The height for the 12 male participants
ranged from 190.50 cm to 165.10cm
with a mean height of 175.68 ± SD 8.9. The weight for the
participants ranged from 60.91Kg to

101Kg with a mean weight of 82.31kg ± 14.1. The body fat
percent for the 12 male participants
ACTIVITY 40
ranged from 7.30% to 25.70% with a mean of 15.28% ± SD
5.23. The mean boy fat percent for
the 12 male participants is considered to be average (14.1% -
17.5%) below average (17.4% -
22.5%) categories (ASCM, 2014). Body mass index (BMI)
ranged from 20.30 Kg/m2 to 33.00
Kg/m2 with mean BMI of 26.56 ± 3.84 Kg/m2. (The 1RM
ranged from 65.91Kg to 136.36 Kg
with the mean 1RM 109.24 ± 21.55Kg presented in Table 1.
Table 1
Descriptive Statistics
Table 1 displays the descriptive statistics for twelve physically
activate male participants.
Displays Age, Height, Weight, Body fat%, BMI and the result
from a one repetition maximum
test performed.
The 12 participants completed 2 experimental sessions lasting

1-week long. During the
first session, the participants had their 1 repetition maximum
(RM) were tested (Table 1). The
subsequent session consisted of a strength training protocol
which included 5 sets of 8
repetitions, using 40% of 1RM for the bench-press exercise, and
subjected to a 1-minute rest
interval. Surface EMG probes were placed on left and right
Pectoralis Major muscles on the
sternal borders, and left and right lateral heads of the Triceps
Brachii to assess neuromuscular
activity within the muscles.
Table 2 through Table 5 display the mean, maximum and
standard deviations of the EMG
data for the left and right Pectoralis Major and Triceps Brachii
obtained during the 5 sets.
N Minimum Maximum Mean Std. Deviation
Age (Yrs.) 12 20.00 28.00 23.67 2.67
Height (Cm) 12 165.10 190.50 175.68 8.92
Weight (Kg) 12 60.91 101.59 82.31 14.14
Body Fat % 12 7.30 25.70 15.28 5.23
BMI 12 20.30 33.00 26.56 3.84
1 RM (Kg) 12 65.91 136.36 109.24 21.55

ACTIVITY 41
Immediately after completing the set, the participant was to
rate their level exertion and
fatigue utilizing a Borg 10 scale (Table 6).
Table 2
Right Pectoralis Mean and Maximum Neuromuscular Activation
Right Pectoralis
Mean Activation
(mV)
Std.
Deviation
Right Pectoralis
Maximum Activation
(mV)
Std.
Deviation
Set 1 0.17 0.080 0.550 0.231
Set 2 0.16 0.067 0.566 0.223
Set 3 0.17 0.075 0.576 0.280
Set 4 0.16 0.070 0.570 0.226
Set 5 0.16 0.070 0.566 0.223
Table 2 displays the mean and maximum neuromuscular

activation for the Right
Pectoralis Major for each set.
Table 3
Right Triceps Mean and Maximum Neuromuscular Activation
Right Triceps Mean
Activation
(mV)
Std.
Deviation
Right Triceps
Maximum Activation
(mV)
Std.
Deviation
Set 1 0.157 0.083 0.437 0.244
Set 2 0.150 0.070 0.430 0.206
Set 3 0.148 0.072 0.423 0.215
Set 4 0.143 0.062 0.400 0.172
Set 5 0.136 0.060 0.383 0.161
Table 3 presents the mean and maximum neuromuscular
activation for the Right Triceps
for each set.

activation for the left pectoralis
major.
ACTIVITY 42
Table 4
Left Pectoralis Mean and Maximum Neuromuscular Activation
Left Pectoralis
Mean Activation
(mV)
Std.
Deviation
Left Pectoralis
Maximum Activation
(mV)
Std.
Deviation
Set 1 0.140 0.065 0.497 0.244
Set 2 0.142 0.065 0.522 0.269

Set 3 0.143 0.069 0.529 0.263
Set 4 0.147 0.071 0.553 0.313
Set 5 0.146 0.073 0.519 0.260
activation for the left triceps for
each set.
Table 5
Left Triceps Mean and Maximum Neuromuscular Activation
Left Triceps Mean
Activation
(mV)
Std.
Deviation
Left Triceps Maximum
Activation
(mV)
Std.
Deviation
Set 1 0.156 0.060 0.418 0.156
Set 2 0.144 0.050 0.402 0.138
Set 3 0.142 0.047 0.400 0.146
Set 4 0.138 0.044 0.391 0.121
Set 5 0.135 0.042 0.398 0.142

Table 6 shows the mean Rate of Perceived exertion for all sets
performed by the twelve
male participants.
Table 6
Mean Rate of Perceived Exertion
RPE Std. Deviation
Set 1 1.08 0.29
Set 2 1.58 0.79
Set 3 1.83 0.83
Set 4 2.08 0.79
Set 5 2.25 0.87
ACTIVITY 43
Table 7 displays the results of the Mauchly’s Test of Sphericity,
which is an important
assumption of a repeated-measures ANOVA. Sphericity refers
to the condition where
the variance of the differences between all possible pairs of
within-subject conditions are equal.
The violation of Sphericity occurs when it is not the case that
the variances of the differences

between all combinations of the conditions are equal.
Mauchly’s Test of Sphericity indicates that the assumption of
Sphericity has not been
violated for right Pectoralis mean activation X2(9) = 15.61, p =
.080, right Pectoralis max
activation X2(9) = 7.93, p = .55, left Pectoralis mean activation
X2(9) = 12.56, p = .19, left
Triceps max activation X2(9) = 3.70, p = .93, and RPE X2(9) =
10.81, p = .30.
In addition, Mauchly’s Test of Sphericity shows that the
assumption of Sphericity has
been violated for the Right Triceps mean X2(9) = 32.47, p =
.000 and maximum activation X2(9)
= 29.67, p = .001, Left Pectoralis Major maximum activation
X2(9) = 21.33, p = .012, and Left
Triceps mean activation, X2(9) = 31.04, p = .000. Lower-bound
estimate, Greenhouse-Geisser
correction and the Huynh-Feldt correction are will be used in
future tests to combat the violation
of Sphericity.

ACTIVITY 44
Table 7
Within Subjects Mauchly's Test of Sphericity
Measure Mauchly's
W
Approx.
Chi-
Square
df Sig. Epsilonb
Greenhouse-
Geisser
Huynh-
Feldt
Lower-
bound
Right
Pectoralis
Mean
Activation
0.19 15.61 9 0.080 0.53 0.665 0.25
Right
Pectoralis Max

Activation
0.43 7.93 9 0.55 0.74 1.0 0.25
Right Triceps
Mean
Activation
0.032 32.47 9 0.000 0.38 0.43 0.25
Right Triceps
Max
Activation
0.043 29.67 9 0.001 0.43 0.50 0.25
Left Pectoralis
Mean
Activation
0.26 12.56 9 0.19 0.62 0.82 0.25
Left Pectoralis
Major Max
Activation
0.10 21.33 9 0.012 0.46 0.54 0.25
Left Triceps
Mean
Activation

0.037 31.04 9 0.000 0.38 0.43 0.25
Left Triceps
Max
Activation
0.68 3.70 9 0.93 0.82 1.0 0.25
RPE 0.32 10.81 9 0.30 0.70 0.97 0.25
ACTIVITY 45
Table 8 displays the results for Multivariate tests and tests of
within-subjects effect for
neuromuscular activation. The multivariate test for within
subject’s effect indicates that there is
a significant within-subjects effect V = 1.11, F (36,136) = 1.66,
Table 8
Multivariate Test for Within Subjects Effect.
Within Subjects
Effect Value F

Hypothesis
df
Error
df Sig.
Partial
Eta
Squared
Noncent.
Parameter
Sets
Pillai's
Trace
1.11 1.66 36 156 0.020 0.28 59.57
Wilks'
Lambda
0.180 2.21 36 136.65 0.001 0.35 73.44
Hotelling's
Trace
3.14 3.01 36 138 0 0.44 108.28
Roy's
Largest
Root
2.67 11.55 9 39 0 0.73 103.98

Follow-up Univariate tests were performed to determine within
which set for a muscle
group did have a significant difference in mean or maximum
EMG data occur.
Table 9 displays the result from a univariate test for within-
subject effects for Right
Pectoralis mean activation. Table 9 indicates there was no
significant difference in mean
neuromuscular activation for the right Pectoralis Major within
the 5 sets, F (4,44) = 1.073, p =
.0381.
ACTIVITY 46
Table 9
Univariate Test for Right Pectoralis Mean Activation
Source Measure Type

III Sum
of
Squares
df Mean
Square
F Sig. Partial
Eta
Squared
Noncent.
Parameter
Pectoralis
Mean
Activation
Sphericity
Assumed
0.001 4 0 1.073 0.381 0.089 4.292
Greenhouse-
Geisser
0.001 2.133 0 1.073 0.362 0.089 2.289
Huynh-Feldt 0.001 2.661 0 1.073 0.37 0.089 2.855
Lower-
bound

0.001 1 0.001 1.073 0.323 0.089 1.073
Pectoralis max activation. Table 10 indicates there was no
significant difference in maximum
neuromuscular activation for the Right Pectoralis Major within
the 4 sets, F (4,44) = 0.247, p =
.91.
Table 10
Univariate Test for Right Pectoralis Max Activation
Source Measure Type
III Sum
of
Squares
df Mean
Square
F Sig. Partial
Eta
Squared
Noncent.
Parameter

Right
Pectoralis
Max
Activation
Sphericity
Assumed
0.004 4 0.001 0.247 0.91 0.022 0.988
Greenhouse-
Geisser
0.004 2.967 0.001 0.247 0.861 0.022 0.733
Huynh-Feldt 0.004 4 0.001 0.247 0.91 0.022 0.988
Lower-
bound
0.004 1 0.004 0.247 0.629 0.022 0.247
ACTIVITY 47
Triceps mean activation. Table 11 indicates there is a

neuromuscular activation for the Right Triceps for within-
subjects over the time of the sets, F
(1.51,16.62) = 4.54, p = .035.
Table 11
Univariate Test for Right Triceps Mean Activation
Source Measure
Type
III Sum
of
Squares
df Mean Square F Sig.
Partial
Eta
Squared
Noncent.
Parameter
Right
Triceps
Mean
Activation
Sphericity
Assumed 0.003 4 0.001 4.54 0.004 0.29 18.16
Greenhouse-

Geisser 0.003 1.51 0.002 4.54 0.035 0.29 6.86
Huynh-Feldt 0.003 1.70 0.002 4.54 0.030 0.29 7.72
Lower-
bound 0.003 1 0.003 4.54 0.057 0.29 4.54
Triceps max activation. Table 12 indicates there is not a
significant difference in maximum
neuromuscular activation for the Right Triceps for within-
(1.70, 18.73) = 3.16, p = .072.
ACTIVITY 48
Table 12
Univariate Test for Right Triceps Max Activation

subject effects for the Left
Pectoralis mean activation. Table 13 indicates there is not a
neuromuscular activation for the Left Pectoralis Major for
within-subjects over the time of the
sets, F (4,44) = 1.07, p = .379.
Table 13
Univariate Test for Left Pectoralis Mean Activation
Source Measure Type
III Sum
of
Squares
df Mean
Square
F Sig. Partial
Eta
Squared
Noncent.
Parameter
Left
Pectoralis
Mean

Activation
Sphericity
Assumed
0 4 9.52 1.077 0.379 0.089 4.31
Greenhouse-
Geisser
0 2.49 0 1.077 0.366 0.089 2.683
Huynh-Feldt 0 3.276 0 1.077 0.375 0.089 3.53
Lower-
bound
0 1 0 1.077 0.322 0.089 1.077
Source Measure
Type
III Sum
of
Squares
Partial
Eta
Squared
Noncent.

Parameter
Right
Triceps
Max
Activation
Sphericity
Assumed 0.024 4 0.006 3.16 0.023 0.223 12.64
Greenhouse-
Geisser 0.024 1.702 0.014 3.16 0.072 0.223 5.379
Huynh-Feldt 0.024 1.982 0.012 3.16 0.063 0.223 6.263
Lower-
bound 0.024 1 0.024 3.16 0.103 0.223 3.16
ACTIVITY 49
Table 14
Univariate Test for Left Pectoralis Maximum Activation
Source Measure
Type
III Sum
of
Squares

Partial
Eta
Squared
Noncent.
Parameter
Left
Pectoralis
Max
Activation
Sphericity
Assumed 0.019 4 0.005 1.09 0.376 0.09 4.339
Greenhouse-
Geisser 0.019 1.82 0.011 1.09 0.351 0.09 1.974
Huynh-Feldt 0.019 2.161 0.009 1.09 0.358 0.09 2.344
Lower-
bound 0.019 1 0.019 1.09 0.32 0.09 1.085
subject effects for the Left
Pectoralis max activation. Table 14 indicates there is no
neuromuscular activation for the Left Pectoralis Major for
within-subjects over the time of the

sets, F (4,44) = 1.09, p = .351.
Table 15
Univariate Test for Left Triceps Mean Activation
Source Measure
Type
III Sum
of
Squares
Partial
Eta
Squared
Noncent.
Parameter
Left
Triceps
Mean
Activation
Sphericity
Assumed 0.003 4 0.001 7.34 0 0.4 29.35
Greenhouse-
Geisser 0.003 1.53 0.002 7.34 0.008 0.4 11.19
Huynh-Feldt 0.003 1.72 0.002 7.34 0.006 0.4 12.63

Lower-
bound 0.003 1 0.003 7.34 0.02 0.4 7.34
ACTIVITY 50
subject effects for Left
Triceps mean activation. Table 15 indicates there is a
neuromuscular activation for the Left Triceps for within-
(1.53,20.8) = 7.34, p = .008.
Table 16
Univariate Test for Left Triceps Maximum Activation
Source Measure Type
III Sum
of
Squares
df Mean
Square
F Sig. Partial

Eta
Squared
Noncent.
Parameter
Left
Triceps
Max
Activation
Sphericity
Assumed
0.005 4 0.001 1.09 0.38 0.09 4.34
Greenhouse-
Geisser
0.005 3.28 0.001 1.09 0.37 0.09 3.56
Huynh-Feldt 0.005 4 0.001 1.09 0.38 0.09 4.34
Lower-
bound
0.005 1 0.005 1.09 0.32 0.09 1.09
subject effect for Left Triceps max
activation. Table 16 indicates there is not a significant
difference in maximum neuromuscular

activation for the Left Triceps for within-subjects over the time
of the sets, F (4,44) = 1.09, p =
.38.
subjects effect for RPE.
Table 17 indicates there is a significant difference in Rate of
Perceived Exertion for within-
subjects over the time of the sets, F (4,44) = 1.09, p = 0.38.
ACTIVITY 51
Table 17
Univariate test for Rate of Perceived Exertion
Source Measure Type
III Sum
of
Squares
df Mean
Square
F Sig. Partial

Eta
Squared
Noncent.
Parameter
RPE
Sphericity
Assumed
10.067 4 2.517 11.615 0.000 0.514 46.462
Greenhouse-
Geisser
10.067 2.804 3.591 11.615 0.000 0.514 32.564
Huynh-Feldt 10.067 3.861 2.608 11.615 0.000 0.514 44.841
Lower-
bound
10.067 1 10.067 11.615 0.006 0.514 11.615
A post-hoc Pair-Wise Comparison between sets was conducted
to determine between
which set there was a significant difference for neuromuscular
activation. The data indicated
there was a significant difference in mean neuromuscular
activation for Right Triceps between

EFFECTS OF REST INTERVALS ON NEUROMUSCULAR ACTIVITY i

EFFECTS OF REST INTERVALS ON NEUROMUSCULAR ACTIVITY i

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