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Lower Limb Biomechanical Analysis of Healthy Participants
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Using bench press load to predict upper body exercise loads in physically active individuals.

Del P Wong1, Kwan-Lung Ngo, Michael A Tse

  • 1Human Performance Laboratory, Department of Health and Physical Education, The Hong Kong Institute of Education , Hong Kong.

Journal of Sports Science & Medicine
|October 24, 2013
PubMed
Summary
This summary is machine-generated.

Predicting upper body assistance exercise loads from the bench press is feasible. The bench press load accurately predicts loads for exercises like hammer curls and shoulder presses, saving time for fitness professionals.

Keywords:
Strength trainingrepetition maximumresistance trainingtraining loadweight

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Area of Science:

  • Sports Science
  • Exercise Physiology
  • Biomechanics

Background:

  • Optimizing training loads is crucial for strength development.
  • Predictive models can enhance training efficiency.
  • The bench press is a foundational upper body exercise.

Purpose of the Study:

  • To determine if upper body assistance exercise loads can be predicted from bench press loads.
  • To develop prediction equations for common assistance exercises.

Main Methods:

  • Twenty-nine collegiate students performed 6-repetition maximum (6RM) tests.
  • Loads for bench press, hammer curl, barbell bicep curl, overhead dumbbell triceps extension, and dumbbell shoulder press were measured.
  • Pearson correlation and linear regression analyses were used to establish relationships.

Main Results:

  • Bench press loads were highly correlated (r=0.80-0.93) with all four assistance exercises.
  • Bench press load significantly predicted assistance exercise loads (R²=0.64-0.86).
  • Prediction equations showed minimal, non-significant differences (6.52%-8.54%) between actual and predicted loads.

Conclusions:

  • The bench press 6RM load is a reliable predictor for upper body assistance exercises.
  • These findings offer a time-efficient method for fitness professionals to prescribe training loads.
  • The established equations can be directly applied in training settings.