Open Access
| Issue |
ITM Web Conf.
Volume 84, 2026
2026 International Conference on Advent Trends in Computational Intelligence and Data Science (ATCIDS 2026)
|
|
|---|---|---|
| Article Number | 01002 | |
| Number of page(s) | 7 | |
| Section | Intelligent Computing in Healthcare and Bioinformatics | |
| DOI | https://doi.org/10.1051/itmconf/20268401002 | |
| Published online | 06 April 2026 | |
- World Health Organization, Rehabilitation (2023) [Google Scholar]
- K. Jack, S. M. McLean, J. K. Moffett, E. Gardiner, Barriers to treatment adherence in physiotherapy outpatient clinics: a systematic review. Manual therapy 15, 220–228 (2010) [Google Scholar]
- Y. LeCun, Y. Bengio, G. Hinton, Deep learning. Nature 521, 436–444 (2015) [CrossRef] [Google Scholar]
- Y. Liao, A. Vakanski, M. Xian, A deep learning framework for assessing physical rehabilitation exercises. IEEE Transactions on Neural Systems and Rehabilitation Engineering 28, 468–477 (2020) [CrossRef] [Google Scholar]
- Z. Cao, G. Hidalgo, T. Simon, S. E. Wei, Y. Sheikh, OpenPose: realtime multi-person 2D pose estimation using part affinity fields. IEEE transactions on pattern analysis and machine intelligence 43, 172–186 (2021) [Google Scholar]
- J. A. Francisco, P. S. Rodrigues, Computer vision based on a modular neural network for automatic assessment of physical therapy rehabilitation activities. IEEE Transactions on Neural Systems and Rehabilitation Engineering 31, 2174–2183 (2023) [Google Scholar]
- Z. Zhang, Q. Fang, X. Gu, Objective assessment of upper-limb mobility for poststroke rehabilitation. IEEE Transactions on Biomedical Engineering 63, 859–868 (2016) [Google Scholar]
- S. Patel, R. Hughes, T. Hester, J. Stein, M. Akay, P. Bonato, A novel approach to automated assessment of motor recovery in stroke survivors using wearable technology, in Proceedings of the 2017 International Conference on Rehabilitation Robotics (ICORR) (2017), pp. 1318–1323 [Google Scholar]
- C. Wang, Y. Zhang, X. Chen, Action quality assessment with temporal pose-image representation, in Proceedings of the 27th ACM international conference on multimedia (2019), pp. 1957–1965 [Google Scholar]
- S. Yan, Y. Xiong, D. Lin, Spatial temporal graph convolutional networks for skeleton-based action recognition, in Proceedings of the AAAI conference on artificial intelligence, Vol. 32 (2018) [Google Scholar]
- Y. Qiu, J. Wang, Z. Jin, H. Chen, M. Zhang, and L. Guo, Pose-guided matching based on deep learning for assessing quality of action on rehabilitation training, Biomedical Signal Processing and Control, vol. 72, p. 103323, (2022). [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.