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The current study investigates the effect of altering the point of force application (PFA) from the rearfoot towards the fore of the foot on the metabolic energy consumption and the influence of transitioning to this technique over a short or a longer timeframe. The participants were randomly assigned into two experimental and one control group: a short-term intervention group (STI, N =17; two training sessions), a long-term intervention group (LTI, N =10; 14-week gradual transition) and a control group (CG, N =11). Data were collected at two running velocities (2.5 and 3.0 m s -1 ). The cost coefficient (i.e. energy required per unit of vertical ground reaction force; J N -1 ) decreased ( P <0.001) after both interventions due to a more anterior PFA during running (STI: 12%, LTI: 11%), but led to a higher ( P <0.001) rate of force generation (STI: 17%, LTI: 15.2%). Dynamic stability of running showed a significant ( P <0.001) decrease in the STI (2.1%), but no differences ( P =0.673) in the LTI. The rate of metabolic energy consumption increased in the STI ( P =0.038), but remained unchanged in the LTI ( P =0.660). The CG had no changes. These results demonstrate that the cost coefficient was successfully decreased following an alteration in the running technique towards a more anterior PFA. However, the energy consumption remained unchanged because of a simultaneous increase in rate of force generation due to a decreased contact time per step. The increased instability found during the short-term intervention and its neutralization after the long-term intervention indicates a role of motor control errors in the economy of running after acute alterations in habitual running execution., Competing Interests: Competing interestsThe authors declare no competing or financial interests., (© 2018. Published by The Company of Biologists Ltd.)

The need to move over uneven terrain is a daily challenge. In order to face unexpected perturbations due to changes in the morphology of the terrain, the central nervous system must flexibly modify its control strategies. We analysed the local dynamic stability and the modular organisation of muscle activation (muscle synergies) during walking and running on an even- and an uneven-surface treadmill. We hypothesized a reduced stability during uneven-surface locomotion and a reorganisation of the modular control. We found a decreased stability when switching from even- to uneven-surface locomotion (p < 0.001 in walking, p = 0.001 in running). Moreover, we observed a substantial modification of the time-dependent muscle activation patterns (motor primitives) despite a general conservation of the time-independent coefficients (motor modules). The motor primitives were considerably wider in the uneven-surface condition. Specifically, the widening was significant in both the early (+40.5%, p < 0.001) and late swing (+7.7%, p = 0.040) phase in walking and in the weight acceptance (+13.6%, p = 0.006) and propulsion (+6.0%, p = 0.041) phase in running. This widening highlighted an increased motor output's robustness (i.e. ability to cope with errors) when dealing with the unexpected perturbations. Our results confirmed the hypothesis that humans adjust their motor control strategies' timing to deal with unsteady locomotion.

We investigated the influence of three different high-pass (HP) and low-pass (LP) filtering conditions and a Gaussian (GNMF) and inverse-Gaussian (IGNMF) non-negative matrix factorization algorithm on the extraction of muscle synergies from myoelectric signals during human walking and running. To evaluate the effects of signal recording and processing on the outcomes, we analyzed the intraday and interday computation reliability. Results show that the IGNMF achieved a significantly higher reconstruction quality and on average needs one less synergy to sufficiently reconstruct the original signals compared to the GNMF. For both factorizations, the HP with a cut-off frequency of 250[Formula: see text]Hz significantly reduces the number of synergies. We identified the filter configuration of fourth order, HP 50[Formula: see text]Hz and LP 20[Formula: see text]Hz as the most suitable to minimize the combination of fundamental synergies, providing a higher reliability across all filtering conditions even if HP 250[Formula: see text]Hz is excluded. Defining a fundamental synergy as a single-peaked activation pattern, for walking and running we identified five and six fundamental synergies, respectively using both algorithms. The variability in combined synergies produced by different filtering conditions and factorization methods on the same data set suggests caution when attributing a neurophysiological nature to the combined synergies.

Introduction: Barefoot running recently received increased attention, with controversial results regarding its effects on injury risk and performance. Numerous studies examined the kinetic and kinematic changes between the shod and the barefoot condition. Intrinsic parameters such as the local dynamic stability could provide new insight regarding neuromuscular control when immediately transitioning from one running condition to the other. We investigated the local dynamic stability during the change from shod to barefoot running. We further measured biomechanical parameters to examine the mechanisms governing this transition., Methods: Twenty habitually shod, young and healthy participants ran on a pressure plate-equipped treadmill and alternated between shod and barefoot running. We calculated the largest Lyapunov exponents as a measure of errors in the control of the movement. Biomechanical parameters were also collected., Results: Local dynamic stability decreased significantly (d=0.41; 2.1%) during barefoot running indicating worse control over the movement. We measured higher cadence (d=0.35; 2.2%) and total flight time (d=0.58; 19%), lower total contact time (d=0.58; -5%), total vertical displacement (d=0.39; -4%), and vertical impulse (d=1.32; 11%) over the two minutes when running barefoot. The strike index changed significantly (d=1.29; 237%) towards the front of the foot., Conclusions: Immediate transition from shod to the barefoot condition resulted in an increased instability and indicates a worst control over the movement. The increased instability was associated with biomechanical changes (i.e. foot strike patterns) of the participants in the barefoot condition. Possible reasons why this instability arises, might be traced in the stance phase and particularly in the push-off. The decreased stability might affect injury risk and performance., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The foot strike pattern (FSP, description of how the foot touches the ground at impact) is recognized to be a predictor of both performance and injury risk. The objective of the current investigation was to validate an original foot strike pattern assessment technique based on the numerical analysis of foot pressure distribution. We analyzed the strike patterns during running of 145 healthy men and women (85 male, 60 female). The participants ran on a treadmill with integrated pressure plate at three different speeds: preferred (shod and barefoot 2.8 ± 0.4 m/s), faster (shod 3.5 ± 0.6 m/s) and slower (shod 2.3 ± 0.3 m/s). A custom-designed algorithm allowed the automatic footprint recognition and FSP evaluation. Incomplete footprints were simultaneously identified and corrected from the software itself. The widely used technique of analyzing high-speed video recordings was checked for its reliability and has been used to validate the numerical technique. The automatic numerical approach showed a good conformity with the reference video-based technique (ICC = 0.93, p < 0.01). The great improvement in data throughput and the increased completeness of results allow the use of this software as a powerful feedback tool in a simple experimental setup.

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). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]