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AI and AI-assisted tools statement
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Financial support and sponsorship
This work was supported by the grants from the National Natural Science Foundation of China (12302424),
the Key Research and Development Program of Shaanxi Province (2023-YBSF-172), the Innovation Chain of
Key Industries of Shaanxi Province (2024SF-ZDCYL-01-14), the Key Natural Science Research Project of the
Education Department of Anhui Province (K2021ZD0150), the Innovation Team of Xi’an Jiaotong
University (xtr062023002), and the Key Scientific Research Project of Xi’an Physical Education University
(2025ZD001).
Conflicts of interest
All authors have declared that there are no conflicts of interest.
Ethical approval and consent to participate
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Consent for publication
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Copyright
© The Author(s) 2026.
REFERENCES
1. Smith, J. A. B.; Murach, K. A.; Dyar, K. A.; Zierath, J. R. Exercise metabolism and adaptation in skeletal muscle. Nat. Rev. Mol. Cell.
Biol. 2023, 24, 607-32. DOI PubMed PMC
2. Egan, B.; Sharples, A. P. Molecular responses to acute exercise and their relevance for adaptations in skeletal muscle to exercise training.
Physiol. Rev. 2023, 103, 2057-170. DOI PubMed
3. Gabbett, T. J. The training-injury prevention paradox: should athletes be training smarter and harder? Br. J. Sports. Med. 2016, 50,
273-80. DOI PubMed PMC
4. Cheung, K.; Hume, P.; Maxwell, L. Delayed onset muscle soreness: treatment strategies and performance factors. Sports. Med. 2003, 33,
145-64. DOI PubMed
5. Valle, X.; Alentorn-Geli, E.; Tol, J. L.; et al. Muscle injuries in sports: a new evidence-informed and expert consensus-based
classification with clinical application. Sports. Med. 2017, 47, 1241-53. DOI PubMed
6. Edouard, P.; Reurink, G.; Mackey, A. L.; et al. Traumatic muscle injury. Nat. Rev. Dis. Primers. 2023, 9, 56. DOI PubMed
7. Impellizzeri, F. M.; Shrier, I.; McLaren, S. J.; et al. Understanding training load as exposure and dose. Sports. Med. 2023, 53, 1667-79.
DOI PubMed PMC
8. Martinez-Valdes, E.; Negro, F.; Laine, C. M.; Falla, D.; Mayer, F.; Farina, D. Tracking motor units longitudinally across experimental
sessions with high-density surface electromyography. J. Physiol. 2017, 595, 1479-96. DOI PubMed PMC
9. Koh, A.; Kang, D.; Xue, Y.; et al. A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat. Sci.
Transl. Med. 2016, 8, 366ra165. DOI PubMed PMC
10. Lee, S. P.; Ha, G.; Wright, D. E.; et al. Highly flexible, wearable, and disposable cardiac biosensors for remote and ambulatory
monitoring. NPJ. Digit. Med. 2018, 1, 2. DOI PubMed PMC
11. Wang, R.; Shen, Y.; Qian, D.; et al. Tensile and torsional elastomer fiber artificial muscle by entropic elasticity with
thermo-piezoresistive sensing of strain and rotation by a single electric signal. Mater. Horiz. 2020, 7, 3305-15. DOI
12. Li Y, ; Li W, ; Sun A, ; et al. A self-reinforcing and self-healing elastomer with high strength, unprecedented toughness and
room-temperature reparability. Mater. Horiz. 2021, 8, 267-75. DOI PubMed
13. Li, C.; Wang, H.; Song, Z.; et al. Wireless, wearable elastography via mechano-acoustic wave sensing for ambulatory monitoring of
tissue stiffness. Sci. Adv. 2025, 11, eady0534. DOI PubMed PMC
14. Cudejko, T.; Button, K.; Al-Amri, M. Wireless pressure insoles for measuring ground reaction forces and trajectories of the centre of
pressure during functional activities. Sci. Rep. 2023, 13, 14946. DOI PubMed PMC

