The effect of attentional cues on mechanical efficiency and movement smoothness in running gait: An interdisciplinary investigation.

The aim was to examine the effect of focus of attention cues on foot angle for retraining movement purposes. Twenty (females: 8) rearfoot-striking recreational runners (mass: 72.5 ± 11.8 kg; height: 1.73 ± 0.09 m; age: 32.9 ± 11.3 years) were randomly assigned to an internal focus (IF) (n = 10) or external focus (EF) (n = 10) verbal cue group. Participants performed 5 × 6 minute blocks of treadmill running (control run, 3 × cued running, retention run) at a self-selected running velocity (9.4 ± 1.1 km∙h-1) during a single laboratory visit. Touchdown foot angle, mechanical efficiency, internal and external work were calculated and, centre of mass (COM) and foot movement smoothness was quantified. Linear-mixed effect models showed an interaction for foot angle (p < 0.001, ηp2 = 0.35) and mechanical efficiency (p < 0.001, ηp2 = 0.40) when comparing the control to the cued running. Only the IF group reduced foot angle and mechanical efficiency during cued running, but not during the retention run. The IF group produced less external work during the 1st cued run than the control run. COM and foot smoothness were unaffected by cueing. Only an IF produced desired technique changes but at the cost of reduced mechanical efficiency. Movement smoothness was unaffected by cue provision. Changes to foot angle can be achieved within 6 minutes of gait retraining.

Movement strategy correspondence across jumping and cutting tasks after anterior cruciate ligament reconstruction.

There are currently a multitude of tests used to assess readiness to return to sport (RTS) following anterior cruciate ligament reconstruction (ACLR). The aim of this study was to establish the extent to which movement strategies transfer between three common assessment tasks to help improve design of athlete testing batteries following ACLR. A cohort of 127 male patients 8-10 months post-ACLR and 45 non-injured controls took part in the study. Three movement tasks were completed (unilateral and bilateral drop jump, and 90° pre-planned cut), while ground reaction forces and three-dimensional kinematics (250 Hz) were recorded. Compared to the bilateral drop jump and cut, the unilateral drop jump had a higher proportion of work done at the ankle (d = 0.29, p < 0.001 and d = -1.87, p < 0.001, respectively), and a lower proportion of work done at the knee during the braking phase of the task (d = 0.447, p < 0.001 and d = 1.56, p < 0.001, respectively). The ACLR group had higher peak hip moments than the non-injured controls, although the proportion of work done at the ankle, knee and hip joints were similar. Movement strategies were moderately and positively related at the ankle (rs  = 0.728, p < 0.001), knee (rs  = 0.638, p < 0.001) and hip (rs  = 0.593, p < 0.001) between the unilateral and bilateral drop jump, but there was no relationship at the ankle (rs  = 0.10, p = 0.104), knee (rs  = 0.106, p = 0.166) and hip (rs  = -0.019, p = 0.808) between the unilateral drop jump and the cut. Clinicians could therefore consider omitting one of the drop jumps from assessment batteries but should include both jumping and cutting tasks.

Angular Velocities and Linear Accelerations Derived from Inertial Measurement Units Can Be Used as Proxy Measures of Knee Variables Associated with ACL Injury.

Given the high rates of both primary and secondary anterior cruciate ligament (ACL) injuries in multidirectional field sports, there is a need to develop easily accessible methods for practitioners to monitor ACL injury risk. Field-based methods to assess knee variables associated with ACL injury are of particular interest to practitioners for monitoring injury risk in applied sports settings. Knee variables or proxy measures derived from wearable inertial measurement units (IMUs) may thus provide a powerful tool for efficient injury risk management. Therefore, the aim of this study was to identify whether there were correlations between laboratory-derived knee variables (knee range of motion (RoM), change in knee moment, and knee stiffness) and metrics derived from IMUs (angular velocities and accelerations) placed on the tibia and thigh, across a range of movements performed in practitioner assessments used to monitor ACL injury risk. Ground reaction forces, three-dimensional kinematics, and triaxial IMU data were recorded from nineteen healthy male participants performing bilateral and unilateral drop jumps, and a 90° cutting task. Spearman's correlations were used to examine the correlations between knee variables and IMU-derived metrics. A significant strong positive correlation was observed between knee RoM and the area under the tibia angular velocity curve in all movements. Significant strong correlations were also observed in the unilateral drop jump between knee RoM, change in knee moment, and knee stiffness, and the area under the tibia acceleration curve (rs = 0.776, rs = -0.712, and rs = -0.765, respectively). A significant moderate correlation was observed between both knee RoM and knee stiffness, and the area under the thigh angular velocity curve (rs = 0.682 and rs = -0.641, respectively). The findings from this study suggest that it may be feasible to use IMU-derived angular velocities and acceleration measurements as proxy measures of knee variables in movements included in practitioner assessments used to monitor ACL injury risk.

Assessments performed on harder surfaces can misrepresent ACL injury risk.

Changes in surface hardness are likely to alter an athlete's movement strategy. Anterior cruciate ligament (ACL) injury risk assessments that are performed on a different surface to that used for training and competition may, therefore, not represent an athlete's on-field movement strategies. The aim of this study was to examine the influence of surface hardness on multidirectional field sport athletes' movement strategies in movements that are commonly used in ACL injury risk assessments (bilateral and unilateral drop jumps, and a cutting manoeuvre). Ground reaction forcesand three-dimensional lower limb kinematics were recorded from 19 healthy, male, multidirectional field sport athletes performing bilateral and unilateral drop jumps, and a 90° cutting task on Mondo track (harder surface) and artificial turf (softer surface). Continuous (statistical parametric mapping) and discrete analyses revealed alterations in vertical and horizontal braking forces and knee and hip moments between surfaces of different hardness in all three movements (p ≤ 0.05, d > 0.5). Injury risk assessments performed on a harder surface (e.g. Mondo track) can misrepresent an athlete's risk of ACL injury compared to the same movements performed on a softer more cushioned surface that is typically used for training and/or matches (e.g. artificial turf).

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

Trained endurance runners appear to fine-tune running mechanics to minimize metabolic cost. Referred to as self-optimization, the support for this concept has primarily been collated from only a few gait (e.g., stride frequency, length) and physiological (e.g., oxygen consumption, heart rate) characteristics. To extend our understanding, the aim of this study was to examine the effect of manipulating ground contact time on the metabolic cost of running in trained endurance runners. Additionally, the relationships between metabolic cost, and leg stiffness and perceived effort were examined. Ten participants completed 5 × 6-min treadmill running conditions. Self-selected ground contact time and step frequency were determined during habitual running, which was followed by ground contact times being increased or decreased in four subsequent conditions whilst maintaining step frequency (2.67 ± 0.15 Hz). The same self-selected running velocity was used across all conditions for each participant (12.7 ± 1.6 km · h-1). Oxygen consumption was used to compute the metabolic cost of running and ratings of perceived exertion (RPE) were recorded for each run. Ground contact time and step frequency were used to estimate leg stiffness. Identifiable minimums and a curvilinear relationship between ground contact time and metabolic cost was found for all runners (r 2 = 0.84). A similar relationship was observed between leg stiffness and metabolic cost (r 2 = 0.83). Most (90%) runners self-selected a ground contact time and leg stiffness that produced metabolic costs within 5% of their mathematical optimal. The majority (n = 6) of self-selected ground contact times were shorter than mathematical optimals, whilst the majority (n = 7) of self-selected leg stiffness' were higher than mathematical optimals. Metabolic cost and RPE were moderately associated (r s = 0.358 p = 0.011), but controlling for condition (habitual/manipulated) weakened this relationship (r s = 0.302, p = 0.035). Both ground contact time and leg stiffness appear to be self-optimized characteristics, as trained runners were operating at or close to their mathematical optimal. The majority of runners favored a self-selected gait that may rely on elastic energy storage and release due to shorter ground contact times and higher leg stiffness's than optimal. Using RPE as a surrogate measure of metabolic cost during manipulated running gait is not recommended.