Bilateral and unilateral load-velocity profiling in a machine-based, single-joint, lower body exercise

English version

Autoři: Carlos Balsalobre-Fernández ^aff001; Mario Cardiel-García ^aff002; Sergio L. Jiménez ^aff002
Působiště autorů: Department of Physical Education, Sport and Human Movement, Autonomous Univerisity of Madrid, Madrid, Spain ^aff001; School of Sports Science, European University of Madrid, Madrid, Spain ^aff002
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0222632

Souhrn

Background

To analyze the goodness of fit of the load-velocity relationship in a machine-based, single-joint exercise performed both in a bilateral and unilateral manner, as well as to study its accuracy to estimate one repetition maximum (1-RM).

Methods

Fifteen resistance trained males performed an incremental test in the bilateral and unilateral leg extension exercise up to the 1-RM in two separate occasions. Mean vertical velocity of the weight plates in the leg extension machine was measured for every repetition using a smartphone application (My Lift).

Results

Linear regression analyses showed a high goodness of fit (R² > 0.93) and small standard errors of estimate (SEE < 5%1-RM) both in the bilateral and unilateral leg extension when individual load-velocity regressions for each participant were computed. Unilateral load-velocity relationships showed significant differences in the intercept of the regression line with the Y-axis and the velocity at each percentage of the 1-RM (Cohen’s d > 1.0, p< 0.05). Finally, non-significant differences were observed between actual and estimated 1-RM from the load-velocity relationships (r = 0.88.0–96, Cohen’s d < 0.2, p> 0.05).

Conclusions

This proof of concept highlights that computing load-velocity relationships in a machine-based, single-joint, angular exercise can be appropriately performed by measuring the mean vertical velocity of the weight plates. These results could help strength and conditioning researchers and coaches who wish to analyze load-velocity relationship in other common machine-based exercises.

Klíčová slova:

Biology and life sciences – Physical sciences – Engineering and technology – Research and analysis methods – Mathematics – Anatomy – Medicine and health sciences – Statistics – Mathematical and statistical techniques – Statistical methods – Public and occupational health – Physical activity – Physics – Equipment – Classical mechanics – Musculoskeletal system – Body limbs – Sports science – Sports and exercise medicine – Exercise – Physical fitness – Regression analysis – Linear regression analysis – Legs – Motion – Velocity – Strength training – Knees – Communication equipment – Cell phones

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