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Dive into the research topics where Ethan C. Hill is active.

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Featured researches published by Ethan C. Hill.


Journal of Strength and Conditioning Research | 2016

Neuromuscular Adaptations After 2 and 4 Weeks of 80% Versus 30% 1 Repetition Maximum Resistance Training to Failure.

Nathaniel D.M. Jenkins; Terry J. Housh; Samuel L. Buckner; Haley C. Bergstrom; Kristen C. Cochrane; Ethan C. Hill; Cory M. Smith; Glen O. Johnson; Joel T. Cramer

Abstract Jenkins, NDM, Housh, TJ, Buckner, SL, Bergstrom, HC, Cochrane, KC, Hill, EC, Smith, CM, Schmidt, RJ, Johnson, GO, and Cramer, JT. Neuromuscular adaptations after 2 and 4 weeks of 80% versus 30% 1 repetition maximum resistance training to failure. J Strength Cond Res 30(8): 2174–2185, 2016—The purpose of this study was to investigate the hypertrophic, strength, and neuromuscular adaptations to 2 and 4 weeks of resistance training at 80 vs. 30% 1 repetition maximum (1RM) in untrained men. Fifteen untrained men (mean ± SD; age = 21.7 ± 2.4 years; weight = 84.7 ± 23.5 kg) were randomly assigned to either a high-load (n = 7) or low-load (n = 8) resistance training group and completed forearm flexion resistance training to failure 3 times per week for 4 weeks. Forearm flexor muscle thickness (MT) and echo intensity, maximal voluntary isometric (MVIC) and 1RM strength, and the electromyographic, mechanomyographic (MMG), and percent voluntary activation (%VA) responses at 10–100% of MVIC were determined at baseline, 2, and 4 weeks of training. The MT increased from baseline (2.9 ± 0.1 cm) to week 2 (3.0 ± 0.1 cm) and to week 4 (3.1 ± 0.1 cm) for the 80 and 30% 1RM groups. MVIC increased from week 2 (121.5 ± 19.1 Nm) to week 4 (138.6 ± 22.1 Nm) and 1RM increased from baseline (16.7 ± 1.6 kg) to weeks 2 and 4 (19.2 ± 1.9 and 20.5 ± 1.8 kg) in the 80% 1RM group only. The MMG amplitude at 80 and 90% MVIC decreased from baseline to week 4, and %VA increased at 20 and 30% MVIC for both groups. Resistance training to failure at 80 vs. 30% 1RM elicited similar muscle hypertrophy, but only 80% 1RM increased muscle strength. However, these disparate strength adaptations were difficult to explain with neuromuscular adaptations because they were subtle and similar for the 80 and 30% 1RM groups.


Frontiers in Physiology | 2017

Greater neural adaptations following high- vs. low-load resistance training

Nathaniel D.M. Jenkins; Amelia A. Miramonti; Ethan C. Hill; Cory M. Smith; Kristen C. Cochrane-Snyman; Terry J. Housh; Joel T. Cramer

We examined the neuromuscular adaptations following 3 and 6 weeks of 80 vs. 30% one repetition maximum (1RM) resistance training to failure in the leg extensors. Twenty-six men (age = 23.1 ± 4.7 years) were randomly assigned to a high- (80% 1RM; n = 13) or low-load (30% 1RM; n = 13) resistance training group and completed leg extension resistance training to failure 3 times per week for 6 weeks. Testing was completed at baseline, 3, and 6 weeks of training. During each testing session, ultrasound muscle thickness and echo intensity, 1RM strength, maximal voluntary isometric contraction (MVIC) strength, and contractile properties of the quadriceps femoris were measured. Percent voluntary activation (VA) and electromyographic (EMG) amplitude were measured during MVIC, and during randomly ordered isometric step muscle actions at 10–100% of baseline MVIC. There were similar increases in muscle thickness from Baseline to Week 3 and 6 in the 80 and 30% 1RM groups. However, both 1RM and MVIC strength increased from Baseline to Week 3 and 6 to a greater degree in the 80% than 30% 1RM group. VA during MVIC was also greater in the 80 vs. 30% 1RM group at Week 6, and only training at 80% 1RM elicited a significant increase in EMG amplitude during MVIC. The peak twitch torque to MVIC ratio was also significantly reduced in the 80%, but not 30% 1RM group, at Week 3 and 6. Finally, VA and EMG amplitude were reduced during submaximal torque production as a result of training at 80% 1RM, but not 30% 1RM. Despite eliciting similar hypertrophy, 80% 1RM improved muscle strength more than 30% 1RM, and was accompanied by increases in VA and EMG amplitude during maximal force production. Furthermore, training at 80% 1RM resulted in a decreased neural cost to produce the same relative submaximal torques after training, whereas training at 30% 1RM did not. Therefore, our data suggest that high-load training results in greater neural adaptations that may explain the disparate increases in muscle strength despite similar hypertrophy following high- and low-load training programs.


Journal of Strength and Conditioning Research | 2016

Effects of Velocity on Electromyographic, Mechanomyographic, and Torque Responses to Repeated Eccentric Muscle Actions.

Ethan C. Hill; Terry J. Housh; Clayton L. Camic; Cory M. Smith; Kristen C. Cochrane; Nathaniel D.M. Jenkins; Joel T. Cramer; Glen O. Johnson

Abstract Hill, EC, Housh, TJ, Camic, CL, Smith, CM, Cochrane, KC, Jenkins, NDM, Cramer, JT, Schmidt, RJ, and Johnson, GO. Effects of velocity on electromyographic, mechanomyographic, and torque responses to repeated eccentric muscle actions. J Strength Cond Res 30(6): 1743–1751, 2016—The purposes of this study were to examine the effects of the velocity of repeated eccentric muscle actions on the torque and neuromuscular responses during maximal isometric and eccentric muscle actions. Twelve resistance-trained men performed 30 repeated, maximal, eccentric, isokinetic muscle actions at randomly ordered velocities of 60, 120, or 180°·s−1 on separate days. Maximal voluntary isometric contractions (MVICs) were performed before (pretest) and after (posttest) the repeated eccentric muscle actions on each day. Eccentric isokinetic peak torque (EIPT) values were the averages of the first 3 and last 3 repetitions of the 30 repeated eccentric muscle actions. During the EIPT and MVIC muscle actions, electromyographic (EMG) and mechanomyographic (MMG) amplitude (EMG AMP and MMG AMP) and mean power frequency (EMG MPF and MMG MPF) values were assessed. These results indicated that the repeated eccentric muscle actions had no effects on EIPT, or the EMG AMP, EMG MPF, or MMG MPF values assessed during the EIPT muscle actions, but decreased MMG AMP. The repeated eccentric muscle actions, however, decreased MVIC torque, and also the EMG AMP and MMG MPF values assessed during the MVIC muscle actions, but increased MMG AMP. The results indicated that the velocity of the repeated eccentric muscle actions affected the MVIC torque responses, but not EIPT or any of the neuromuscular parameters. Furthermore, there are differences in the torque and neuromuscular responses for isometric vs. eccentric muscle actions after repeated eccentric muscle actions.


Applied Physiology, Nutrition, and Metabolism | 2015

Electromyographic, mechanomyographic, and metabolic responses during cycle ergometry at a constant rating of perceived exertion.

Kristen C. Cochrane; Terry J. Housh; Nathaniel D.M. Jenkins; Haley C. Bergstrom; Cory M. Smith; Ethan C. Hill; Glen O. Johnson; Joel T. Cramer

Ten subjects performed four 8-min rides (65%-80% peak oxygen consumption) to determine the physical working capacity at the OMNI rating of perceived exertion (RPE) threshold (PWCOMNI). Polynomial regression analyses were used to examine the patterns of responses for surface electromyographic (EMG) amplitude (EMG AMP), EMG mean power frequency (EMG MPF), mechanomyographic (MMG) AMP, and MMG MPF of the vastus lateralis as well as oxygen consumption rate, respiratory exchange ratio (RER), and power output (PO) were examined during a 1-h ride on a cycle ergometer at a constant RPE that corresponded to the PWCOMNI. EMG AMP and MMG MPF tracked the decreases in oxygen consumption rate, RER, and PO, while EMG MPF and MMG AMP tracked RPE. The decreases in EMG AMP and MMG MPF were likely attributable to decreases in motor unit (MU) recruitment and firing rate, while the lack of change in MMG AMP may have resulted from a balance between MU de-recruitment as PO decreased, and an increase in the ability of activated fibers to oscillate. The current findings suggested that during submaximal cycle ergometry at a constant RPE, MU de-recruitment and mechanical changes within the muscle may influence the perception of effort via feedback from group III and IV afferents.


Journal of Strength and Conditioning Research | 2015

Relative Contributions of Strength, Anthropometric, and Body Composition Characteristics to Estimated Propulsive Force in Young Male Swimmers

Kristen C. Cochrane; Terry J. Housh; Cory M. Smith; Ethan C. Hill; Nathaniel D.M. Jenkins; Glen O. Johnson; Dona J. Housh; Joel T. Cramer

Abstract Cochrane, KC, Housh, TJ, Smith, CM, Hill, EC, Jenkins, NDM, Johnson, GO, Housh, DJ, Schmidt, RJ, and Cramer, JT. Relative contributions of strength, anthropometric, and body composition characteristics to estimated propulsive force in young male swimmers. J Strength Cond Res 29(6): 1473–1479, 2015—The purpose of this study was to determine the relative contributions of isokinetic forearm flexion (FLX) and extension (EXT) peak torque (PT) at 180°·s−1, height (HT), percent body fat (%BF), and fat-free mass (FFM) to the prediction of estimated propulsive force (EPF) and which of these variables should be a focus of training in young male swimmers. Thirty young male swimmers (mean age ± SD = 12.4 ± 2.7 years) volunteered for this study. The subjects were members of local swimming clubs who competed in the front crawl. The swimmers were measured for FLX and EXT PT at 180°·s−1, HT, body mass (BM), arm muscle area (AMA), arm circumference, triceps skinfold, %BF, and FFM. Arm muscle area was used to calculate EPF. Zero-order correlations and stepwise multiple regression analyses were used to examine the relationships among variables and the relative contributions of FLX, EXT, HT, %BF, and FFM to the prediction of EPF. Forearm flexion PT at 180°·s−1, EXT, BM, HT, FFM, AMA, and EPF were significantly intercorrelated (r = 0.83–1.00). In addition, 4 variables contributed significantly to the prediction of EPF (standardized regression coefficients = FFM [1.00], FLX [0.92], EXT [−0.62], and HT [−0.35]). Percent body fat did not contribute to any of the stepwise models. These findings suggested that age-related increases in HT and FFM, as well as training for increases in FLX and EXT strength may improve propulsive force and swimming performance in young male swimmers.


Journal of Electromyography and Kinesiology | 2015

Effects of the innervation zone on the time and frequency domain parameters of the surface electromyographic signal

Cory M. Smith; Terry J. Housh; Trent J. Herda; Jorge M. Zuniga; Eric D. Ryan; Clayton L. Camic; Haley C. Bergstrom; Doug B. Smith; Joseph P. Weir; Joel T. Cramer; Ethan C. Hill; Kristen C. Cochrane; Nathaniel D.M. Jenkins; Glen O. Johnson

The purposes of the present study were to examine the effects of electrode placements over, proximal, and distal to the innervation zone (IZ) on electromyographic (EMG) amplitude (RMS) and frequency (MPF) responses during: (1) a maximal voluntary isometric contraction (MVIC), and; (2) a sustained, submaximal isometric muscle action. A linear array was used to record EMG signals from the vastus lateralis over the IZ, 30mm proximal, and 30mm distal to the IZ during an MVIC and a sustained isometric muscle action of the leg extensors at 50% MVIC. During the MVIC, lower EMG RMS (p>0.05) and greater EMG MPF (p<0.05) values were recorded over the IZ compared to away from the IZ, however, no differences in slope coefficients for the EMG RMS and MPF versus time relationships over, proximal, and distal to the IZ occurred. Thus, the results of the present study indicated that during an MVIC, EMG RMS and MPF values recorded over the IZ are not comparable to those away from the IZ. However, the rates of fatigue-induced changes in EMG RMS and MPF during sustained, submaximal isometric muscle actions of the leg extensors were the same regardless of the electrode placement locations relative to the IZ.


Physiological Measurement | 2016

Combining regression and mean comparisons to identify the time course of changes in neuromuscular responses during the process of fatigue

Cory M. Smith; Terry J. Housh; Nathaniel D.M. Jenkins; Ethan C. Hill; Kristen C Cochrane; Amelia A. Miramonti; Glen O. Johnson

The purposes of the present study were to apply a unique method for the identification of the time course of changes in neuromuscular responses and to infer the motor unit activation strategies used to maintain force during a fatiguing, intermittent isometric workbout. Eleven men performed 50, 6 s intermittent isometric muscle actions of the leg extensors, each separated by 2 s of rest at 60% maximal voluntary isometric contraction (MVIC). Electromyographic (EMG) and mechanomyographic (MMG) amplitude (root mean square; RMS) and frequency (mean power frequency; MPF) were obtained from the vastus lateralis (VL) every 5 of the 50 repetitions and normalized as a percent of the initial repetition. Polynomial regression analyses were used to determine the model of best fit for the normalized EMG RMS, EMG MPF, MMG RMS, and MMG MPF versus repetition relationships and one-way repeated measures ANOVAs with post-hoc Student Newman-Keuls were used to identify when these neuromuscular parameters changed from the initial repetition. The findings of the present study indicated two unique phases of neuromuscular responses (repetitions 1-20 and 20-50) during the fatiguing workbout. The time course of changes in these four neuromuscular responses suggested that the after-hyperpolarization theory could not explain the maintenance of force production, but Muscle Wisdom and the Onion Skin Scheme could. The findings of the current study suggested that the time course of changes in neuromuscular responses can provide insight in to the motor unit activation strategies used to maintain force production and allow for a greater understanding of the fatiguing process by identifying the time-points at which these neuromuscular parameters changed.


Journal of Strength and Conditioning Research | 2016

Time Course of Changes in Neuromuscular Parameters During Sustained Isometric Muscle Actions

Cory M. Smith; Terry J. Housh; Trent J. Herda; Jorge M. Zuniga; Clayton L. Camic; Haley C. Bergstrom; Doug B. Smith; Joseph P. Weir; Ethan C. Hill; Kristen C. Cochrane; Nathaniel D.M. Jenkins; Glen O. Johnson

Abstract Smith, CM, Housh, TJ, Herda, TJ, Zuniga, JM, Camic, CL, Bergstrom, HC, Smith, DB, Weir, JP, Hill, EC, Cochrane, KC, Jenkins, NDM, Schmidt, RJ, and Johnson, GO. Time course of changes in neuromuscular parameters during sustained isometric muscle actions. J Strength Cond Res 30(10): 2697–2702, 2016—The objective of the present study was to identify the time course of changes in electromyographic (EMG) and mechanomyographic (MMG) time and frequency domain parameters during a sustained isometric muscle action of the leg extensors at 50% maximal voluntary isometric contraction. The EMG and MMG signals were measured from the vastus lateralis of 11 subjects to identify when motor unit activation strategies changed throughout the sustained isometric muscle action. The EMG amplitude (muscle activation) had a positive linear relationship (p = 0.018, r 2 = 0.77) that began to increase at the initiation of the muscle action and continued until task failure. Electromyographic frequency (motor unit action potential conduction velocity) and MMG frequency (global motor unit firing rate) had negative quadratic relationships (p = 0.002, R 2 = 0.99; p = 0.015, R 2 = 0.94) that began to decrease at 30% of the time to exhaustion. The MMG amplitude (motor unit activation) had a cubic relationship (p = 0.001, R 2 = 0.94) that increased from 10 to 30% of the time to exhaustion, then decreased from 40 to 70% of the time to exhaustion, and then markedly increased from 70% to task failure. The time course of changes in the neuromuscular parameters suggested that motor unit activation strategies changed at approximately 30 and 70% of the time to exhaustion during the sustained isometric muscle action. These findings indicate that the time course of changes in neuromuscular responses provide insight into the strategies used to delay the effects of fatigue and are valuable tools for quantifying changes in the fatiguing process during training programs or supplementation research.


Muscle & Nerve | 2015

Muscle activation of the quadriceps and hamstrings during incremental running

Clayton L. Camic; Attila J. Kovacs; Evan A. Enquist; Trisha A. McLain; Ethan C. Hill

The aim of this study was to determine the patterns of responses for the electromyographic (EMG) amplitude vs. oxygen uptake ( V̇ O2) relationships from muscles of the quadriceps femoris and hamstrings during incremental treadmill running. Methods: Twelve men volunteered to perform an incremental test to exhaustion while EMG signals were recorded from the vastus lateralis, vastus medialis, biceps femoris, and semitendinosus muscles. Polynomial regression analyses were used to determine the best model fit for the EMG amplitude vs. V̇ O2 relationships. Results: There were significant (P < 0.05) increases in EMG amplitude across V̇ O2 for the vastus lateralis (quadratic, R = 0.995), vastus medialis (quadratic, R = 0.997), biceps femoris (cubic, R = 0.999), and semitendinosus (linear, R = 0.992) muscles as well as the hamstrings‐to‐quadriceps ratio (cubic, R = 0.999). Conclusion: These findings indicate that the patterns of responses for muscle activation vs. exercise intensity appear to be unique among muscles of the thigh. Muscle Nerve 52: 1023–1029, 2015


Muscle & Nerve | 2017

Changes in Electromechanical Delay During Fatiguing Dynamic Muscle Actions.

Cory M. Smith; Terry J. Housh; Ethan C. Hill; Glen O. Johnson

The onsets of the electromyographic (EMG) signal, mechanomyographic (MMG) signal, and force production were used to identify voluntary electromechanical delay (EMD) during maximal and submaximal leg extensions.

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Cory M. Smith

University of Nebraska–Lincoln

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Terry J. Housh

University of Nebraska–Lincoln

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Glen O. Johnson

University of Nebraska–Lincoln

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Nathaniel D.M. Jenkins

University of Nebraska–Lincoln

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Kristen C. Cochrane

University of Nebraska–Lincoln

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Joel T. Cramer

University of Nebraska–Lincoln

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Clayton L. Camic

University of Nebraska–Lincoln

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Joshua L. Keller

University of Nebraska–Lincoln

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Amelia A. Miramonti

University of Nebraska–Lincoln

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