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Record W2083315777 · doi:10.1519/jsc.0b013e3182a99459

Analysis of Pushing Exercises

2013· article· en· W2083315777 on OpenAlexaff
Stuart M. McGill, Jordan Cannon, Jordan Andersen

Bibliographic record

VenueThe Journal of Strength and Conditioning Research · 2013
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTorsoKinematicsPhysical medicine and rehabilitationTask (project management)MetronomeSuspension (topology)Physical therapyCoachingSimulationComputer scienceMathematicsPsychologyMedicineEngineeringAnatomyPhysics

Abstract

fetched live from OpenAlex

Labile surfaces in the form of suspension straps are increasingly being used as a tool in resistance training programs. Pushing is a common functional activity of daily living and inherently part of a well-rounded training program. This study examined pushing exercises performed on stable surfaces and unstable suspension straps, specifically muscle activation levels and spine loads were quantified together with the influence of employing technique coaching. There were several main questions that this study sought to answer: Which exercises challenged particular muscles? What was the magnitude of the resulting spine load? How did stable and unstable surfaces differ? Did coaching influence the results? Fourteen men were recruited as part of a convenience sample (mean age, 21.1 ± 2.0 years; height, 1.77 ± 0.06 m; mean weight, 74.6 ± 7.8 kg). Data were processed and input to a sophisticated and anatomically detailed 3D model that used muscle activity and body segment kinematics to estimate muscle force-in this way, the model was sensitive to the individuals choice of motor control for each task; muscle forces and linked segment joint loads were used to calculate spine loads. Exercises were performed using stable surfaces for hand/feet contact and repeated where possible with labile suspension straps. Speed of movement was standardized across participants with the use of a metronome for each exercise. There were gradations of muscle activity and spine load characteristics to every task. In general, the instability associated with the labile exercises required greater torso muscle activity than when performed on stable surfaces. Throughout the duration of an exercise, there was a range of compression; the TRX push-up ranged from 1,653 to 2,128.14 N, whereas the standard push-up had a range from 1,233.75 to 1,530.06 N. There was no significant effect of exercise on spine compression (F(4,60) = 0.86, p = 0.495). Interestingly, a standard push-up showed significantly greater shear than TRX angle 1 (p = 0.02), angle 2 (p = 0.01), and angle 3 (p = 0.02). As with any training program for the elite or recreational athlete alike, specific exercises and programs should reflect one's injury history, capabilities, limitations, and training goals. Although none of the exercises examined here breached the NIOSH action limit for compression, those exercises that produced higher loads should be used relative to the individual. Thus, the atlas of muscle activation, compression, and shear forces provided can be used to create an appropriate program. Those individuals not able to tolerate certain loads may refer to the atlas and choose exercises that minimize load and still provide sufficient muscle activation. Conversely, an individual with a resilient back that requires an increased muscular challenge may choose exercises with higher muscle activation and spine load. This helps the individual, trainer, or coach in program design respecting individual differences and training goals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.357
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations68
Published2013
Admission routes1
Has abstractyes

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