AIMC Topic: Athletes

Clear Filters Showing 1 to 10 of 102 articles

Internet of things enabled deep learning monitoring system for realtime performance metrics and athlete feedback in college sports.

Scientific reports
This study presents an Internet of Things (IoT)-enabled Deep Learning Monitoring (IoT-E-DLM) model for real-time Athletic Performance (AP) tracking and feedback in collegiate sports. The proposed work integrates advanced wearable sensor technologies ...

Fatigue and stamina prediction of athletic person on track using thermal facial biomarkers and optimized machine learning algorithm.

Scientific reports
Athletic person's fatigue and stamina prediction plays a vital role for improving the overall performance in the sports. Identification of the athletic person's facial expression on track and field using image, is still a challenge task. The complex ...

Assessment of Recommendations Provided to Athletes Regarding Sleep Education by GPT-4o and Google Gemini: Comparative Evaluation Study.

JMIR formative research
BACKGROUND: Inadequate sleep is prevalent among athletes, affecting adaptation to training and performance. While education on factors influencing sleep can improve sleep behaviors, large language models (LLMs) may offer a scalable approach to provid...

Evaluation of sports training methods and technical characteristics based on multi-dimensional driving fuzzy intelligent computing.

PloS one
To improve the competitive state of badminton athletes and summarize the technical characteristics of badminton players, this paper introduces multi-dimensional fuzzy removal intelligent computing. Taking 120 badminton students from a sports school a...

Comparison of lower limb kinematic and kinetic estimation during athlete jumping between markerless and marker-based motion capture systems.

Scientific reports
Markerless motion capture (ML) systems, which utilize deep learning algorithms, have significantly expanded the applications of biomechanical analysis. Jump tests are now essential tools for athlete monitoring and injury prevention. However, the vali...

Using the Language of elite athletes to predict their personality and on court transgressions.

Scientific reports
Personality is predictive of many behaviors, but personality questionnaires cannot be readily administered to persons of interest. The language people use to express themselves can often predict personality and so should, in theory, provide a surroga...

Deep learning-based recognition model of football player's technical action behavior using PCA-LBP algorithm.

Scientific reports
Football is a sport that requires sportsmen to have both physical strength and physical features. It must consider the distinctions between individuals and then provide targeted training. Football players can perform better on the field with targeted...

Estimating oxygen uptake in simulated team sports using machine learning models and wearable sensor data: A pilot study.

PloS one
Accurate assessment of training status in team sports is crucial for optimising performance and reducing injury risk. This pilot study investigates the feasibility of using machine learning (ML) models to estimate oxygen uptake (VO2) with wearable se...

Footwork recognition and trajectory tracking in track and field based on image processing.

Scientific reports
In track and field sports, footwork can greatly affect the effect and performance of sports. Accurate footwork can effectively improve the performance of professional athletes, and for ordinary trainers, it can reduce the probability of training inju...

Investigating the increase in the specialized performance of athletes using artificial neural network (ANN) exercises.

Scientific reports
Badminton, a dynamic and fast-paced racket sport, demands a unique combination of physical, technical, and cognitive abilities from its players. This study investigates the impact of a tailored core strength training program on the specialized perfor...