To date, there are no reviews on machine learning (ML) for predicting outcomes in trauma.
Consequently, it remains unclear as to how ML-based prediction models compare in the …

This critical review considers the epistemological and historical background of the
theoretical construct of motor learning for a more differentiated understanding. More than …

Running gait patterns have implications for revealing the causes of injuries between higher-
mileage runners and low-mileage runners. However, there is limited research on the …

Abstract Machine learning (ML) techniques such as (deep) artificial neural networks (DNN)
are solving very successfully a plethora of tasks and provide new predictive models for …

Background Finding the best subset of gait features among biomechanical variables is
considered very important because of its ability to identify relevant sports and clinical gait …

Artificial intelligence (AI) is a fascinating new technology that incorporates machine learning
and neural networks to improve existing technology or create new ones. Potential …

Kinetic information during human gait can be estimated with inverse dynamics, which is
based on anthropometric, kinematic, and ground reaction data. While collecting ground …

In this paper, the major assumptions of influential approaches to the structure of variability in
practice conditions are discussed from the perspective of a generalized evolving attractor …

Gait classification has been widely used for children with cerebral palsy (CP) to assist with
clinical decision making and to evaluate different treatment outcomes. The aim of this study …

The aim of this study was to examine whether it is possible to utilize the fluctuations in
human motor behaviour to induce a self-organizing process in the athlete, which takes …