Literature DB >> 33467511

Estimating Functional Threshold Power in Endurance Running from Shorter Time Trials Using a 6-Axis Inertial Measurement Sensor.

Antonio Cartón-Llorente1, Felipe García-Pinillos2,3, Jorge Royo-Borruel1, Alberto Rubio-Peirotén1, Diego Jaén-Carrillo1, Luis E Roche-Seruendo1.   

Abstract

Wearable technology has allowed for the real-time assessment of mechanical work employed in several sporting activities. Through novel power metrics, Functional Threshold Power have shown a reliable indicator of training intensities. This study aims to determine the relationship between mean power output (MPO) values obtained during three submaximal running time trials (i.e., 10 min, 20 min, and 30 min) and the functional threshold power (FTP). Twenty-two recreationally trained male endurance runners completed four submaximal running time trials of 10, 20, 30, and 60 min, trying to cover the longest possible distance on a motorized treadmill. Absolute MPO (W), normalized MPO (W/kg) and standard deviation (SD) were calculated for each time trial with a power meter device attached to the shoelaces. All simplified FTP trials analyzed (i.e., FTP10, FTP20, and FTP30) showed a significant association with the calculated FTP (p < 0.001) for both MPO and normalized MPO, whereas stronger correlations were found with longer time trials. Individual correction factors (ICF% = FTP60/FTPn) of ~90% for FTP10, ~94% for FTP20, and ~96% for FTP30 were obtained. The present study procures important practical applications for coaches and athletes as it provides a more accurate estimation of FTP in endurance running through less fatiguing, reproducible tests.

Entities:  

Keywords:  aerobic; assessment; performance; physiology; technology; training; wearable

Year:  2021        PMID: 33467511     DOI: 10.3390/s21020582

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  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.  The Relationship between VO2max, Power Management, and Increased Running Speed: Towards Gait Pattern Recognition through Clustering Analysis.

Authors:  Juan Pardo Albiach; Melanie Mir-Jimenez; Vanessa Hueso Moreno; Iván Nácher Moltó; Javier Martínez-Gramage
Journal:  Sensors (Basel)       Date:  2021-04-01       Impact factor: 3.576

Review 3.  Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis.

Authors:  Lauren C Benson; Anu M Räisänen; Christian A Clermont; Reed Ferber
Journal:  Sensors (Basel)       Date:  2022-02-23       Impact factor: 3.576

  3 in total

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