Hamstring Glute Complex Range of Motion and Strength Improvement in 92seconds

PRELIMINARY EVALUATION OF A TIME EFFICIENT ALTERNATIVE TO “BREAKDOWN SETS” USING AN ACCOMMODATING RESISTANCE TRAINING DEVICE

Paul C. Di Vico, Ed.D, FACSM, CSCS, and Lee N. Cunningham, D.Sc., FACSM
Health Metrics, Inc., Fountain Hills, AZ,
James Warren, B.S., Team America Health and Fitness, Thousand Oaks, CA
Ryan Hogan, M.S, Scott Rollins B.S., CSCS, Human Hybrid Athletics, Westlake Village, CA.

Hamstring Station 1

Introduction and Rationale
Motor Units (MU) consist of the motor nerve and all innervated muscle fibers connected to said nerve via its branches. MUs are muscle fiber type specific. Type I fibers (T1) predominate in responses to lower intensity tasks (slow-twitch/higher volume/more repetitions). Type II (T2) fibers predominate in response to higher intensity tasks (fast twist/greater resistance/weight). Though there are sub-types of fibers, for simplicity and for the purpose of this analysis we will consider only these two primary categories of muscle fiber types.
Typically, the smaller T1 fibers are recruited before larger T2 fibers. Achieving movement for a specific task requires myriad interactive systems that influence the MU recruitment patterns (e.g., resistance, planes of motion, speed of motion, body position, skill level, conditioning status, progressive fatigue, etc.) and thus determine the relative contribution of the each fiber type to the task. , Classic strength training exercises or functional movement patterns require varying proportions of each fiber type to accomplish a task, series of tasks, or the continuance of a single task. Thus, based on the relationship of work intensity relative to work volume, the relative number of MUs of each type of fiber that are recruited changes since all types of MUs activate in an “all or none” response.
What has research demonstrated? Recent work by Kallio demonstrated there is little question optimal motor unit (MU) activation in submaximal work is typically achieved with concentric (isotonic) contractions, even when compared to eccentric (think plyometrics) and isometric contractions. We know that fewer MUs are activated in response to a specific load with eccentric contractions when compared to concentric contractions. However, when maximal voluntary contractions (MVC) are required (specifically isometric contractions), both motor unit discharge rate (MUDR) and total MU activation isometric contractions occur. In fact, during isometric contractions Fallentine and associates demonstrated that there appears to be something of a rotation of MU recruitment as a way to mitigate fatigue during extended contractions. Further, Clamann and associates extended this concept of rotation to various MUs that have tension specific firing patterns, which are dependent on force requirements that are clearly task specific in nature. The authors went on to note that such tension specific firing patters facilitates fine control of weak movements and rapid production of powerful movements.8
Recently, Westcott considered the basic principles of strength conditioning using breakdown sets (also termed drop sets). Essentially their purpose was to promote fatigue of the major MUs in response to a specific exercise. In an oversimplified example, after a set to failure, rather than rest, one quickly reduces the load (usually by 10%) and continues repetitions in a “breakdown set” (usually half the initial set’s repetitions or until failure is reached). In essence, this approach fatigues the initially recruited MUs followed by the brain calling upon additional MUs that have not yet fatigued to either continue or complete the task.
Westcott explains that the extension of the initial set basically activates MUs that would not have been called upon.9 For this analogy, consider the first bank of MUs recruited as the “task specific prime movers” and those recruited to compensate for the initial fatigue of the primary MUs as “secondary movers.” The whole point is to stimulate and then fatigue more MUs than would be accomplished by a traditional sets/reps/rest approach. It had been acknowledged, however, that while the breakdown set approach is prospectively more efficient, one of the concerns with this type of training is the potential for overreach rather than just overload, which brings forth the prospect of overtraining and performance decrement as a result.9, ,
We theorized that a similar effect might be achieved with an exercise device that would permit the trainer or trainee to control both the fatigue of the primary MUs and the stimulation to fatigue of the secondary MUs using a single exercise that combines isometric contraction with maximal dynamic variable contraction of the associated muscle groups, throughout a given range of motion. The thought was that combining a single maximal isometric contraction with a series of full range of motion variable load isotonic contractions would promote changes in performance measures. In theory the combination of the two modes of contraction would achieve a similar stimulus to fatigue among the primary MUs and optimize recruitment of additional MUs of varying types that might vary across the functional range of motion. Our thought was that the presence of the isometric contraction followed by maximal dynamic contractions optimized to the force output variations across the entire range of motion would result in substantial functional strength gains within a time efficient workout that would also result in a minimal degree of muscle soreness and residual fatigue.

Purpose

The present study represents a preliminary assessment of the impact of a single exercise, a “straight leg – glute-hamstring extension” exercise, on both range of motion and glute-ham strength using a dynamic accommodating resistance exercise as a training stimulus. It was theorized that “pre-fatiguing” the primary MUs through a maximal isometric contraction would lead to activation of secondary MUs and associated functional improvements in strength and range of motion of the involved muscle groups.

Methods

Male (17) and female (7) volunteers were separated into a Control Group (CG)(Male, n=8, Female, n=3; mean age 33.55±15.46 yrs; Ht. 69.30±3.30. in.; Wt. 163.44±30.44 lb.) and Experimental Group (EG)(Male, n=9, Female, n=4; mean age 52.77±12.31 yrs; Ht. 69.23±5.04 in.; Wt. 173.00±30.62 lb.). All participants were active members of a commercial health club and had been training for a minimum of one year. They were divided into the two groups based on their availability to complete the baseline and post training trials as well as their commitment to three-times-a-week completion of the single study exercise in addition to their regular exercise activities. All pre- and post treatment measures for both groups were completed by the same individual to ensure consistency of any measurement error variance. Across the 8-week study period several subjects withdrew from the study due to unanticipated scheduling conflicts. The data analyzed and reported is solely associated with the subjects who met their expectations for exercise and test participation. As a result, 12 subjects remained in the Experimental Group and 8 in the Control Group.
Phase I of the pilot study included baseline measurements and morphologic data collected for all subjects across a 5-day period dictated by the subjects’ availability. Range of motion (ROM) of each leg was assessed using a goniometer as degrees of movement (º). Measurement was assessed from the hip, fully flexed as far as each subject could comfortably raise the each leg from a supine lying position toward the head according to standard protocols. A minimum of two trials for each leg were completed. If the ROM for the two were the same, the measurement was accepted and recorded. If they differed, a third trial was completed and if any two of the three measurements were the same, that value was recorded as the result. If all three were different, the highest two measurements were averaged and recorded. Summary data for ROM, force generated (DSM/strength) and Functional Movement Screen (FMS) score are revealed in Table 1 for the Experimental Group and Table 2 for the Control Group.
Additional measurements associated with the FMS were also taken. The FMS is a muscle balance and integrated movement functional screening tool intended to assist with postural assessments and determination of whole body muscular balance capabilities. It was taken as part of the baseline assessment and was not considered to be substantially related to the single exercise treatment associated with phase one. Results of this measurement are reported and analyzed as part of the overall data collection (see tables).
Strength measurements were assessed for each leg using a digital strength meter (DSM) for glute-hamstring strength. For the DSM assessment, the maximum force exerted from full flexion on extension to return to supine was recorded across a 12-second dynamic contraction (extension) of the leg. Full flexion was determined as the elevation (flexion) of the leg that was consistent with the ROM measurement recorded previously. The two highest values achieved for each leg were averaged to determine DSM strength as revealed in Table 2. Measurements were taken by attaching the DSM to the actual training device in question, the EXER-GENIE® Trainer (X).
While the control subjects were not monitored during the four week treatment period, verification that they had not used the X at all during the study period was made via verbal questioning during retesting. It was also verified that they had maintained their regular exercise program. On the other hand, the treatment group was also asked to complete their regular training program, but modify it to ensure that three times per week they would add the X-based glute-ham exercise (supervised by the study investigators) prior to starting their regular workouts.
The target exercise intervention was a glute-ham extension using the X. This exercise was completed by first placing the subject in a supine position. The leg of the subject was then moved to a hip-flexed position at a self selected maximum angle toward the head. The X was attached using an ankle strap prior to raising the leg. The trainer held the opposite end of the resistance control cord and controlled the following two movements:

  1. The subject was required to extend the leg at the hip in an attempt to return it to the floor. This required a maximal isometric contraction for 10 seconds and the trainer (or when on their own, the subject) restricted the motion by control of the resistance rope termed the “control line.”
  2. After 10 seconds, a 12 second isotonic contraction of the leg was completed. The trainer permitted only enough reduction in resistance to ensure a smooth slow movement with maximum effort on the subject’s part to return the leg to the supine position across 12 seconds. The dynamic contraction was repeated immediately two more times, but without any additional isometric contractions.

After a four-week initial training period, t-tests were applied to assess performance changes for ROM (degrees of movement)(º) for each leg, the average ROM for both legs (Mean) and the ROM summed for both legs (SUM). Similarly, DSM measures for force exerted (lbs.) for each leg was completed. DSM for both legs (Mean) and DSM summed for both legs (SUM) were analyzed in the same way. P-value was set at ≤0.05 for all analyses.
A similar analysis was applied to all subjects who completed baseline (T1) and both post-baseline assessments (at 4 weeks (T-2) and at 8 weeks (T-3)). As revealed in Tables 1 and 2, the assessment ended with EG at n=12 subjects and CG at n=8 subjects.

Results and Discussion:

Only subjects who completed all three trials were included in the analysis. T-Tests of dependent sample means were applied to all data at the p= For the EG across T1 and T2 there were no significant differences in ROM average across both extremities and ROM summed across both extremities. However, both variables demonstrated significant differences (improvement) when T1 was compared to T3 and also when T2 was compared to T3.
Similarly, DSM average and DSM summed across both extremities demonstrated no significant differences between T1 and T2. DSM summed across both legs was not significantly different between T2 and T3. However, all other values across trials T1 and T3 as well as T2 and T3 demonstrated significant improvement (DSM average for both legs and DSM summed for both legs).
As part of this analysis, assessment of the control and experimental groups for performance on Grey Cook’s Functional Movement Screen (FMS) assessment were also completed. There were no changes across trials for the C group. The influence of the single Exergenie-based exercise on the FMS was statistically significant between T2 and T3 for the EG group. However, there is no explanation for an absence of difference between T1 and T3 for this group. The premise of evaluator error must be considered. No significant changes in performance were achieved for either group across any of the other assessments other than T2 to T3. The primary purpose for inclusion of an FMS assessment in the study was to consider its contribution to functional assessments which are to follow using more than one exercise. We wanted to explore the potential confounding effect of the glute-ham exercise on total FMS score as additional X exercises are added to the analytical process.

Summary and Conclusions:

The gluteal-hamstring exercise using the X device as a stand-alone intervention is not influential on total body functional movement, at least as assessed using the FMS. A follow-up study that will include a total body exercise similar to that associated with the movements of a power-clean/push-jerk exercise is planned to further assess this prospective training effect and its influence on FMS outcomes.
It has been suggested that early changes in strength and range of motion are not necessarily associated with morphologic changes to the muscle fibers themselves. Rather, such changes are typically the result of improved neuromotor function (e.g., MU recruitment patterns and neural pathway efficiency). , While applied clinical trials such as this one are typically unable to make use of EMG studies, these results were promising in suggesting that either one or both factors are contributing to the performance improvements demonstrated in this pilot-study.
More importantly, the X-based gluteal-hamstring extension/flexion exercise training across an 8-week period appears to have a significant effect on ROM and Strength of the muscle groups activated.
These effects may be based on central nervous system (CNS) response. Schmidt and associates have suggested that the CNS learns and stores motor programs for use when required. As such, it is possible that differential recruitment patterns for specific movements may indeed be enhances if said recruitment demands have a broader range of “imprints” associated with training based variants. In fact, it may also be that protective as well as performance responses would benefit from such alternative training strategies.
Further analysis applying surface electromyography would be insightful. Changes in muscle morphology over time may add to the basis of the performance changes noted.
The potential contribution of these findings to those concerned with athletic injury risk-management and athletic performance is should not be overlooked. These are due to the theorized alterations in MU recruitment patterns and CNS responses to high demand exercise that were likely indexed by the responses achieved using X-based exercise. Further, the potential application of the X- concept to training programs as an alternate programming strategy relative to “step-down” sets should be explored further.

TABLE 1

Experimental group (N = 12) Data
Test Mean
(degrees) SD
(degrees) t p Sig
ROM avg T1
ROM avg T2 46.4
49.7 12.83
16.76 1.14 0.279 ns
ROM avg T1
ROM avg T3 46.4
58.04 12.83
14.06 3.89 0.0024 *
ROM avg T2
ROM avg T3 49.7
58.04 16.76
14.06 3.28 0.0074 *
ROM sum T1
ROM sum T2 45.88
46.38 13.87
12.41 0.228 0.831 ns
ROM sum T1
ROM sum T3 45.88
57.42 13.87
16.95 2.48 0.03 *
ROM sum T2
ROM sum T3 46.38
57.42 12.41
16.95 3.18 0.009 *
Test Mean
lbs. SD
lbs t p Sig
DSM avg T1
DSM avg T2 46.15
48.15 12.81
14.35 0.829 0.424 ns
DSM avg T1
DSM avg T3 46.15
57.73 12.81
14.97 3.14 0.009 *
DSM avg T2
DSM avg T3 48.15
57.73 14.35
14.97 3.61 0.004 *
DSM sum T1
DSM sum T2 92.29
101.79 25.63
25.72 0.823 0.511 ns
DSM sum T1
DSM sum T3 92.29
115.46 25.63
29.94 3.14 0.04 *
DSM sum T2
DSM sum T3 101.79
115.46 25.72
29.94 1.947 0.49 ns
Task (Total Score) Mean SD t p Sig
FMS avg T1
FMS avg T2 18.33
17.75 2.81
2.76 1.246 0.238 ns
FMS avg T1
FMS avg T3 18.33
19.25
2.81
2.18 1.216 0.249 ns
FMS avg T2
FMS avg T3 17.75
19.25 2.76
2.18 2.32 0.40 *
* Indicates a statically significance difference between tests (p ≤0.05)
ns Indicates the differences between tests are not statistically significant
TABLE 2
Control group (N = 8) Data
Test Mean
(degrees) SD
(degrees) t p Sig
ROM avg T1
ROM avg T2 56.5
50.56 22.45
17.99 -0.86 0.419 ns
ROM avg T1
ROM avg T3 56.5
50.25 22.45
15.44 0.839 0.43 ns
ROM avg T2
ROM avg T3 50.56
50.25 17.99
15.44 -0.837 0.43 ns
ROM sum T1
ROM sum T2 54.94
50.50 20.4
17.35 -0.536 0.609 ns
ROM sum T1
ROM sum T3 54.94
50.63 20.4
14.46 -0.583 0.578 ns
ROM sum T2
ROM sum T3 50.50
50.63 17.35
14.46 0.052 0.0.959 ns
Task Mean
lbs. SD
lbs t p Sig
DSM avg T1
DSM avg T2 55.72
50.53 21.05
17.59 0.497 0.511 ns
DSM avg T1
DSM avg T3 55.72
50.44 21.05
14.57 -0.716 0.497 ns
DSM avg T2
DSM avg T3 50.53
50.44 17.59
14.57 -0.046 0.964 ns
DSM sum T1
DSM sum T2 111.44
101.06 42.10
35.17 -0.692 0.511 ns
DSM sum T1
DSM sum T3 111.44
100.88 42.10
29.14 -0.716 0.497 ns
DSM sum T2
DSM sum T3 101.06
100.88 35.17
29.14 -0.047 0.964 ns
Task (Total Score) Mean SD t p Sig
FMS avg T1
FMS avg T2 18.75
17.50 2.66
3.12 -1.193 0.272 ns
FMS avg T1
FMS avg T3 18.75
19.13
2.70
2.66 1.157 0.285 ns
FMS avg T2
FMS avg T3 17.50
19.13 3.12
2.66 1.688 0.135 ns
* Indicates a statically significance difference between tests (p ≤0.05)
ns Indicates the difference between tests are not statistically significant

References

[1] Baechle, T and R. Earle (editors), Essentials of Strength Training and Conditioning, 3rd edition.  Human Kinetics, Champaign, IL., 2008. p.3.

[1] Henneman, E. Relationship Between Size of Motor Neurons and their Susceptibility to Discharge. Science, 126:1345-1347, 1957.

[1] Komi, P., Nauromuscular Performance:  Factors Influencing Force and Speed Production.  Scandinavian Journal of Sports Science, 1(1):1-15, 1979.

[1] Kawamori, N. and G. Haff.  The Optimal Training Load for the Development of Muscular Power. Journal of Strength Conditioning Research. 18(3): 675-684, 2005.

[1] Kallio, J. et. al., Motor Unit Firing Behaviour [sic] of Soleus Muscle in Isometrics and Dynamic Contractions, PLoS One(2): e53425-53431, 2/2015.

[1] Bigland, B. and O. Lippolf, Motor Unit Activity in the Voluntary Contraction of Human Muscle, Journal of Physiology, 125:  322-335, 1954.

[1] Fallentine, N. et. al., Motor Unit Recruitment During Prolonged Isometric Contractions.  European Journal of Applied Physiology, 67(4):  335-341, 1993.

[1] Clamann, H. et. al., Motor Unit Recruitment and the Gradation of Muscle Force.  Physical Therapy, 73:  830-843, 1993.

[1] Wescott, W., Muscle Fiber/Motor Unit Recruitment.  ACSM Certified News. 26 (1): 3, 8, 2016.

[1] Schoenfeld, B., The Use of Specialized Training Techniques to Maximize Muscle Hypertrophy.  Strength and Conditioning Journal, 33(4): 60-65, 2011.

[1] Willardson, J., et. al., Training to Failure and Beyond in Mainstream Resistance Exercise Programs.  Strength and Conditioning Journal, 32(3), 21-29, 2010.

[1] Cook, Gray (Editor). Functional Movement Systems: Screening, Assessment, Corrective Strategies 1st Edition, On Target Publications, Aptos, CA, 2010.

[1] Moritani, T., and H. deVries. Neural Factors Versus Hypertrophy in the Time Course of Muscle Strength Gain. American Journal of Physiological Medicine, 58, 115-130, 1979.

[1] Sale, D. Influence of Exercise and Training on Motor Unit Activation. Exercise and Sports Science Reviews, 15: 95-151, 1987.

[1] Schmidt, R. and T. Lee, Motor Control and Learning. A Behavioral Emphasis, (4th Ed.), Human Kinetics, Champaign, IL, 2005.

[1] Johansson, H. Neurophysiology of Joints. In: Wright, V. and E. Radin (Eds.) Mechanics of Human Joints:  Physiology, Pathophysiology and Treatment.  Decker, New York, pp. 243-284, 1993.

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