A Comparison of 3D Methods for Identifying the Stance Phase in Treadmill Running for Both Rearfoot and Forefoot Runners

Abstract

Abstract:We compared six 3D methods, OptoGait, and Myotest Run for the determination of contact time for runners with different foot strike patterns. Twenty male participants were divided into two groups: the heel group, who attack the ground with the heel (n = 12), and the toe group, who attack the ground with the middle/front of the foot (n = 8). They performed trials at speeds of 8 km/h then 16 km/h. To detect foot strike, the use of peak velocity of 3D markers located on the heel, the fifth metatarsal, and the great toe provided the best results for both groups. To detect the toe off, the minimum vertical position of a 3D marker placed in line with the great toe gave the most satisfactory results for both groups. In this way, the values of contact time measured with the 3D methods are consistent.Values measured with OptoGait appear consistent too, while those of the Myotest Run underestimate the contact time for both speeds. 3D analysis provides interesting opportunities for calculation of contact time for both rearfoot and forefoot runners, using specific peak velocities to determine foot strike and marker displacement to determine toe off.

Bilateral asymmetries and sex differences in the kinematics of running gait cycle of a group of Andalusian recreational runners (Asimetrías y diferencias por sexo en la cinemática del ciclo de carrera en un grupo de corredores recreativos andaluces)

“…These differences may be attributed to our testing running speeds. Our participants were not professional runners and at the moment the study was carried out they ran two/three times per week and not much more than 10 km per week, so our testing speeds were lower than those used in most investigations with runners and, as it is well known, the swing phase becomes proportionately longer and the stance phase shorter as the speed increases (Deflandre, et al, 2016;Kharb, et al, 2011;Muñoz, et al, 2018;Nicola & Jewison, 2012;Novacheck, 1998;Rubinstein, et al, 2017;Smith & Hanley, 2013). However, our results are similar to those calculated with the data provided by López-Gómez et al (2020) even if their soccer players run at a higher speed but it may be explained by the different running pattern due to the different running surfaces (Ariza-Viviescas, et al, 2021;López-Gómez, et al, 2020) or by the fact that they were children with a lower height which undoubtedly reduces the stance phase.…”

“…The duration of the stance phase and the float phase varies with speed. As speed increases the stance phase becomes shorter and the swing phase longer (Deflandre, Schwartz, Weerts, Croisier, & Bury, 2016;De Wit, et al, 2000;Kharb, et al, 2011;Muñoz, García, Soto, & Latorre, 2018;Nicola & Jewison, 2012;Novacheck, 1998;Rubinstein, et al, 2017;Smith & Hanley, 2013). Thus, in running, typical swing times contribute between 64 and 78% of the running gait cycle's duration, dependent on speed (Lohman, et al, 2011;Novacheck, 1998;Smith & Hanley, 2013).…”

Reproducibility of the Evolution of Stride Biomechanics During Exhaustive Runs

“…We chose to use 3D analysis as it provides a precise record of the runner’s kinematics ( Deflandre et al, 2016 ) and we needed accurate data on biomechanics of the entire stride. This method of analysis requires the subject to run on a treadmill; however, running reliability should be similar in the field and on a treadmill (Hopkins et al, 2001).…”

“…reduction in stride frequency (Hunter and Smith, 2007), reduction in stance duration ( Degache et al, 2013 ) and increase in knee flexion at impact (Kellis and Liassou, 2009; Mizrahi et al, 2000 )). It has previously been shown that foot location at impact varies considerably between individuals ( Delgado et al, 2013 ; Lieberman et al, 2010 ); for instance, a distinction has been drawn between heel-striking and toe-striking runners ( Deflandre et al, 2016 ; Gruber et al, 2013 ). Our results suggest that the evolution of impact location is also highly individually variable and does not follow the same pattern in each trial (ICC = .04; positive slopes for the first and second trials and a negative slope for the third trial).…”

“…All these tools have their pros and cons; three-dimensional (3D) motion capture is powerful and is extensively used by investigators (although the validity of the data is sometimes questionable due to skin movement artefacts) ( Leardini et al, 2005 ; Reinschmidt et al, 1997 ). It is suited to assess biomechanical patterns of the normal gait ( Deflandre et al, 2016 ; Pietraszewski et al, 2012 ), to investigate abnormal movements that cause injuries ( Bruderer-Hofstetter et al, 2015 ) and to estimate the success of interventions intended to correct gait anomalies ( Ferber et al, 2005 ) or enhance performance ( Snyder et al, 2009 ).…”