AI Medical Compendium Journal:
Journal of sports sciences

Showing 21 to 30 of 33 articles

Improving energy expenditure estimates from wearable devices: A machine learning approach.

Journal of sports sciences
A means of quantifying continuous, free-living energy expenditure (EE) would advance the study of bioenergetics. The aim of this study was to apply a non-linear, machine learning algorithm (random forest) to predict minute level EE for a range of act...

Auto detecting deliveries in elite cricket fast bowlers using microsensors and machine learning.

Journal of sports sciences
Cricket fast bowlers are at a high risk of injury occurrence, which has previously been shown to be correlated to bowling workloads. This study aimed to develop and test an algorithm that can automatically, reliably and accurately detect bowling deli...

Identifying playing talent in professional football using artificial neural networks.

Journal of sports sciences
The aim of the current study was to objectively identify position-specific key performance indicators in professional football that predict out-field players league status. The sample consisted of 966 out-field players who completed the full 90 minut...

Profiling movement behaviours in pre-school children: A self-organised map approach.

Journal of sports sciences
Application of machine learning techniques has the potential to yield unseen insights into movement and permits visualisation of complex behaviours and tangible profiles. The aim of this study was to identify profiles of relative motor competence (MC...

A machine learning approach for automatic detection and classification of changes of direction from player tracking data in professional tennis.

Journal of sports sciences
The purpose of this study was to develop an automated method for identifying and classifying change of direction (COD) movements in professional tennis using tracking data. Three sport science and strength and conditioning experts coded match-play fo...

Determining motions with an IMU during level walking and slope and stair walking.

Journal of sports sciences
This study investigated whether using an inertial measurement unit (IMU) can identify different walking conditions, including level walking (LW), descent (DC) and ascent (AC) slope walking as well as downstairs (DS) and upstairs (US) walking. Thirty ...

Predicting centre of mass horizontal speed in low to severe swimming intensities with linear and non-linear models.

Journal of sports sciences
We aimed to compare multilayer perceptron (MLP) neural networks, radial basis function neural networks (RBF) and linear models (LM) accuracy to predict the centre of mass (CM) horizontal speed at low-moderate, heavy and severe swimming intensities us...

A rule induction framework for the determination of representative learning design in skilled performance.

Journal of sports sciences
Representative learning design provides a framework for the extent to which practice simulates key elements of a performance setting. Improving both the measurement and analysis of representative learning design would allow for the refinement of spor...

Cricket fast bowling detection in a training setting using an inertial measurement unit and machine learning.

Journal of sports sciences
Fast bowlers are at a high risk of overuse injuries. There are specific bowling frequency ranges known to have negative or protective effects on fast bowlers. Inertial measurement units (IMUs) can classify movements in sports, however, some commercia...

Machine and deep learning for sport-specific movement recognition: a systematic review of model development and performance.

Journal of sports sciences
Objective assessment of an athlete's performance is of importance in elite sports to facilitate detailed analysis. The implementation of automated detection and recognition of sport-specific movements overcomes the limitations associated with manual ...