Use of self-organizing maps to study sex- and speed-dependent changes in running biomechanics

Clustering analysis across different speeds reveals two distinct running techniques with no differences in running economy

Establishing the links between running technique and economy remains elusive due to high inter-individual variability. Clustering runners by technique may enable tailored training recommendations, yet it is unclear if different techniques are equally economical and whether clusters are speed-dependent. This study aimed to identify clusters of runners based on technique and to compare cluster kinematics and running economy. Additionally, we examined the agreement of clustering partitions of the same runners at different speeds. Trunk and lower-body kinematics were captured from 84 trained runners at different speeds on a treadmill. We used Principal Component Analysis for dimensionality reduction and agglomerative hierarchical clustering to identify groups of runners with a similar technique, and we evaluated cluster agreement across speeds. Clustering runners at different speeds independently produced different partitions, suggesting single speed clustering can fail to capture the full speed profile of a runner. The two clusters identified using data from the whole range of speeds showed differences in pelvis tilt and duty factor. In agreement with self-optimisation theories, there were no differences in running economy, and no differences in participants' characteristics between clusters. Considering inter-individual technique variability may enhance the efficacy of training designs as opposed to 'one size fits all' approaches.

Method for Assessing the Motor Coordination of Runners Based on the Analysis of Multichannel EMGs

In this paper, we propose a method to evaluate the motor coordination of runners based on the analysis of amplitude and spatiotemporal dynamics of multichannel electromyography. A new diagnostic index for the coordination of runners was proposed, including the amplitude of electromyography, the spatiotemporal stability coefficient, and the symmetry coefficient of muscle force. The motor coordination of 13 professional runners was studied. Detailed anthropometric information was recorded about the professional runners. It has been found that professional athletes are characterized by the stability of movement repetition (more than 83%) and the high degree of symmetry of muscle efforts of the left and right legs (more than 81%) regardless of the changes in load during running at a speed of 8-12 km/hr. Scientific and technological means can support the scientific training of athletes. The end of the Winter Olympic Games has shown us the powerful power of a series of intelligent scientific equipment, including electro-magnetic gun, in sports training. We also look forward to the continuous innovation of these advanced technologies, which will contribute to the intelligent development of sports scientific research.

A Proposed Framework to Describe Movement Variability within Sporting Tasks: A Scoping Review

Movement variability is defined as the normal variations in motor performance across multiple repetitions of a task. However, the term "movement variability" can mean different things depending on context, and when used by itself does not capture the specifics of what has been investigated. Within sport, complex movements are performed repeatedly under a variety of different constraints (e.g. different situations, presence of defenders, time pressure). Movement variability has implications for sport performance and injury risk management. Given the importance of movement variability, it is important to understand the terms used to measure and describe it. This broad term of "movement variability" does not specify the different types of movement variability that are currently being assessed in the sporting literature. We conducted a scoping review (1) to assess the current terms and definitions used to describe movement variability within sporting tasks and (2) to utilise the results of the review for a proposed framework that distinguishes and defines the different types of movement variability within sporting tasks. To be considered eligible, sources must have assessed a sporting movement or skill and had at least one quantifiable measure of movement variability. A total of 43 peer-reviewed journal article sources were included in the scoping review. A total of 280 terms relating to movement variability terminology were extracted using a data-charting form jointly developed by two reviewers. One source out of 43 (2%) supplied definitions for all types of movement variability discussed. Moreover, 169 of 280 terms (60%) were undefined in the source material. Our proposed theoretical framework explains three types of movement variability: strategic, execution, and outcome. Strategic variability describes the different approaches or methods of movement used to complete a task. Execution variability describes the intentional and unintentional adjustments of the body between repetitions within the same strategy. Outcome variability describes the differences in the result or product of a movement. These types emerged from broader frameworks in motor control and were adapted to fit the movement variability needs in sports literature. By providing specific terms with explicit definitions, our proposed framework can ensure like-to-like comparisons of previous terms used in the literature. The practical goal of this framework is to aid athletes, coaches, and support staff to gain a better understanding of how the different types of movement variability within sporting tasks contribute to performance. The framework may allow training methods to be tailored to optimise the specific aspects of movement variability that contribute to success. This review was retrospectively registered using the Open Science Framework (OSF) Registries ( https://osf.io/q73fd ).

Sex-specific tuning of modular muscle activation patterns for locomotion in young and older adults

There is increasing evidence that including sex as a biological variable is of crucial importance to promote rigorous, repeatable and reproducible science. In spite of this, the body of literature that accounts for the sex of participants in human locomotion studies is small and often produces controversial results. Here, we investigated the modular organization of muscle activation patterns for human locomotion using the concept of muscle synergies with a double purpose: i) uncover possible sex-specific characteristics of motor control and ii) assess whether these are maintained in older age. We recorded electromyographic activities from 13 ipsilateral muscles of the lower limb in young and older adults of both sexes walking (young and old) and running (young) on a treadmill. The data set obtained from the 215 participants was elaborated through non-negative matrix factorization to extract the time-independent (i.e., motor modules) and time-dependent (i.e., motor primitives) coefficients of muscle synergies. We found sparse sex-specific modulations of motor control. Motor modules showed a different contribution of hip extensors, knee extensors and foot dorsiflexors in various synergies. Motor primitives were wider (i.e., lasted longer) in males in the propulsion synergy for walking (but only in young and not in older adults) and in the weight acceptance synergy for running. Moreover, the complexity of motor primitives was similar in younger adults of both sexes, but lower in older females as compared to older males. In essence, our results revealed the existence of small but defined sex-specific differences in the way humans control locomotion and that these are not entirely maintained in older age.

Are there different gait profiles in patients with advanced knee osteoarthritis? A machine learning approach

BACKGROUND

Determine whether knee kinematics features analyzed using machine-learning algorithms can identify different gait profiles in knee OA patients.

METHODS

3D gait kinematic data were recorded from 42 patients (Kellgren-Lawrence stages III and IV) walking barefoot at individual maximal gait speed (0.98 ± 0.34 m/s). Principal component analysis, self-organizing maps, and k-means were applied to the data to identify the most relevant and discriminative knee kinematic features and to identify gait profiles.

FINDINGS

Four different gait profiles were identified and clinically characterized as type 1: gait with the knee in excessive varus and flexion (n = 6, 14%, increased knee adduction and increased maximum and minimum knee flexion, p < 0.01); type 2: gait with knee external rotation, either in varus or valgus (n = 11, 26%, excessive maximum and minimum external rotation, p < 0.001); type 3: gait with a stiff knee (n = 17, 40%, decreased knee flexion range of motion, p < 0.001); and type 4: gait with knee varus 'thrust' and decreased rotation (n = 8, 19%, increased and reduced range of motion in the coronal and transverse plane, respectively, p < 0.05).

INTERPRETATION

In a group of patients with homogeneous Kellgren-Lawrence classification of knee OA, gait kinematics data permitted to identify four different gait profiles. These gait profiles can be a valuable tool for helping surgical decisions and treatment. To allow generalization, further studies should be carried with a larger and heterogeneous population.