Literature DB >> 30528962

Prediction of power output at different running velocities through the two-point method with the Stryd power meter.

Felipe García-Pinillos1, Pedro Á Latorre-Román2, Luis E Roche-Seruendo3, Amador García-Ramos4.   

Abstract

BACKGROUND: The force- and power-velocity (F-V and P-V, respectively) relationships have been extensively studied in recent years. However, its use and application in endurance running events is limited. RESEARCH QUESTION: This study aimed to determine if the P-V relationship in endurance runners fits a linear model when running at submaximal velocities, as well as to examine the feasibility of the "two-point method" for estimating power values at different running velocities.
METHODS: Eighteen endurance runners performed, on a motorized treadmill, an incremental running protocol to exhaustion. Power output was obtained at each stage with the Stryd™ power meter. The P-V relationship was determined from a multiple-point method (10, 12, 14, and 17 km·h-1) as well as from three two-point methods based on proximal (10 and 12 km·h-1), intermediate (10 and 14 km·h-1) and distal (10 and 17 km·h-1) velocities.
RESULTS: The P-V relationship was highly linear ( r = 0.999). The ANOVAs revealed significant, although generally trivial (effect size < 0.20), differences between measured and estimated power values at all the velocities tested. Very high correlations ( r = 0.92) were observed between measured and estimated power values from the 4 methods, while only the multiple-point method ( r2 = 0.091) and two-point method distal ( r2 = 0.092) did not show heteroscedasticity of the error. SIGNIFICANCE: The two-point method based on distant velocities (i.e., 10 and 17 km·h-1) is able to provide power output with the same accuracy than the multiple-point method. Therefore, since the two-point method is quicker and less prone to fatigue, we recommend the assessment of power output under only two distant velocities to obtain an accurate estimation of power under a wide range of submaximal running velocities.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Endurance runners; Linear regression; Power output; Two-Velocity method

Mesh:

Year:  2018        PMID: 30528962     DOI: 10.1016/j.gaitpost.2018.11.037

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  3 in total

1.  Influence of the Shod Condition on Running Power Output: An Analysis in Recreationally Active Endurance Runners.

Authors:  Diego Jaén-Carrillo; Luis E Roche-Seruendo; Alejandro Molina-Molina; Silvia Cardiel-Sánchez; Antonio Cartón-Llorente; Felipe García-Pinillos
Journal:  Sensors (Basel)       Date:  2022-06-26       Impact factor: 3.847

2.  Foot Strike Angle Prediction and Pattern Classification Using LoadsolTM Wearable Sensors: A Comparison of Machine Learning Techniques.

Authors:  Stephanie R Moore; Christina Kranzinger; Julian Fritz; Thomas Stӧggl; Josef Krӧll; Hermann Schwameder
Journal:  Sensors (Basel)       Date:  2020-11-25       Impact factor: 3.576

Review 3.  Mechanical Power in Endurance Running: A Scoping Review on Sensors for Power Output Estimation during Running.

Authors:  Diego Jaén-Carrillo; Luis E Roche-Seruendo; Antonio Cartón-Llorente; Rodrigo Ramírez-Campillo; Felipe García-Pinillos
Journal:  Sensors (Basel)       Date:  2020-11-13       Impact factor: 3.576

  3 in total

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