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A robotic test rig for performance assessment of prosthetic joints

Etoundi, Appolinaire C.; Dobner, Alexander; Agrawal, Subham; Semasinghe, Chathura L.; Georgilas, Ioannis; Jafari, Aghil


Appolinaire C. Etoundi

Alexander Dobner

Subham Agrawal

Chathura L. Semasinghe

Ioannis Georgilas


Movement within the human body is made possible by joints connecting two or more elements of the musculoskeletal system. Losing one or more of these connections can seriously limit mobility, which in turn can lead to depression and other mental issues. This is particularly pertinent due to a dramatic increase in the number of lower limb amputations resulting from trauma and diseases such as diabetes. The ideal prostheses should re-establish the functions and movement of the missing body part of the patient. As a result, the prosthetic solution has to be tested stringently to ensure effective and reliable usage. This paper elaborates on the development, features, and suitability of a testing rig that can evaluate the performance of prosthetic and robotic joints via cyclic dynamic loading on their complex movements. To establish the rig’s validity, the knee joint was chosen as it provides both compound support and movement, making it one of the major joints within the human body, and an excellent subject to ensure the quality of the prosthesis. Within the rig system, a motorised lead-screw simulates the actuation provided by the hamstring-quadricep antagonist muscle pair and the flexion experienced by the joint. Loads and position are monitored by a load cell and proximity sensors respectively, ensuring the dynamics conform with the geometric model and gait analysis. Background: Robotics, Prosthetics, Mechatronics, Assisted Living. Methods: Gait Analysis, Computer Aided Design, Geometry Models. Conclusion: Modular Device, Streamlining Rehabilitation.


Etoundi, A. C., Dobner, A., Agrawal, S., Semasinghe, C. L., Georgilas, I., & Jafari, A. (2022). A robotic test rig for performance assessment of prosthetic joints. Frontiers in Robotics and AI, 8, Article 613579.

Journal Article Type Article
Acceptance Date Dec 22, 2021
Online Publication Date Mar 7, 2022
Publication Date Mar 7, 2022
Deposit Date Mar 9, 2022
Publicly Available Date Mar 9, 2022
Journal Frontiers in Robotics and AI
Electronic ISSN 2296-9144
Publisher Frontiers Media
Peer Reviewed Peer Reviewed
Volume 8
Article Number 613579
Keywords Artificial Intelligence; Computer Science Applications
Public URL


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