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Analysis of Body Behavior Characteristics after Sports Training Based on Convolution Neural Network.

Computational intelligence and neuroscience
The use of artificial intelligence technology to analyze human behavior is one of the key research topics in the world. In order to detect and analyze the characteristics of human body behavior after training, a detection model combined with a convol...

AGTH-Net: Attention-Based Graph Convolution-Guided Third-Order Hourglass Network for Sports Video Classification.

Journal of healthcare engineering
As a hot research topic, sports video classification research has a wide range of applications in switched TV, video on demand, smart TV, and other fields and is closely related to people's lives. Under this background, sports video classification re...

Analysing the predictive capacity and dose-response of wellness in load monitoring.

Journal of sports sciences
This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offerin...

Digital Twin Coaching for Physical Activities: A Survey.

Sensors (Basel, Switzerland)
Digital Twin technology has been rising in popularity thanks to the popularity of machine learning in the last decade. As the life expectancy of people around the world is increasing, so is the focus on physical activity to remain healthy especially ...

The path to international medals: A supervised machine learning approach to explore the impact of coach-led sport-specific and non-specific practice.

PloS one
Research investigating the nature and scope of developmental participation patterns leading to international senior-level success is mainly explorative up to date. One of the criticisms of earlier research was its typical multiple testing for many in...

A Hierarchical Learning Approach for Human Action Recognition.

Sensors (Basel, Switzerland)
In the domain of human action recognition, existing works mainly focus on using RGB, depth, skeleton and infrared data for analysis. While these methods have the benefit of being non-invasive, they can only be used within limited setups, are prone to...

Using Artificial Intelligence for Pattern Recognition in a Sports Context.

Sensors (Basel, Switzerland)
Optimizing athlete's performance is one of the most important and challenging aspects of coaching. Physiological and positional data, often acquired using wearable devices, have been useful to identify patterns, thus leading to a better understanding...

On-field player workload exposure and knee injury risk monitoring via deep learning.

Journal of biomechanics
In sports analytics, an understanding of accurate on-field 3D knee joint moments (KJM) could provide an early warning system for athlete workload exposure and knee injury risk. Traditionally, this analysis has relied on captive laboratory force plate...