Closed-Loop digital therapeutics empowered by deep reinforcement learning and wearable sensing for precision orthopedic rehabilitation: a simulation-based proof-of-concept study
- 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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Cite this work
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
Source records
- crossref · retrieved 2026-09-25T10:47:23.716Z