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Predicting relative load by peak movement velocity and ratings of perceived exertion in power clean

Predicting relative load by peak movement velocity and ratings of perceived exertion in power clean

Naclerio, Fernando ORCID: 0000-0001-7405-4894 and Larumbe-Zabala, Eneko (2018) Predicting relative load by peak movement velocity and ratings of perceived exertion in power clean. Journal of Human Sport and Exercise, 13 (3). ISSN 1988-5202 (doi:https://doi.org/10.14198/jhse.2018.133.14)

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Abstract

Evaluating an individual’s maximal strength is considered a key factor in prescribing and regulating resistance training programs in athletes. The present study analyzed the suitability of predicting the relative load lifted in the power clean exercise from the peak movement velocity and perceived exertion. In order to determine the full-load velocity and load-perceived exertion relationships, 154 young, resistance-trained male athletes performed a 4- to 6-set progressive test up to the one-repetition maximum. Longitudinal regression models were used to predict the relative load from the peak velocity and the OMNI-RES 0-10 scale, taking sets as the time-related variable. Load associated with peak velocity and with perceived exertion scale values expressed after performing 1 or 2 repetitions, were used to construct two adjusted predictive equations: Relative load = 128.85 – 25.86 × peak velocity; and Relative load = 31.10 + 7.26 × OMNI-RES 0–10 scale value. Although both models provided effective estimates of relative load, the coefficient of determination (R2) of the OMNI-RES perceived exertion scale was larger than when using the peak movement velocity model (88% vs. 46%). These findings highlight the importance of perceived exertion to estimate strength performance in the power clean exercise.

Item Type: Article
Uncontrolled Keywords: OMNI-RES SCALE, One Repetition Maximum (1RM), Loading Intensity, Weightlifting
Subjects: Q Science > QP Physiology
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Centre for Science and Medicine in Sport and Exercise
Faculty of Engineering & Science > Department of Life & Sports Sciences
Last Modified: 16 Jul 2018 10:46
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/20288

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