Real-time continuous assessment of fatigue from surface electromyography with deep learning for training load regulation in elite cyclists.
- DOI
- 10.1186/s13102-026-02080-2
- Published
- 2026 Sep 16
- Container
- BMC sports science, medicine & rehabilitation
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1186/s13102-026-02080-2,
title = {Real-time continuous assessment of fatigue from surface electromyography with deep learning for training load regulation in elite cyclists.},
author = {Zhai R and Ma G and Qiu J and Gong M and Niu W and Wang L},
year = {2026},
journal = {BMC sports science, medicine \& rehabilitation},
doi = {10.1186/s13102-026-02080-2},
url = {https://doi.org/10.1186/s13102-026-02080-2}
}RIS
TY - JOUR TI - Real-time continuous assessment of fatigue from surface electromyography with deep learning for training load regulation in elite cyclists. AU - Zhai R AU - Ma G AU - Qiu J AU - Gong M AU - Niu W AU - Wang L PY - 2026 JO - BMC sports science, medicine & rehabilitation DO - 10.1186/s13102-026-02080-2 UR - https://doi.org/10.1186/s13102-026-02080-2 ER -
APA
R, Z., G, M., J, Q., M, G., W, N., & L, W. (2026). Real-time continuous assessment of fatigue from surface electromyography with deep learning for training load regulation in elite cyclists.. BMC sports science, medicine & rehabilitation. https://doi.org/10.1186/s13102-026-02080-2
Source records
- pubmed · retrieved 2026-09-25T14:43:29.403Z