Mechanical Sciences
Mechanical Sciences
Mechanical Sciences
Articles | Volume 17, issue 1
Articles | Volume 17, issue 1
https://doi.org/10.5194/ms-17-685-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ms-17-685-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 1
Research article
 | 
26 Jun 2026
Research article |  | 26 Jun 2026

Research on compliance control strategy of elbow–wrist rehabilitation robot based on information fusion

Hui Bian, Hang Shang, Zihan Li, Yifan Xu, Peixuan Du, Mingzhi Wang, Runyang Liu, and Ze Luo

Viewed

Total article views: 26 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
25 1 0 26 0 0
  • HTML: 25
  • PDF: 1
  • XML: 0
  • Total: 26
  • BibTeX: 0
  • EndNote: 0
Views and downloads (calculated since 26 Jun 2026)
Cumulative views and downloads (calculated since 26 Jun 2026)

Viewed (geographical distribution)

Total article views: 12 (including HTML, PDF, and XML) Thereof 12 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 16 Jul 2026
Download
Short summary
Aiming to address the problems of the large time delay and low compliance of the system caused by the slow speed of motion intention recognition based on the force signal, this paper integrates the force signal and the surface electromyography (sEMG) signal as the input of the elbow–wrist rehabilitation robot, thereby achieving a good balance between fast response and force compliance in the control system.
Read more
Share