Several recent investigations have linked running economy to heel length, with shorter heels being associated with less metabolic energy consumption. It has been hypothesized that shorter heels require larger plantar flexor muscle forces, thus increasing tendon energy storage and reducing metabolic cost. The goal of this study was to investigate this possible mechanism for metabolic cost reduction. Fifteen male subjects ran at 16 km⋅h−1 on a treadmill and subsequently on a force-plate instrumented runway. Measurements of oxygen consumption, kinematics, and ground reaction forces were collected. Correlational analyses were performed between oxygen consumption and anthropometric and kinetic variables associated with the ankle and foot. Correlations were also computed between kinetic variables (peak joint moment and peak tendon force) and heel length. Estimated peak Achilles tendon force normalized to body weight was found to be strongly correlated with heel length normalized to body height (r = −.751, p = .003). Neither heel length nor any other measured or calculated variable were correlated with oxygen consumption, however. Subjects with shorter heels experienced larger Achilles tendon forces, but these forces were not associated with reduced metabolic cost. No other anthropometric and kinetic variables considered explained the variance in metabolic cost across individuals.
Herman van Werkhoven and Stephen J. Piazza
Paige E. Rice, Herman van Werkhoven, Edward K. Merritt and Jeffrey M. McBride
Greater levels of bone ultimate fracture load, bone stress–strain index, muscle cross-sectional area, and maximal voluntary isometric plantarflexion (MVIP) strength of the lower leg may be adaptations from chronic exposure to stretch-shortening cycle (SSC) actions. Dancers, a population that habitually performs SSC movements primarily about the ankle joint, may serve as a novel population to gain broader understanding of SSC function. A total of 10 female collegiate dancers and 10 untrained controls underwent peripheral quantitative computed tomography scans of both lower legs and performed MVIPs, countermovement hops, and drop hops at 20, 30, and 40 cm on a custom-made inclined sled. Dancers had greater right and left ultimate fracture load values and significantly (P ≤ .05) greater left leg stress–strain index than controls. Dancers had significantly larger right and left muscle cross-sectional area and MVIP values and hopped significantly higher during all hopping conditions in comparison with controls. Average force–time and power–time curves revealed significantly greater relative force and power measurements during the concentric phase for all hopping conditions in dancers when compared with controls. This investigation provides evidence that dance may be a stimulus for positive muscle and bone adaptations, strength levels, and enhanced SSC capabilities.
Daniel E. Lidstone, Justin A. Stewart, Reed Gurchiek, Alan R. Needle, Herman van Werkhoven and Jeffrey M. McBride
Heavy load carriage has been identified as a main contributing factor to the high incidence of overuse injuries in soldiers. Peak vertical ground reaction force (VGRFMAX) and maximal vertical loading rates (VLRMAX) may increase during heavy prolonged load carriage with the development of muscular fatigue and reduced shock attenuation capabilities. The objectives of the current study were (1) to examine physiological and biomechanical changes that occur during a prolonged heavy load carriage task, and (2) to examine if this task induces neuromuscular fatigue and changes in muscle architecture. Eight inexperienced female participants walked on an instrumented treadmill carrying operational loads for 60 minutes at 5.4 km·h–1. Oxygen consumption (), heart rate, rating of perceived exertion (RPE), trunk lean angle, and ground reaction forces were recorded continuously during task. Maximal force and in-vivo muscle architecture were assessed pre- and posttask. Significant increases were observed for VGRFMAX, VLRMAX, trunk lean angle,
Reed D. Gurchiek, Hasthika S. Rupasinghe Arachchige Don, Lasanthi C. R. Pelawa Watagoda, Ryan S. McGinnis, Herman van Werkhoven, Alan R. Needle, Jeffrey M. McBride and Alan T. Arnholt
Field-based sprint performance assessments rely on metrics derived from a simple model of sprinting dynamics parameterized by 2 constants, v 0 and τ, which indicate a sprinter’s maximal theoretical velocity and the time it takes to approach v 0, respectively. This study aims to automate sprint assessment by estimating v 0 and τ using machine learning and accelerometer data. To this end, photocells recorded 10-m split times of 28 subjects for three 40-m sprints while wearing an accelerometer around the waist. Features extracted from the accelerometer data were used to train a classifier to identify the sprint start and regression models to estimate the sprint model parameters. Estimates of v 0, τ, and 30-m sprint time (t 30) were compared between the proposed method and a photocell method using root mean square error and Bland–Altman analysis. The root mean square error of the sprint start estimate was .22 seconds and ranged from .52 to .93 m/s for v 0, .14 to .17 seconds for τ, and .23 to .34 seconds for t 30. Model-derived sprint performance metrics from most regression models were significantly (P < .01) correlated with t 30. Comparison of the proposed method and a physics-based method suggests pursuit of a combined approach because their strengths appear to complement each other.