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This is a Quantitative Study study.

October 23, 2025Journal of Computational Methods in Sciences and Engineering

Research on innovative application of virtual reality technology based on digital twinning in simulation and evaluation of track and field training

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LRLongyun RenQinghai University

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Implication

Analysis using neural networks shows improved gesture recognition performance in sports training, highlighting advancements in virtual training systems.

Key Points

Gesture recognition achieved 98% performance using a feedforward neural network with 300 datasets from 5 individuals.
Back-propagation algorithm utilized in training neural networks for static gesture recognition maximized accuracy.
Static gestures tested with recognition rates of 86.38% and 90.45% using different algorithm setups.
These advancements in virtual reality setups may enhance effectiveness in track and field training approaches.

Cite This Study

Longyun Ren (2025) studied this question.

synapsesocial.com/papers/68fa1210f9f8b44535bfce3f https://doi.org/10.1177/14727978251391331

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Implication

Analysis using neural networks shows improved gesture recognition performance in sports training, highlighting advancements in virtual training systems.

Research on innovative application of virtual reality technology based on digital twinning in simulation and evaluation of track and field training

Discussion

Member takes

Implication

Key Points

Cite This Study

Research on innovative application of virtual reality technology based on digital twinning in simulation and evaluation of track and field training

Discussion

Member takes

Implication

Key Points

Cite This Study

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