Literature DB >> 33488407

Predicting Temporal Gait Kinematics: Anthropometric Characteristics and Global Running Pattern Matter.

Aurélien Patoz1,2, Thibault Lussiana3,4, Cyrille Gindre2,3, Laurent Mourot4,5.   

Abstract

Equations predicting stride frequency (SF) and duty factor (DF) solely based on running speed have been proposed. However, for a given speed, kinematics vary depending on the global running pattern (GRP), i.e., the overall individual movement while running, which depends on the vertical oscillation of the head, antero-posterior motion of the elbows, vertical pelvis position at ground contact, antero-posterior foot position at ground contact, and strike pattern. Hence, we first verified the validity of the aforementioned equations while accounting for GRP. Kinematics during three 50-m runs on a track (n = 20) were used with curve fitting and linear mixed effects models. The percentage of explained variance was increased by ≥133% for DF when taking into account GRP. GRP was negatively related to DF (p = 0.004) but not to SF (p = 0.08), invalidating DF equation. Second, we assessed which parameters among anthropometric characteristics, sex, training volume, and GRP could relate to SF and DF in addition to speed, using kinematic data during five 30-s runs on a treadmill (n = 54). SF and DF linearly increased and quadratically decreased with speed (p < 0.001), respectively. However, on an individual level, SF was best described using a second-order polynomial equation. SF and DF showed a non-negligible percentage of variance explained by random effects (≥28%). Age and height were positively and negatively related to SF (p ≤ 0.05), respectively, while GRP was negatively related to DF (p < 0.001), making them key parameters to estimate SF and DF, respectively, in addition to speed.
Copyright © 2021 Patoz, Lussiana, Gindre and Mourot.

Entities:  

Keywords:  biomechanics; duty factor; predictive equation; running; running speed; stride frequency

Year:  2021        PMID: 33488407      PMCID: PMC7820750          DOI: 10.3389/fphys.2020.625557

Source DB:  PubMed          Journal:  Front Physiol        ISSN: 1664-042X            Impact factor:   4.566


  36 in total

1.  Partitioning the energetics of walking and running: swinging the limbs is expensive.

Authors:  Richard L Marsh; David J Ellerby; Jennifer A Carr; Havalee T Henry; Cindy I Buchanan
Journal:  Science       Date:  2004-01-02       Impact factor: 47.728

2.  Aerial and Terrestrial Patterns: A Novel Approach to Analyzing Human Running.

Authors:  C Gindre; T Lussiana; K Hebert-Losier; L Mourot
Journal:  Int J Sports Med       Date:  2015-10-28       Impact factor: 3.118

3.  Computer optimization of a minimal biped model discovers walking and running.

Authors:  Manoj Srinivasan; Andy Ruina
Journal:  Nature       Date:  2005-09-11       Impact factor: 49.962

4.  Defining functional groups based on running kinematics using Self-Organizing Maps and Support Vector Machines.

Authors:  Stefan Hoerzer; Vinzenz von Tscharner; Christian Jacob; Benno M Nigg
Journal:  J Biomech       Date:  2015-03-20       Impact factor: 2.712

5.  Inter-individual differences in stride frequencies during running obtained from wearable data.

Authors:  B T Van Oeveren; C J De Ruiter; M J M Hoozemans; P J Beek; J H Van Dieën
Journal:  J Sports Sci       Date:  2019-05-13       Impact factor: 3.337

6.  Is the Relationship Between Stride Length, Frequency, and Velocity Influenced by Running on a Treadmill or Overground?

Authors:  Joshua Bailey; Tiffany Mata; John A Mercer
Journal:  Int J Exerc Sci       Date:  2017-11-01

7.  Running Technique is an Important Component of Running Economy and Performance.

Authors:  Jonathan P Folland; Sam J Allen; Matthew I Black; Joseph C Handsaker; Stephanie E Forrester
Journal:  Med Sci Sports Exerc       Date:  2017-07       Impact factor: 5.411

8.  Lower limb sagittal gait kinematics can be predicted based on walking speed, gender, age and BMI.

Authors:  Florent Moissenet; Fabien Leboeuf; Stéphane Armand
Journal:  Sci Rep       Date:  2019-07-02       Impact factor: 4.379

9.  Humans Optimize Ground Contact Time and Leg Stiffness to Minimize the Metabolic Cost of Running.

Authors:  Isabel S Moore; Kelly J Ashford; Charlotte Cross; Jack Hope; Holly S R Jones; Molly McCarthy-Ryan
Journal:  Front Sports Act Living       Date:  2019-11-04

Review 10.  Is There an Economical Running Technique? A Review of Modifiable Biomechanical Factors Affecting Running Economy.

Authors:  Isabel S Moore
Journal:  Sports Med       Date:  2016-06       Impact factor: 11.136

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