What question did this study set out to answer?

To develop an artificial-intelligence-driven personalized instructional system for track and field using computer vision and motion recognition to provide real-time biomechanical feedback.

August 16, 2026Advanced ElectromagneticsOpen Access

Artificial Intelligence-Enabled Physical Education: Design of a Personalized Teaching System for Track and Field Projects Based on Motion Recognition Technology

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To develop an artificial-intelligence-driven personalized instructional system for track and field using computer vision and motion recognition to provide real-time biomechanical feedback.
Extracted and normalized human skeletal key points from high-definition video captures to remove variations in body shape and camera distance.
Constructed a temporal graph convolutional network to model spatial skeletal topology and temporal action evolution across running, jumping, and throwing sub-actions.
Integrated biomechanical metrics and expert rule sets into an evaluation model to diagnose technical movement deviations and output targeted corrections.
The temporal graph convolutional network achieved an average recognition accuracy of 94.2%, a recall of 93.8%, and an F1 score of 93.9%.
Classroom implementation demonstrated increased motor-skill scores, elevated frequency of effective practice, and an overall learning satisfaction score of 4.5/5.

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Implication

Experimental evaluation demonstrates high motion recognition accuracy and improved motor skills in physical education students, suggesting effective automated athletic coaching.

Cite This Study

L. N. Chen (2026) studied this question.

synapsesocial.com/papers/6a817ab4f2fb91fc834aec5a https://doi.org/10.7716/aem.v15i3.3934

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Implication

Experimental evaluation demonstrates high motion recognition accuracy and improved motor skills in physical education students, suggesting effective automated athletic coaching.

Artificial Intelligence-Enabled Physical Education: Design of a Personalized Teaching System for Track and Field Projects Based on Motion Recognition Technology

Key Points

Discussion

Implication

Cite This Study

Artificial Intelligence-Enabled Physical Education: Design of a Personalized Teaching System for Track and Field Projects Based on Motion Recognition Technology

Key Points

Discussion

Implication

Cite This Study

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