Closed-Loop digital therapeutics empowered by deep reinforcement learning and wearable sensing for precision orthopedic rehabilitation: a simulation-based proof-of-concept study

Jiahao Dong, Tao Chen, Zhongyu Peng

Open source

DOI
10.3389/fresc.2026.1822939
Published
2026-06-11
Container
Frontiers in Rehabilitation Sciences
Publisher
Frontiers Media SA
Open access
unknown

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BibTeX

@article{allodium:10.3389/fresc.2026.1822939,
  title = {Closed-Loop digital therapeutics empowered by deep reinforcement learning and wearable sensing for precision orthopedic rehabilitation: a simulation-based proof-of-concept study},
  author = {Jiahao Dong and Tao Chen and Zhongyu Peng},
  year = {2026},
  journal = {Frontiers in Rehabilitation Sciences},
  doi = {10.3389/fresc.2026.1822939},
  url = {https://doi.org/10.3389/fresc.2026.1822939}
}

RIS

TY  - JOUR
TI  - Closed-Loop digital therapeutics empowered by deep reinforcement learning and wearable sensing for precision orthopedic rehabilitation: a simulation-based proof-of-concept study
AU  - Jiahao Dong
AU  - Tao Chen
AU  - Zhongyu Peng
PY  - 2026
JO  - Frontiers in Rehabilitation Sciences
DO  - 10.3389/fresc.2026.1822939
UR  - https://doi.org/10.3389/fresc.2026.1822939
ER  - 

APA

Dong, J., Chen, T., & Peng, Z. (2026). Closed-Loop digital therapeutics empowered by deep reinforcement learning and wearable sensing for precision orthopedic rehabilitation: a simulation-based proof-of-concept study. Frontiers in Rehabilitation Sciences. https://doi.org/10.3389/fresc.2026.1822939

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