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Anthropometric, neuromuscular, physiologic and training variables as determinants to laboratory cycling performance. | LitMetric

AI Article Synopsis

Article Abstract

Background: The goal of this study was to verify whether anthropometric, physiological and neuromuscular factors, as well as training characteristics, could predict cycling performance during maximal incremental and time-to-exhaustion tests.

Methods: Twenty cyclists were evaluated: Anthropometric variables, knee extensor muscle activation and architecture, training history, and training volume were assessed. Second ventilatory threshold (VT2), maximal oxygen uptake (VO2MAX), and maximal power output (POMAX) were assessed during the incremental test. Muscle architecture of the vastus lateralis (VL) and rectus femoris (RF) muscles was evaluated bilaterally to calculate the mean thighs' muscle thickness, pennation angle and fascicle length, at rest condition. After that, time-to-exhaustion test at POMAX was performed. Muscle activation of the VL, RF and vastus medialis (VM) was evaluated of both legs.

Results: Cyclists' height (r=0.37), experience time and training volume (r=0.46) were predictors of POMAX (P<0.02), while cadence (r=0.30) was the only predictive variable for the time-to-exhaustion performance (P<0.01).

Conclusions: These results suggest that training characteristics and experience are important when training for incremental cycling conditions, whereas cadence (and its determinant variables) should be looked at during maximal and exhaustive conditions.

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Source
http://dx.doi.org/10.23736/S0022-4707.24.15547-8DOI Listing

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