The that particular muscle.2 In analyzing data concerning muscular

The acute effects of power and high resistance circuit training programs on balance, fatigue and agility in Division II Lacrosse Players. PHTH 654: Research Symposium  Sandy Ross, PT, DPT, MHS, PCSKatlin Abt, SPTJordan Green, SPTJeremy Kertz, SPTCam McCullough, SPTDevan Wright, SPTFaculty Advisor: Jack Bennett, PT, DPT, SCS, M.Ed, CSCSFebruary 9, 2018INTRODUCTION    When an athlete’s performance declines late in the event, it is generally attributed to fatigue. In regard to sports, fatigue can be defined as an overall decrease of the athletic capabilities of that individual as a result of exercise.1 Fatigue has already been discussed in the literature as a cause for decline in several aspects of performance, including muscle force, motor skill execution, and muscle and whole body power.1 Muscle fatigue, in general, is when only sub-maximal contractions can be reached due to prolonged use of that particular muscle.2 In analyzing data concerning muscular fatigue, it is important to understand the role that different body systems and environment hold. Like all body organs, muscle requires adequate nutrition in order to perform its function. This includes ample supply of protein, enzymes, hormones and many other biological factors. Appropriate muscle activation also requires the motor cortex to command and generate action potential through motor units. A decrease in voluntary activation will produce a decrease in muscle force and thus a decrease in athletic performance. This has been shown by several studies seeking to find the correlation between muscle performance and voluntary activation. Babault et al., 2006, found an 8.1% decrease in maximum voluntary contraction torque and 2.1% decrease in voluntary activation following three maximal concentric contractions, while also finding an 8.6% decrease in maximum voluntary contraction torque and 3.8% decrease in voluntary action following three maximal isometric contractions. While there is no evidence of the specific percentage of contribution to muscle fatigue, deficits in both or either of these systems may lead to decrease in maximal performance. Reliable data showing the relationship between fatigue and resistance exercise programs would immensely facilitate and change the way that athletes, trainers, and therapists condition for specific sports in order to better accommodate for fatigue-induced balance deficits. Izquierdo et al., 2009, utilized heavy resistance training protocols to determine the effect of high resistance training on fatigue. They found after this short-term training, peak power lost was greater, blood lactate accumulation was higher and loss of maximal strength was higher compared to their pre-training statistics.4  Based on the findings of this study, several outcome measures have been found to be impacted by heavy resistance training; to add to the current literature, we believe it would be beneficial to explore the effects it has on balance. A vital component to consider when examining the relationship between resistance exercise and fatigue includes the specific type of resistance protocol being used. The two types of programs often used are high resistance training and/or power circuit training. It was found that when using the Borg CR-10 Scale, high resistance training was perceived as “very hard”, and the power circuit training was perceived as “somewhat hard”; therefore, it was concluded that high resistance training produces greater intensity than power circuit training and rest.5 When comparing high resistance and power circuit training, similar results were found with outcome measures such as vertical jumps and repeated-sprint ability and agility. Freitas et al., 2016, showed that when you perform in high resistance training you have increased fatigued compared to power training, and in turn experience a negative effect on the performance outcomes.Assessing the relationship between fatigue and balance has shed light on several conclusions. Hosseinimehr et al., 2010, found that fatigue results in a meaningful reduction in all eight directions of the Star Excursion Balance Test (SEBT) based on the results of the t-test difference between the pre and post test measures in college athletes. In contrast, when looking at static postural control there was no significant difference between pre and post test measures. Due to the fact that a person has minimum movement in his or her base of support during static postural control, the body compensates for the defect in balance secondary to fatigue by recruiting other systems (vision, vestibular, and somatosensory); therefore, no significant difference was found between pre and post test results. From this information, it can be concluded that it’s more beneficial to assess dynamic balance over static balance when applying it to fatigue.  Although it is an unrealistic expectation for a coach to stop practice or decrease practice times because of fatigue, which may lead to injury, this topic needs further attention.6Majid Fatahi et al. also looked at the relationship between fatigue and balance. They used the Biodex system to fatigue the rectus femoris, hamstrings, tibialis anterior, and gastrocnemius to 50% of their maximum contraction.  Immediately after, they performed the Y-Balance test. It was found that an individual requires core stability, neuromuscular control, and proprioception in order to be successful in the SEBT test, which the Y-Balance test was a derivative of.8,9 The results concluded that the performance of the Y-Balance test were significantly reduced after fatiguing all muscles.  Electrodes were placed on all the muscles and showed that the activity of all the muscles significantly decreased after the fatiguing protocol.  Based on the results, we can conclude that because the muscles were fatigued, the participants did not have the neuromuscular control, stability, and proprioception in their lower extremity to successfully perform the Y-Balance test.Performance outcomes should be a major concern for physical therapists as recent research has found that decreases in certain performance measures have been linked to an increase in incidence of injury. For instance, decrease in balance performance can be a strong predictor for lower limb injury in high school basketball players.10 Plisky et al., 2006, used the SEBT as a Predictor of Lower Extremity Injury in High School Basketball Players in order to find a correlation between preseason SEBT measurements and incidence of lower extremity injuries. They took bilateral balance measures for all the athletes and looked at their limb lengths. They found a 2.5 greater risk for injury in those athletes that had a difference of 4 cm or more in the anterior reach test and 6.5 greater risk in girls whose reach distance was less than 94% of their limb length.10 While this study focused on the affects of balance on injury, further research is needed to determine the affects of training on balance. Research studies such as these can help healthcare professionals identify and understand mechanisms of injury, which then can in turn help establish injury prevention protocols.With this current knowledge about deficits in balance leading to injury, it is important to take into consideration the timing of these injuries as well. Kyle Nagle et al. conducted a study using a variety of high school sports (men and women’s basketball, lacrosse, soccer, men’s football and ice hockey, and women’s field hockey) looking at the timing of injuries in practice vs. competition.  In mens lacrosse, the rate of injury per 10,000 athlete exposures were greater in competition compared to practice, 1.9 and .04 respectively.  This was the trend across all sports looked at in the study.  When only looking at practice, most injuries occurred greater than 1 hour into practice.  When looking at injuries in competition, 53%-66% injuries occur in the second half of games with halves.  In quarter games, 11%-15% occurred in the first quarter, 31%-32% occurred in the second quarter, 30%-35% occurred in the third quarter, and 22%-26% occurred in the fourth quarter.  When combining the quarters into halves, 53-58% of injuries occurred in the second half.  An explanation for these results are that a player gets more fatigued as the game goes on.  Based on the information explained previously, we can justify studying the effects of lower extremity fatigue on neuromuscular control, proprioception, and stability, therefore, potentially decreasing the risk of injury. The research found indicates relationships between fatigue and performance, and balance and injury. However, since there is limited research on the different means of fatigue and their effects on balance, further research is needed in this area. Therefore, the purpose of this study is to determine the difference between high resistance and power circuit training programs regarding fatigue, and performance related measures including balance and agility.EXPERIMENTAL DESIGN AND METHODS This study was a crossover design in which participants were randomly assigned one of two possible interventions the first week and then completed the opposite intervention the following week. The interventions consisted of squats, deadlifts, and calf raises of varying weighs dependent upon each participant’s individual measured maximal strength. Testing was completed prior to intervention to establish each participant’s baseline measures and then again following each intervention. The Institutional Review Board at Maryville University has approved this study. Participant Selection  Participants were recruited from the Maryville University Division II Men’s Lacrosse team. We recruited members of this population based on convenience, their already standardized training protocol, and the fact that there is currently literature on balance and injury on collegiate athletes. Players interested in participating were given a screening questionnaire to acquire information on any previous injuries and/or medications they were taking. Players were excluded from the study if they had any current injury affecting performance, had pre-existing balance impairments, or were taking medications that could alter their performance in the study. All players who volunteered for this study were fully informed of all training and testing procedures in the informed consent they signed. Prior to testing, all participants had completed a physical examination, as is required by Maryville University for athletic involvement. Participants were instructed to maintain their normal practice schedule and diet throughout the duration of this study. Outcome Measures  Outcome measures utilized included single-limb static balance, single-limb dynamic balance, and agility. There were three stations with the same researcher present for baseline and post-intervention measures.  The first station was the NeuroCom Balance Master, which is a system that is used to measure postural sway during static single-limb stance. We performed the test on both lower extremities with eyes open and then again with eyes closes. The system took into account any deviations in the participant’s balance and static control. The NeuroCom has a high test-retest reliability for endpoint excursion, high reliability for movement velocity, and moderate reliability for directional control. The NSBM has also be proven to be a valid measure of balance when assessing healthy individuals.12 The second station was the Y-Balance. Subjects were tested barefoot and instructed to push the distance indicator as far as they could with their foot. They had three attempts in each direction with each foot. The testing order for the direction of the limb was as follows: right foot anterior, left foot anterior, right foot posterolateral, left foot posterolateral, right foot posteromedial, left foot posteromedial. If the subject’s foot touched the top of the distance indicator, if the subject kicked the indicator, or if the subject’s foot touched the floor before returning to the center plate, that trial was discarded. By having a standard procedure order and a more precise measurement device, the YBT has greater precision than the SEBT. The composite ICC of intrarater reliability = 0.91 and the SEM = 5.84 cm.  The composite ICC of interrater reliability = 0.99 and the SEM = 2.08-3.31 cm.13   The third and final station was the T-Test utilizing the Speedlight dual beam photo cell light-gated timing system. The test was conducted by timed forward sprinting, side shuffling, and backwards sprinting. The cones are placed in a “T”. Cone 1 was place a distance of 9.14 m from the starting line. Cone 2 was placed 4.57 m to the right of cone 1. Cone 3 was placed 4.57 m to the left of cone 1. The players sprinted to cone 1, side shuffled to cone 2, side shuffled to cone 3, side shuffled back to cone 1 and then backpedaled towards the starting point.10 In order for the trial to count, the participant had to remain facing the same direction throughout the entirety of the test. The t-test has a high factorial validity, as well as a high ICC (= 0.928) and alpha (= 0.932). Data has shown that the t-test is one of the most reliable tests of agility, especially  when looking at athletic measurements.14 The SpeedLight dual beam photocell light-gate timing system was used to measure the time it took each participant to complete the t-test procedure.The Speedlight system was set up at the beginning of the test and served as the starting and finishing line. The system was triggered when the athlete was past the beam for at least three seconds. Once the system registered the athlete and was set, the participant could begin the test whenever they were ready. After they ran the entire test and back peddled through the beam, the test would conclude. This system was used secondary to the evidence provided, which concluded that electrical timing systems produced more reliable results when compared to hand timing systems (-0.25 ± 0.09 seconds).15 The electronic system used in this study consisted of a dual beam timing system. When comparing false signals from an outstretched arm or leg instead of the torso, the dual beam timing system (5-17 milliseconds) provides decreased frequency and duration of error than the single beam timing systems (12-42 milliseconds).16The Borg Rate of Perceived Exertion Scale is a common measurement tool used to grade the degree of physical stress. Borg et al. found perceived exertion to be a valid indicator of the degree of physical stress by comparing it to multiple physiological variables such as heart rate, blood lactate concentration, and oxygen uptake.17 The standard Borg scale is a 6-20 point scale, however for our study, the subjects used the modified Borg CR-10 scale. The subjects were instructed on how to use the scale prior to each testing session to ensure they provided the most accurate measure of their level of fatigue.  The subjects were also given a handout with a visual description of each level on the scale. The time period between completion of each resistance training and the rating of perceived exertion was kept constant for each subject and training session. It has been confirmed that the Borg ratings of perceived exertion accurately depict increases in blood lactate concentration, muscle lactate concentration and heart rate in subjects subdued to different levels of exercise.18 Data Analysis Conducted using IBM SPSS Statistics for Windows.  All data expressed as Mean +- SD. We will use Shapiro-Wilk test for normality and the Levene test for homogeneity of variances.  Repeated-measures analysis of variance will be used to look at the within and between groups differences. Bonferroni adjustment will be used to adjust for the alpha-inflation.  Cohen’s d will be used to look at the effect sizes.  Statistical significance will be considered for p < 0.05.RESULTSDISCUSSION AND CONCLUSIONSREFERENCES1. Knicker AJ, Renshaw I, Oldham AR, Cairns SP. Interactive Processes Link the Multiple Symptoms of Fatigue in Sport Competition. Sports Medicine. 2011;41(4):307-328.2. Enoka RM, Duchateau J. Muscle fatigue: what, why and how it influences muscle function. The Journal of Physiology. 2008;586(1):11-23.3. Babault N, Desbrosses K, Fabre MS, Michaut A, Pousson M. Neuromuscular fatigue development during maximal concentric and isometric knee extensions. J Appl Physiol. 2006; 100:780-785. Pubmed4. Izquierdo M, Ibañez J, Calbet J, et al. Neuromuscular Fatigue after Resistance Training. International Journal of Sports Medicine. 2009;30(08):614-623.5. Freitas TT, Calleja-González J, Alarcón F, Alcaraz PE. Acute Effects of Two Different Resistance Circuit Training Protocols on Performance and Perceived Exertion in Semiprofessional Basketball Players. Journal of Strength and Conditioning Research. 2016;30(2):407-414. 6. Hosseinimehr SH, Daneshmandi H, Norasteh AA. The Effects of Activity Related Fatigue on Static and Dynamic Postural Control in College Athletes. Brazilian Journal of Biometricity. 2010;4(2):148-155.7. Fatahi M, Ghasemi GHA, Mongashti Joni Y, Zolaktaf V, Fatahi F. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016;6(1):37-50. 8. Gribble PA, Hertel J. Effect of lower-extremity muscle fatigue on postural control. Archives of Physical Medicine & Rehabilitation. 2004; 85(4):589-92.9. Gribble PA, Hertel J, Denegar CR, Buckley WE. The effects of fatigue and chronic ankle instability on dynamic postural control. Journal of Athletic Training. 2004; 39(4)321-9.10. 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