"Biofeedback-based return to sport": individualization through objective assessments

Elite athletes are regularly exposed to high and repetitive mechanical stresses and impacts, resulting in high injury rates. The consequences of injury can range from time lost from training and competition to chronic physical and psychological burden, with no guarantee that the athlete will return to preinjury levels of sport activity and performance. Prominent predictors include load management and previous injury, highlighting the importance of the postinjury period for effective return to sport (RTS). Currently, there is conflicting information on how to choose and assess the best reentry strategy. Treating RTS as a continuum, with controlled progression of training load and complexity, seems to provide benefits in this process. Furthermore, objectivity has been identified as a critical factor in improving the effectiveness of RTS. We propose that assessments derived from biomechanical measurements in functional settings can provide the objectivity needed for regular biofeedback cycles. These cycles should aim to identify weaknesses, customize the load, and inform on the status of RTS progress. This approach emphasizes individualization as the primary determinant of RTS and provides a solid foundation for achieving it

The influence of footwear on the modular organization of running

For most of our history, we predominantly ran barefoot or in minimalist shoes. The advent of modern footwear, however, might have introduced alterations in the motor control of running. The present study investigated shod and barefoot running under the perspective of the modular organization of muscle activation, in order to help addressing the neurophysiological factors underlying human locomotion. On a treadmill, 20 young and healthy inexperienced barefoot runners ran shod and barefoot at preferred speed (2.8 ± 0.4 m/s). Fundamental synergies, containing the time-dependent activation coefficients (motor primitives) and the time-invariant muscle weightings (motor modules), were extracted from 24 ipsilateral electromyographic activities using non-negative matrix factorization. In shod running, the average foot strike pattern was a rearfoot strike, while in barefoot running it was a mid-forefoot strike. In both conditions, five fundamental synergies were enough to describe as many gait cycle phases: weight acceptance, propulsion, arm swing, early swing and late swing. We found the motor primitives to be generally shifted earlier in time during the stance-related phases and later in the swing-related ones in barefoot running. The motor primitive describing the propulsion phase was significantly of shorter duration (peculiarity confirmed by the analysis of the spinal motor output). The arm swing primitive, instead, was significantly wider in the barefoot condition. The motor modules demonstrated analogous organization with some significant differences in the propulsion, arm swing and late swing synergies. Other than to the trivial absence of shoes, the differences might be deputed to the lower ankle gear ratio (and the consequent increased system instability) and to the higher recoil capabilities of the longitudinal foot arch during barefoot compared to shod running. © 2017 Santuz, Ekizos, Janshen, Baltzopoulos and Arampatzis

KINEMATIC STRATEGIES TO KEEP AN UNCHANGED MARGIN OF STABILITY DURING TREADMILL RUNNING ON AN EVEN AND UNEVEN SURFACE

Understanding how to control stability when running, particularly when being exposed to uneven terrain, is vital to prevent falls and to get an insight into compensatory strategies while running on uneven terrain. The purpose of this study was to assess surface related differences of the margin of stability, kinematics of hip and knee and upper body acceleration which may affect the control of running stability. Eighteen healthy younger adults ran on an even and an uneven surfaced treadmill for two minutes at fixed speeds of 2.0 m/s (female) and 2.2 m/s (male), respectively. Results showed an unchanged margin of stability in both conditions. Further, lower limb kinematics, step width variability and upper body acceleration increased on the uneven surface meaningfully to keep the extrapolated centre of mass within the base of support

Whole-body vibration training induces hypertrophy of the human patellar tendon

I Brage finner du siste tekst-versjon av artikkelen, og den kan inneholde ubetydelige forskjeller fra forlagets pdf-versjon. Forlagets pdf-versjon finner du på onlinelibrary.wiley.com / In Brage you'll find the final text version of the article, and it may contain insignificant differences from the journal's pdf version. The definitive version is available at onlinelibrary.wiley.comAnimal studies suggest that regular exposure to whole-body vibration (WBV) induces an anabolic response in bone and tendon. However, the effects of this type of intervention on human tendon properties and its influence on the muscle-tendon unit function have never been investigated. The aim of this study was to investigate the effect of WBV training on the patellar tendon mechanical, material and morphological properties, the quadriceps muscle architecture and the knee extension torque–angle relationship. Fifty-five subjects were randomized into either a vibration, an active control, or an inactive control group. The active control subjects performed isometric squats on a vibration platform without vibration. Muscle and tendon properties were measured using ultrasonography and dynamometry. Vibration training induced an increase in proximal (6.3%) and mean (3.8%) tendon cross-sectional area, without any appreciable change in tendon stiffness and modulus or in muscle architectural parameters. Isometric torque at a knee angle of 90° increased in active controls (6.7%) only and the torque–angle relation remained globally unchanged in all groups. The present protocol did not appreciably alter knee extension torque production or the musculo-tendinous parameters underpinning this function. Nonetheless, this study shows for the first time that WBV elicits tendon hypertrophy in humans.Seksjon for fysisk prestasjonsevne / Department of Physical Performanc

Lower complexity of motor primitives ensures robust control of high-speed human locomotion

Walking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we challenged human locomotion by having our participants walk and run at a very broad spectrum of submaximal and maximal speeds. The synergistic activations of lower limb locomotor muscles were obtained through decomposition of electromyographic data via non-negative matrix factorization. We analyzed the duration and complexity (via fractal analysis) over time of motor primitives, the temporal components of muscle synergies. We found that the motor control of high-speed locomotion was so challenging that the neuromotor system was forced to produce wider and less complex muscle activation patterns. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that humans cope with the challenges of high-speed locomotion by adapting the neuromotor dynamics through a set of strategies that allow for efficient creation and control of locomotion.Peer Reviewe

The Maximum Lyapunov Exponent During Walking and Running: Reliability Assessment of Different Marker-Sets

The maximum Lyapunov exponent (MLE) has often been suggested as the prominent measure for evaluation of dynamic stability of locomotion in pathological and healthy population. Although the popularity of the MLE has increased in the last years, there is scarce information on the reliability of the method, especially during running. The purpose of the current study was, thus, to examine the reliability of the MLE during both walking and running. Sixteen participants walked and ran on a treadmill completing two measurement blocks (i.e., two trials per day for three consecutive days per block) separated by 2 months on average. Six different marker-sets on the trunk were analyzed. Intraday, interday and between blocks reliability was assessed using the intraclass correlation coefficient (ICC) and the root mean square difference (RMSD). The MLE was on average significantly higher (p < 0.001) in running (1.836 ± 0.080) compared to walking (1.386 ± 0.207). All marker-sets showed excellent ICCs (>0.90) during walking and mostly good ICCs (>0.75) during running. The RMSD ranged from 0.023 to 0.047 for walking and from 0.018 to 0.050 for running. The reliability was better when comparing MLE values between blocks (ICCs: 0.965–0.991 and 0.768–0.961; RMSD: 0.023–0.034 and 0.018–0.027 for walking and running respectively), and worse when considering trials of the same day (ICCs: 0.946–0.980 and 0.739–0.844; RMSD: 0.042–0.047 and 0.045–0.050 for walking and running respectively). Further, different marker-sets affect the reliability of the MLE in both walking and running. Our findings provide evidence that the assessment of dynamic stability using the MLE is reliable in both walking and running. More trials spread over more than 1 day should be considered in study designs with increased demands of accuracy independent of the locomotion condition

Muscle activation patterns are more constrained and regular in treadmill than in overground human locomotion

The use of motorized treadmills as convenient tools for the study of locomotion has been in vogue for many decades. However, despite the widespread presence of these devices in many scientific and clinical environments, a full consensus on their validity to faithfully substitute free overground locomotion is still missing. Specifically, little information is available on whether and how the neural control of movement is affected when humans walk and run on a treadmill as compared to overground. Here, we made use of linear and non-linear analysis tools to extract information from electromyographic recordings during walking and running overground, and on an instrumented treadmill. We extracted synergistic activation patterns from the muscles of the lower limb via non-negative matrix factorization. We then investigated how the motor modules (or time-invariant muscle weightings) were used in the two locomotion environments. Subsequently, we examined the timing of motor primitives (or time-dependent coefficients of muscle synergies) by calculating their duration, the time of main activation, and their Hurst exponent, a non-linear metric derived from fractal analysis. We found that motor modules were not influenced by the locomotion environment, while motor primitives were overall more regular in treadmill than in overground locomotion, with the main activity of the primitive for propulsion shifted earlier in time. Our results suggest that the spatial and sensory constraints imposed by the treadmill environment might have forced the central nervous system to adopt a different neural control strategy than that used for free overground locomotion, a data-driven indication that treadmills could induce perturbations to the neural control of locomotion

Modular control of human movement during running: An open access data set

The human body is an outstandingly complex machine including around 1000 muscles and joints acting synergistically. Yet, the coordination of the enormous amount of degrees of freedom needed for movement is mastered by our one brain and spinal cord. The idea that some synergistic neural components of movement exist was already suggested at the beginning of the 20th century. Since then, it has been widely accepted that the central nervous system might simplify the production of movement by avoiding the control of each muscle individually. Instead, it might be controlling muscles in common patterns that have been called muscle synergies. Only with the advent of modern computational methods and hardware it has been possible to numerically extract synergies from electromyography (EMG) signals. However, typical experimental setups do not include a big number of individuals, with common sample sizes of 5 to 20 participants. With this study, we make publicly available a set of EMG activities recorded during treadmill running from the right lower limb of 135 healthy and young adults (78 males and 57 females). Moreover, we include in this open access data set the code used to extract synergies from EMG data using non-negative matrix factorization (NMF) and the relative outcomes. Muscle synergies, containing the time-invariant muscle weightings (motor modules) and the time-dependent activation coefficients (motor primitives), were extracted from 13 ipsilateral EMG activities using NMF. Four synergies were enough to describe as many gait cycle phases during running: weight acceptance, propulsion, early swing, and late swing. We foresee many possible applications of our data that we can summarize in three key points. First, it can be a prime source for broadening the representation of human motor control due to the big sample size. Second, it could serve as a benchmark for scientists from multiple disciplines such as musculoskeletal modeling, robotics, clinical neuroscience, sport science, etc. Third, the data set could be used both to train students or to support established scientists in the perfection of current muscle synergies extraction methods. All the data is available at Zenodo (doi: 10.5281/zenodo.1254380). © 2018 Frontiers Media S.A.All right reserved

Runners Employ Different Strategies to Cope With Increased Speeds Based on Their Initial Strike Patterns

In this paper we examined how runners with different initial foot strike pattern (FSP) develop their pattern over increasing speeds. The foot strike index (FSI) of 47 runners [66% initially rearfoot strikers (RFS)] was measured in six speeds (2.5–5.0 ms−1), with the hypotheses that the FSI would increase (i.e., move toward the fore of the foot) in RFS strikers, but remain similar in mid- or forefoot strikers (MFS) runners. The majority of runners (77%) maintained their original FSP by increasing speed. However, we detected a significant (16.8%) decrease in the FSI in the MFS group as a function of running speed, showing changes in the running strategy, despite the absence of a shift from one FSP to another. Further, while both groups showed a decrease in contact times, we found a group by speed interaction (p < 0.001) and specifically that this decrease was lower in the MFS group with increasing running speeds. This could have implications in the metabolic energy consumption for MFS-runners, typically measured at low speeds for the assessment of running economy.Peer Reviewe