DOI: 10.5061/dryad.p2ngf1vxf
title: Joint angles during early sprint acceleration with wearable resistance among Australian Rules football players

description: Rapid acceleration is an important quality for field-based sport athletes.
 Technical factors contribute to greater acceleration and these can be
 deliberately influenced by coaches through implementation of constraints,
 which afford particular coordinative states or induce variability
 generally. Lightweight wearable resistance is an emerging training tool,
 which can act as a constraint on acceleration. At present, however, the
 effects on whole-body coordination resulting from different WR
 configurations and magnitudes are unknown. To better understand these
 effects, five male Australian Rules football athletes performed a series
 of 20 m sprints with either relatively light or heavy wearable resistance
 applied to the anterior or posterior aspects of the thighs or shanks.
 Whole body coordination during one complete stride in early acceleration
 was examined across eight wearable resistance conditions and compared with
 baseline (unresisted) acceleration coordination using group- and
 individual-level hierarchical cluster analysis. Self-organising maps and a
 joint-level distance matrix were used to further investigate specific
 kinematic changes in conditions where coordination differed most from
 baseline. Across the group, relatively heavy wearable resistance applied
 to the thighs resulted in the greatest difference to whole-body
 coordination compared with baseline acceleration. On average, heavy
 posterior thigh wearable resistance led to altered pelvic position and
 greater hip extension, while heavy anterior thigh wearable resistance led
 to accentuated movement at the shoulders in the transverse and sagittal
 planes. These findings offer a useful starting point for coaches seeking
 to use wearable resistance to promote the emergence of greater hip
 extension or upper body contribution during acceleration. Importantly,
 individuals varied in how they responded to heavy thigh wearable
 resistance, which coaches should be mindful of. The present findings also
 offer more focussed future research directions around the question of
 coordinative changes in response to wearable resistance, which may be
 investigated among larger sample groups.
description: <em><strong>Study
 design </strong></em> Testing was undertaken in the Biomechanics Laboratory at Victoria University, Footscray Park, Melbourne, Australia. Five participants attended the laboratory on 10 occasions in total, comprising one familiarisation session, one baseline testing session, and eight WR testing sessions. Each testing session was separated by at least 1 week. During testing sessions, participants performed four maximal 20 m sprints commencing from a stationary position, interspersed with 3 min rest periods. During WR testing sessions, participants were exposed to one of eight unique WR loading configurations and magnitudes when performing sprints 2-4. The order of exposure to each WR loading configuration and magnitude was randomised. In each sprint, 10 m split and 20 m sprint times were recorded, and whole-body spatiotemporal measures and joint kinematics were captured at the 4 m mark to examine coordination during the early acceleration phase of sprinting. <strong><em>Experimental setup</em></strong> A 20 m section of the Biomechanics Laboratory with Mondo track surface defined the sprint area. Infrared timing gates (Smart Speed, Fusion Sport, Brisbane, Australia) were situated at the 0, 10, and 20 m marks along the sprint area. For each sprint, participants adopted a self-selected 2-point upright starting stance with the front foot 0.9 m behind the starting line. Timing began when the timing gates at the 0 m mark were triggered by the participant commencing their sprint. Motion analysis cameras were arranged around the 4 m mark and the approximate capture volume was 5.0 m long, 2.5 m high, and 3.0 m wide. A 10-camera VICON motion analysis system (T-40 series, Vicon Nexus v2, Oxford, UK) sampling at 250 Hz was used for collection of whole-body spatiotemporal and joint kinematic data. A total of 58 reflective markers with 12.7 mm diameter were attached to body landmarks on the upper arms, trunk, pelvis, thighs, shanks, and feet according to the Plug-In-Gait model (Plug-In-Gait Marker Set, Vicon, Oxford, UK). <em><strong>Wearable resistance</strong></em> Throughout testing, participants wore LilaTM ExogenTM (Sportboleh Sdh Bhd, Kuala Lumpur, Malaysia) compression shorts and calf sleeves. During WR exposure trials, a combination of 50, 100, and 200 g fusiform shaped loads (with Velcro backing) totalling the required loading magnitude were attached to the compression garments. Four loading configurations were investigated – anterior thigh, posterior thigh, anterior shank, and posterior shank – with both “light” and “heavy” loading magnitudes in each, totalling eight WR conditions. “Light” and “heavy” loading magnitudes corresponded to an increase of 3% and 6% in the moment of inertia about the hip throughout an acceleration stride, respectively, in accordance with sagittal plane lower limb motion previously observed during early acceleration. Participant height and weight was used to determine the specific loading magnitudes required at each segment to satisfy these conditions based on Plagenhoef’s estimations of segment parameters. Table 1 provides an example of the loading magnitudes per leg for a 180 cm, 70 kg male. Fusiform loads were added in an alternating fashion between a proximal-dominant and distal-dominant orientation. The smallest number of possible loads to achieve the required loading magnitude was used. Table 1. Example loading magnitudes for a 180 cm, 70 kg male participant.   Magnitude Configuration Light (g per leg) Heavy (g per leg) Anterior thigh 550 1100 Posterior thigh 550 1100 Anterior shank 250 500 Posterior shank 250 500   <em><strong>Data collection</strong></em> Following the application of compression garments and attachment of reflective markers, participants undertook an initial warm-up, which consisted of a series of dynamic mobility drills followed by four sub-maximal 20 m sprints. The 15-grade Borg rating of perceived exertion (RPE) scale was explained to participants, and instruction was given to perform the four warm-up sprints corresponding to “fairly light”, “somewhat hard”, “hard”, and “very hard” levels of exertion, respectively. Participants then performed four maximal 20 m sprints, each separated by 3 minutes rest. The only instruction provided to participants was to sprint as fast as possible. In WR testing sessions, researchers applied the requisite WR loads to the participant during the rest period between the first and second sprint, and the WR was left on for the remaining three sprints. <strong><em>Data processing</em></strong> Raw marker data were labelled in Vicon Nexus with spline filling used in instances of marker drop out (up to a maximum of 10 frames). Whole body spatiotemporal measures and joint kinematics were then obtained from Visual 3D software (C-motion, Rockville, MD, USA). First, a global reference system was defined with the positive Y-axis horizontal in the direction of the sprint, the positive X-axis perpendicular to the Y-axis – horizontal in the right direction, and the positive Z-axis in the vertical direction. Marker trajectories were smoothed via a fourth order low-pass Butterworth filter with 10 Hz cut-off frequency, based on mean results of residual analyses. A 10-segment model (upper arms, trunk, pelvis, thighs, shanks, and feet) was then constructed for each participant. Each sprint was trimmed to one complete stride cycle, which was defined as the period between two consecutive toe-off events on the same limb. Toe-off was defined by the initial rise in vertical displacement of the toe marker proceeding its lowest point at the end of the stance phase. Without explicit instruction, all participants chose to commence sprints with the left foot forward. Analysis was therefore able to be carried out on the stride defined by left foot toe-off to left foot toe-off corresponding to steps 3 and 4 of the sprint effort. This stride was taken as representative of the first phase of acceleration identified by Nagahara et al., (2014), who reported, on average, a definitive breakpoint in acceleration kinematics beyond step 4. Of the 180 captured sprints, only three were unable to be successfully reconstructed according to the above process and these were excluded from analysis. In all instances, sprints 2-4 from each testing session were used when comparing effects between conditions, unless otherwise stated. For whole-body spatiotemporal measures; centre of mass (COM) velocity was taken as the average COM velocity in the Y-axis across the stride. Flight time was defined as the point of take-off from one foot to the point of ground contact on the contralateral foot. Ground contact time was defined as the point of initial ground contact until the point of take-off on the same foot. Step length was defined as the horizontal distance between successive toe-off events of each contralateral foot. Flight time, ground contact time, and step length were all calculated as an average across the two steps composing the stride cycle. Step frequency was defined as the number of steps taken per second and was calculated as the inverse of stride duration multiplied by two. For joint kinematics, sagittal, frontal, and transverse plane angles were computed from the transformation between two adjacent segments’ local coordinate systems described by an XYZ Cardan sequence of rotations. The following joints/segments were included: pelvis, thorax, right and left side hips, knees, ankles, and shoulders. In all cases, proximal segments were used as reference segments, except for the pelvis in which angles were defined in relation to the global reference frame. A total of 30 kinematic variables therefore contributed to defining whole body coordination profiles. All angles were normalised to 101 data points (0-100% of the stride cycle) prior to further analysis.
description: # Joint angles during early sprint acceleration with wearable resistance
 among Australian Rules football players
 [https://doi.org/10.5061/dryad.p2ngf1vxf](https://doi.org/10.5061/dryad.p2ngf1vxf) 1) Spatiotemporal data for five Australian Rules football players during steps 3 and 4 of a 20 m maximal sprint. Experimental conditions are baseline (no added resistance) and the following wearable resistance configurations: Heavy posterior thigh, heavy anterior thigh, light posterior thigh, light anterior thigh, heavy posterior shank, heavy anterior shank, light posterior shank, light anterior shank. 2) Whole body joint kinematic data for five Australian Rules football players during steps 3 and 4 of a 20 m maximal sprint under all experimental conditions. ## Description of the data and file structure Participants are designated by P1-P5. 10 m and 20 m splits were obtained from infrared timing gates. For each sprint, participants adopted a self-selected 2-point upright starting stance with the front foot 0.9 m behind the starting line. Timing began when the timing gates at the 0 m mark were triggered by the participant commencing their sprint. Centre of mass (COM) velocity was taken as the average COM velocity in the Y-axis (forward direction) across the stride. Flight time was defined as the point of take-off from one foot to the point of ground contact on the contralateral foot. Ground contact time was defined as the point of initial ground contact until the point of take-off on the same foot. Step length was defined as the horizontal distance between successive toe-off events of each contralateral foot. Flight time, ground contact time, and step length were all calculated as an average across the two steps composing the stride cycle. Step frequency was defined as the number of steps taken per second and was calculated as the inverse of stride duration multiplied by two. For joint kinematic data, raw marker data were labelled in Vicon Nexus with spline filling used in instances of marker drop out (up to a maximum of 10 frames). Joint kinematics were then obtained from Visual 3D software (C-motion, Rockville, MD, USA). First, a global reference system was defined with the positive Y-axis horizontal in the direction of the sprint, the positive X-axis perpendicular to the Y-axis – horizontal in the right direction, and the positive Z-axis in the vertical direction. Marker trajectories were smoothed via a fourth order low-pass Butterworth filter with 10 Hz cut-off frequency, based on mean results of residual analyses. A 10-segment model (upper arms, trunk, pelvis, thighs, shanks, and feet) was then constructed for each participant. Each sprint was trimmed to one complete stride cycle, which was defined as the period between two consecutive toe-off events on the same limb. Of the 180 captured sprints, only three were unable to be successfully reconstructed according to the above process. Sagittal (X), frontal (Y), and transverse (Z) plane angles were computed from the transformation between two adjacent segments’ local coordinate systems described by an XYZ Cardan sequence of rotations. The following joints/segments were included: pelvis, thorax, right and left side hips, knees, ankles, and shoulders. In all cases, proximal segments were used as reference segments, except for the pelvis in which angles were defined in relation to the global reference frame. A total of 30 kinematic variables therefore contributed to defining whole body coordination profiles. All angles were normalised to 101 data points (0-100% of the stride cycle). Missing data denoted by NA. ## Code/Software R code for analysis of data is provided at https://github.com/ktrounson/WR-acceleration