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This is a Quantitative Study study.

Energy management methods for real-time monitoring in sports training using wearable sensors

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Energy consumption estimation accuracy reached 92.71%, addressing prior limitations in estimation methods.
Monitoring system with multi-modal wearable sensors effectively tracked exercise, improving energy management outcomes.
Data augmentation using an enhanced generative adversarial network expanded sample size and enhanced model efficacy.
Improved residual neural network reduced computational complexity while estimating motion energy efficiently.

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Observational analysis improved energy management for athletes using wearable sensors, indicating significant accuracy gains.

Haidong Zhou (2025) studied this question.

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