The effects of speed and performance level on race walking kinematics

Journal of Sports Sciences

2016

The aim of this study was to analyse lower limb work patterns in world-class race walkers. Seventeen male and female athletes race walked at competitive pace.Ground reaction forces (1000 Hz) and high-speed videos (100 Hz) were recorded and normalised joint moments, work and power, stride length, stride frequency and speed estimated. The hip flexors and extensors were the main generators of energy (24.5 J (± 6.9) and 40.3 J (± 8.3) respectively), with the ankle plantarflexors (16.3 J (± 4.3)) contributing to the energy generated during late stance. The knee generated little energy but performed considerable negative work during swing (-49.1 J (± 8.7)); the energy absorbed by the knee extensors was associated with smaller changes in velocity during stance (r = .783, P < .001), as was the energy generated by the hip flexors (r = -.689, P = .002). The knee flexors did most negative work (-38.6 J (± 5.8)) and the frequent injuries to the hamstrings are probably due to this considerable negative work. Coaches should note the important contributions of the hip and ankle muscles to energy generation and the need to develop knee flexor strength in reducing the risk of injury.3

Section: Discussionmentioning

confidence: 44%

Analysis of lower limb work-energy patterns in world-class race walkers

Journal of Sports Sciences

2016

“…Similarly, Knicker and Loch (1990) defined straightness as between 175 and 185 • , but these values should not apply to current racewalkers given those studies were conducted under the pre-1995 rule. In terms of the actual angles that occur, the results of a very recent laboratory study showed that the mean knee angle at first contact was 180 • (Hanley et al, 2018), similar to that found in world-class competition (Hanley et al, 2014), in laboratory settings using high-speed cameras (Padulo et al, 2013), and using optoelectronic systems (Pavei and La Torre, 2016), but whether this matches judges' opinions has not been hitherto analyzed. Furthermore, it has not been established whether there are differences in accuracy between IAAF judging Levels, a potentially important factor in deciding the future direction of judge education.…”

Section: Introductionmentioning

confidence: 80%

Assessment of IAAF Racewalk Judges' Ability to Detect Legal and Non-legal Technique

Tucker

Front. Sports Act. Living

2019

IAAF Rule 230.2 states that racewalkers must have no visible (to the human eye) loss of contact with the ground and that their advancing leg must be straightened from first contact with the ground until the "vertical upright position." The aims of this study were first to analyze racewalking judges' accuracy in assessing technique and, second, to measure flight times across a range of speeds to establish when athletes were likely to lose visible contact. Twenty racewalkers were recorded in a laboratory using a panning video camera (50 Hz), a high-speed camera (100 Hz), and three force plates (1,000 Hz). Eighty-three judges of different IAAF Levels (and none) viewed the panned videos online and indicated whether each athlete was racewalking legally. Flight times shorter than 0.033 s were detected by fewer than 12.5% of judges, and thus indicated non-visible loss of contact. Flight times between 0.040 and 0.045 s were usually detected by no more than three out of eight judges. Very long flight times (≥0.060 s) were detected by nearly all judges. The results also showed that what judges generally considered straightened knees (>177 • ) was close to a geometrically straight line. Within this inexact definition, IAAF World Championship-standard Level III judges were most accurate, being more likely to detect anatomically bent knees and less likely to indicate bent knees when they did not occur. For the second part, the men racewalked down a 45-m indoor track at 11, 12, 13, 14, and 15 km/h in a randomized order, whereas the women's trials were at 10, 11, 12, 13, and 14 km/h. Flight times, measured using an OptoJump Next photocell system (1,000 Hz), increased for the men from 0.015 s at 11 km/h to 0.040 s at 14 km/h and 0.044 s at 15 km/h, and for the women from 0.013 s at 10 km/h to 0.041 s at 13 km/h and 0.050 s at 14 km/h. For judging by the human eye, the threshold for avoiding visible loss of contact therefore occurred for most athletes at ∼14 km/h for men and 13 km/h for women.

“…The stance phase is the most important to analyse in race walking because technical legality is assessed between initial contact and midstance only. Race walkers typically adopt a narrow stride width (Hanley & Bissas, 2016;Pavei & La Torre, 2016) that results from hip adduction; the present study has shown that this frontal plane movement of the athletes' lower limbs might have been what caused greater differences between systems at midstance than at initial contact, and shows the importance of using clusters of markers where possible. Regarding other movements, transverse plane movements of the knee are restricted during stance in race walking because of its extended (or hyperextended) position, and although Graci & Salsich (2016) found transverse plane differences between a 3D model that included a greater trochanter marker and one without it, differences were small for knee sagittal plane movements, and the authors concluded that models with or without the greater trochanter could therefore be used interchangeably.…”

Section: Discussionmentioning

confidence: 65%

“…For the most part, two-dimensional (2D) sagittal plane analyses using a single video camera have been conducted in race walking (Hanley & Bissas, 2017;Hoga, Ae, Enomoto, & Fujii, 2003;Padulo et al, 2013;White & Winter, 1985) but three-dimensional (3D) analysis offers the 4 potential to more accurately measure this joint's motion (e.g., during the combination of extension with internal rotation of the tibia). Although Alkjaer, Simonsen, & Dyhre-Poulsen (2001) found that using a 2D model of joint moments was appropriate for human gait analysis because of how similar the results produced were to a 3D model, 3D motion analysis using optoelectronic systems has become more prominent within race walking research (Cazzola, Pavei, & Preatoni, 2016;Donà, Preatoni, Cobelli, Rodano & Harrison 2009;Pavei & La Torre, 2016;Preatoni, Ferrario, Donà, Hamill, & Rodano, 2010). These optoelectronic systems tend to have the advantage that quick, precise and accurate 3D data analysis is possible, but the need for skin marker attachment means visual light systems (usually camcorders) are required if analysing competitive performances instead.…”

Section: Introductionmentioning

confidence: 99%

“…Under laboratory conditions, skin markers can be attached to the participant to aid identification of joint centres and improve digitiser reliability when using visual light systems (Bartlett, Bussey, & Flyger, 2006), and are essential when using optoelectronic systems. Different methodologies have been adopted in gait research to identify body segment movements, including using single or paired markers at joint centres (Cazzola et al, 2016;Pavei & La Torre, 2016) or a combination of single markers and clusters (Sinclair, Richards, Taylor, Edmundson, Brooks, & Hobbs, 2013). Regardless of the motion analysis system used, a potential source of 5 error is the overlying skin movement over bone that occurs to facilitate joint motion.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Differences between motion capture and video analysis systems in calculating knee angles in elite-standard race walking

Tucker

Journal of Sports Sciences

2017

Race walking is an event where the knee must be straightened from first contact with the ground until midstance. The aim of this study was to compare knee angle measurements between 2D videography and 3D optoelectronic systems. Passive retroreflective markers were placed on the right leg of 12 race walkers and 3D marker coordinate data captured (250 Hz), with 2D video data (100 Hz) recorded simultaneously. Knee angle data were first derived based on the markers' coordinates, and separately by using a 3D model that also incorporated thigh and shank clusters; the video data were analysed using both automatic tracking and manual digitising, creating four conditions overall. Differences were calculated between conditions for stance (using root mean square values), and at discrete events. There were few differences between systems, although the 3D model produced larger angles at midstance than using automatic tracking and marker coordinates (by 3 - 6°, P < 0.05). These differences might have occurred because of how the 3D model locates the hip joint, and because of the addition of marker clusters. 2D videography gave similar results to the 3D model when using manual digitising, as it allowed for errors caused by skin movement to be corrected.