Literature DB >> 27806673

Sprint performance and mechanical outputs computed with an iPhone app: Comparison with existing reference methods.

Natalia Romero-Franco1, Pedro Jiménez-Reyes2, Adrián Castaño-Zambudio2, Fernando Capelo-Ramírez2, Juan José Rodríguez-Juan3, Jorge González-Hernández2, Francisco Javier Toscano-Bendala2, Víctor Cuadrado-Peñafiel4, Carlos Balsalobre-Fernández5.   

Abstract

The purpose of this study was to assess validity and reliability of sprint performance outcomes measured with an iPhone application (named: MySprint) and existing field methods (i.e. timing photocells and radar gun). To do this, 12 highly trained male sprinters performed 6 maximal 40-m sprints during a single session which were simultaneously timed using 7 pairs of timing photocells, a radar gun and a newly developed iPhone app based on high-speed video recording. Several split times as well as mechanical outputs computed from the model proposed by Samozino et al. [(2015). A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running. Scandinavian Journal of Medicine & Science in Sports. https://doi.org/10.1111/sms.12490] were then measured by each system, and values were compared for validity and reliability purposes. First, there was an almost perfect correlation between the values of time for each split of the 40-m sprint measured with MySprint and the timing photocells (r = 0.989-0.999, standard error of estimate = 0.007-0.015 s, intraclass correlation coefficient (ICC) = 1.0). Second, almost perfect associations were observed for the maximal theoretical horizontal force (F0), the maximal theoretical velocity (V0), the maximal power (Pmax) and the mechanical effectiveness (DRF - decrease in the ratio of force over acceleration) measured with the app and the radar gun (r = 0.974-0.999, ICC = 0.987-1.00). Finally, when analysing the performance outputs of the six different sprints of each athlete, almost identical levels of reliability were observed as revealed by the coefficient of variation (MySprint: CV = 0.027-0.14%; reference systems: CV = 0.028-0.11%). Results on the present study showed that sprint performance can be evaluated in a valid and reliable way using a novel iPhone app.

Keywords:  Acceleration; biomechanics; technology; testing

Mesh:

Year:  2016        PMID: 27806673     DOI: 10.1080/17461391.2016.1249031

Source DB:  PubMed          Journal:  Eur J Sport Sci        ISSN: 1536-7290            Impact factor:   4.050


  29 in total

Review 1.  Methods of Power-Force-Velocity Profiling During Sprint Running: A Narrative Review.

Authors:  Matt R Cross; Matt Brughelli; Pierre Samozino; Jean-Benoit Morin
Journal:  Sports Med       Date:  2017-07       Impact factor: 11.136

2.  SPRINT PERFORMANCE IN FOOTBALL (SOCCER) PLAYERS WITH AND WITHOUT A PREVIOUS HAMSTRING STRAIN INJURY: AN EXPLORATIVE CROSS-SECTIONAL STUDY.

Authors:  Lasse Ishøi; Kristian Thorborg; Per Hölmich; Kasper Krommes
Journal:  Int J Sports Phys Ther       Date:  2020-12

3.  Effects of the Menstrual Cycle on Jumping, Sprinting and Force-Velocity Profiling in Resistance-Trained Women: A Preliminary Study.

Authors:  Felipe García-Pinillos; Pascual Bujalance-Moreno; Carlos Lago-Fuentes; Santiago A Ruiz-Alias; Irma Domínguez-Azpíroz; Marcos Mecías-Calvo; Rodrigo Ramirez-Campillo
Journal:  Int J Environ Res Public Health       Date:  2021-04-30       Impact factor: 3.390

4.  Level of Agreement, Reliability, and Minimal Detectable Change of the MusclelabTM Laser Speed Device on Force-Velocity-Power Sprint Profiles in Division II Collegiate Athletes.

Authors:  Jamie J Ghigiarelli; Keith J Ferrara; Kevin M Poblete; Carl F Valle; Adam M Gonzalez; Katie M Sell
Journal:  Sports (Basel)       Date:  2022-04-08

5.  Validity and reliability of GPS and LPS for measuring distances covered and sprint mechanical properties in team sports.

Authors:  Matthias W Hoppe; Christian Baumgart; Ted Polglaze; Jürgen Freiwald
Journal:  PLoS One       Date:  2018-02-08       Impact factor: 3.240

6.  Relationship between vertical and horizontal force-velocity-power profiles in various sports and levels of practice.

Authors:  Pedro Jiménez-Reyes; Pierre Samozino; Amador García-Ramos; Víctor Cuadrado-Peñafiel; Matt Brughelli; Jean-Benoît Morin
Journal:  PeerJ       Date:  2018-11-13       Impact factor: 2.984

7.  Effects of including endurance and speed sessions within small-sided soccer games periodization on physical fitness.

Authors:  Daniel Castillo; Javier Raya-González; Hugo Sarmento; Filipe Manuel Clemente; Javier Yanci
Journal:  Biol Sport       Date:  2020-10-22       Impact factor: 2.806

8.  Truncated Estimation of Skating Force-Velocity Profiling When Using High-Speed Video-Based Methods Compared to Radar-Derived Processing.

Authors:  Jerome Perez; Gaël Guilhem; Franck Brocherie
Journal:  Front Bioeng Biotechnol       Date:  2021-06-24

9.  Maximizing Acceleration and Change of Direction in Sport: A Case Series to Illustrate How the Force-Velocity Profile Provides Additional Information to That Derived from Linear Sprint Time.

Authors:  Andrés Baena-Raya; Manuel A Rodríguez-Pérez; Pedro Jiménez-Reyes; Alberto Soriano-Maldonado
Journal:  Int J Environ Res Public Health       Date:  2021-06-07       Impact factor: 3.390

10.  Analysis of Wearable and Smartphone-Based Technologies for the Measurement of Barbell Velocity in Different Resistance Training Exercises.

Authors:  Carlos Balsalobre-Fernández; David Marchante; Eneko Baz-Valle; Iván Alonso-Molero; Sergio L Jiménez; Mario Muñóz-López
Journal:  Front Physiol       Date:  2017-08-28       Impact factor: 4.566

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.