Recognition and Scoring Physical Exercises via Temporal and Relative Analysis of Skeleton Nodes Extracted from the Kinect Sensor DOI Creative Commons

Raana Esmaeeli,

Mohammad Javad Valadan Zoej, Alireza Safdarinezhad

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(20), P. 6713 - 6713

Published: Oct. 18, 2024

Human activity recognition is known as the backbone of development interactive systems, such computer games. This process usually performed by either vision-based or depth sensors. So far, various solutions have been developed for this purpose; however, all challenges not completely resolved. In paper, a solution based on pattern has labeling and scoring physical exercises in front Kinect sensor. Extracting features from human skeletal joints then generating relative descriptors among them first step our method. led to quantification meaningful relationships between different parts during exercise performance. method, discriminating each motion are used identify adaptive kernels Constrained Energy Minimization method target detector operator. The results indicated an accuracy 95.9% motions. Scoring motions was second after process, which geometric interpolate numerical quantities extracted descriptor vectors transform into semantic scores. demonstrated coincided with scores derived sports coach 99.5 grade R

Language: Английский

Future Perspectives and Ecosystems DOI
Keisuke Fujii

SpringerBriefs in computer science, Journal Year: 2025, Volume and Issue: unknown, P. 101 - 121

Published: Jan. 1, 2025

Language: Английский

Citations

0
Clustering algorithm-based prediction model for athlete performance grading and injury risks DOI

Yang Yu

Journal of Computational Methods in Sciences and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 25, 2025

For athlete performance evaluation and injury risk prediction—which is increasingly crucial—traditional approaches find difficulty handling complex, multidimensional data. We introduce the PerfoRisk-KDB model to precisely estimate by combining K-means DBSCAN clustering techniques. By these two techniques, idea of this work surpasses constraints a single technique increases accuracy robustness for complex high-dimensional This tests assessment prediction real dataset against conventional models. Based on tests, shows good several criteria application possibilities.

Language: Английский

Citations

0
Big Data and Artificial Intelligence in Sports Analytics DOI
Daniel Rojas‐Valverde

Springer eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 14

Published: Jan. 1, 2025

Language: Английский

Citations

0
Data science in sports analytics: A review of performance optimization and fan engagemen DOI Creative Commons

Ogugua Chimezie,

Samuel Onimisi Dawodu,

Shedrack Onwusinkwue

et al.

World Journal of Advanced Research and Reviews, Journal Year: 2024, Volume and Issue: 21(1), P. 2663 - 2670

Published: Jan. 30, 2024

The intersection of data science and sports analytics has emerged as a powerful catalyst in revolutionizing the landscape performance fan engagement. This review explores multifaceted role optimizing athlete enhancing overall experience for enthusiasts. In realm optimization, become an indispensable tool coaches, analysts, athletes alike. Advanced statistical models, machine learning algorithms, predictive are employed to extract actionable insights from massive datasets encompassing player statistics, biomechanical data, in-game dynamics. These not only aid strategic decision-making but also facilitate personalized training regimens, injury prevention strategies, fine-tuning game tactics. integration wearables sensors further amplifies granularity enabling more comprehensive understanding athlete's physical mental well-being. Beyond confines playing field, significantly reshaped Leveraging big social media analytics, user behavior patterns, organizations can tailor content interactions create immersive fans. Predictive modeling allows anticipation preferences, targeted marketing strategies creation interactive platforms that foster deeper connection between fans their favorite teams. conclusion, symbiotic relationship science, engagement is at forefront innovation industry. As technology continues evolve, cutting-edge data-driven methodologies will undoubtedly redefine way train, compete, captivate audiences worldwide. provides overview current landscape, highlighting transformative impact shaping future sports.

Language: Английский

Citations

3
Recognition and Scoring Physical Exercises via Temporal and Relative Analysis of Skeleton Nodes Extracted from the Kinect Sensor DOI Creative Commons

Raana Esmaeeli,

Mohammad Javad Valadan Zoej, Alireza Safdarinezhad

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(20), P. 6713 - 6713

Published: Oct. 18, 2024

Human activity recognition is known as the backbone of development interactive systems, such computer games. This process usually performed by either vision-based or depth sensors. So far, various solutions have been developed for this purpose; however, all challenges not completely resolved. In paper, a solution based on pattern has labeling and scoring physical exercises in front Kinect sensor. Extracting features from human skeletal joints then generating relative descriptors among them first step our method. led to quantification meaningful relationships between different parts during exercise performance. method, discriminating each motion are used identify adaptive kernels Constrained Energy Minimization method target detector operator. The results indicated an accuracy 95.9% motions. Scoring motions was second after process, which geometric interpolate numerical quantities extracted descriptor vectors transform into semantic scores. demonstrated coincided with scores derived sports coach 99.5 grade R

Language: Английский

Citations

2