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.

Using wearable technology data to explain recreational running injury: A prospective longitudinal feasibility study.

OBJECTIVES: Investigate 1) if collecting and analysing wristwatch inertial measurement unit (IMU) and global positioning system (GPS) data using a commercially-available training platform was feasible in recreational runners and 2) which variables were associated with subsequent injury. DESIGN: Prospective longitudinal cohort. PARTICIPANTS: Healthy recreational runners. MAIN OUTCOME MEASURES: We set a priori feasibility thresholds for recruitment (maximum six-months), acceptance (minimum 80%), adherence (minimum 70%), and data collection (minimum 80%). Participants completed three patient-reported outcome measures (PROMS) detailing their psychological health, sleep quality, and intrinsic motivation to run. We extracted baseline anthropometric, biomechanical, metabolic, and training load data from their IMU/GPS wristwatch for analysis. Participants completed a weekly injury status surveillance questionnaire over the next 12-weeks. Feasibility outcomes were analysed descriptively and injured versus non-injured group differences with 95% confidence intervals were calculated for PROM/IMU/GPS data. RESULTS: 149 participants consented; 86 participants completed (55 men, 31 women); 21 developed an injury (0.46 injuries/1000km). Feasibility outcomes were satisfied (recruitment = 47 days; acceptance = 133/149 [89%]; adherence = 93/133 [70%]; data collection = 86/93 [92%]). Acute load by calculated effort was associated with subsequent injury (mean difference -562.14, 95% CI -1019.42, -21.53). CONCLUSION: Collecting and analysing wristwatch IMU/GPS data using a commercially-available training platform was feasible in recreational runners.

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.

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.