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

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
doi: 10.1371/journal.pone.0222632



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).


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).


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).


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


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2019 Číslo 9

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