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 | 04018 | |
| Number of page(s) | 9 | |
| Section | Computer Vision, Robotic Systems, and Intelligent Control | |
| DOI | https://doi.org/10.1051/itmconf/20268404018 | |
| Published online | 06 April 2026 | |
- A. Saldarriaga, L. C. Valero, L. C. Paredes, Soft hand exoskeletons for rehabilitation: Recent advances and future perspectives. Front. Robot. AI 11, 1–12 (2024). [Google Scholar]
- P. Rojek, P. Borys, D. Słota, Hand exoskeleton—development of own concept. Sensors 23, 4002 (2023). [Google Scholar]
- B. Gherman, I. Zima, C. Vaida, P. Tucan, A. Pisla, I. Birlescu, J. Machado, D. Pisla, Robotic systems for hand rehabilitation—past, present and future. Technologies 13, 37 (2025) [Google Scholar]
- M. Cempini, S. Cortese, N. Vitiello, A powered finger–thumb wearable hand exoskeleton with self-aligning joint axes. IEEE Trans. Robot. 32, 1179–1192 (2016) [Google Scholar]
- L. Resquní, J. I. Serrano, A. del Ama, Upper -limb exoskeletons for rehabilitation: State of the art and future challenges. Sensors 22, 6127 (2022) [Google Scholar]
- Z. Li, S. Song, T. Zhang, Intention-driven rehabilitation control using deep learning in exoskeleton robots. IEEE Access 10, 65432–65445 (2022) [Google Scholar]
- P. Polygerinos, N. Correll, B. Morin, Soft robotics: Review of recent developments of pneumatic soft manipulators and soft grippers. Adv. Eng. Mater. 19, 1600096 (2017) [Google Scholar]
- J.-K. Lee, D. Kim, Reinforcement learning-based adaptive control for soft exoskeleton hands, in Lecture Notes in Electrical Engineering, vol. 1033, Springer, Singapore (2024), pp. 1069–1081 [Google Scholar]
- C. Toro-Ossaba, C. Valverde, D. Rojas, Myoelectric control in rehabilitative and assistive soft exoskeletons: A comprehensive review. Biomed. Eng. Online 24, 55–71 (2025) [Google Scholar]
- D. K. S. Gopura, K. Kiguchi, Mechanical designs of active upper-limb exoskeleton robots: State-of-the-art and design difficulties. IEEE Robot. Autom. Mag. 21, 66–73 (2014) [Google Scholar]
- K. Harada, K. Takahashi, T. Noda, Development of a hand rehabilitation robot with independent finger motion, in Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), Noordwijk, The Netherlands (2006) [Google Scholar]
- G. Xiloyannis, M. Chiaradia, D. Cappello, Soft robotic exoskeletons for hand rehabilitation: A review. IEEE Trans. Neural Syst. Rehabil. Eng. 27, 772–785 (2019) [Google Scholar]
- M. Mashud, M. Hasan, A. Rahman, Advances in control techniques for rehabilitation exoskeleton robots: A review. Robot. Auton. Syst. 173, 104688 (2025). [Google Scholar]
- S. S. Norman, J. Jamaludin, N. A. Malik, Advancements in hand assistive technologies for stroke rehabilitation: A systematic review of mechanical assistive devices, in Proc. 2025 IEEE 8th Int. Conf. Electr., Control and Comput. Eng. (InECCE), pp. 161–166 (2025). [Google Scholar]
- R. M. Rossi, C. Bossi, F. Cordella, Human–machine synergy in soft hand exoskeletons: Challenges and perspectives. Front. Bioeng. Biotechnol. 12, 2024. [Google Scholar]
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