Biomechanical Analysis of the Effect of the Finger Extensor Mechanism on Hand Grasping Performance

Yuyang Wei, Zhenmin Zou, Zhihui Qian, Lei Ren, Guowu Wei

Research output: Contribution to journalArticlepeer-review

Abstract

Quantifying the effect of routing and topology of the inter-connected finger extensor mechanism on hand grasping performances is a long-standing research problem for the better clinical diagnosis, surgical planning and biomimetic hand development. However, it is technically demanding to measure the hand performance parameters such as the contact forces and contact area during hand manipulation. It is also difficult to replicate human hand performance through the physical hand model due to its sophisticated musculotendinous structure. In this study, an experimental validated subject-specific finite element (FE) human hand model was used for the first time to quantify the influence of different tendon topologies and material properties on hand grasping quality. It is found that the grasping quality is reduced by 15.94% and 8.54% if there are no extensor hood and lateral band respectively, and the former plays a more important role in transmitting forces and maintaining grasping qualities than the latter. Excluding extensor hood in the topology causes more reductions in hand contact pressure and contact area than omitting lateral band. 7.5% of the grasping quality is lost due to a softened tendon with half of its original Young’s Modulus. Hardened extensor tendon does increase the grasping quality, but the enhancing effect tends to level off once the tendon Young’s Modulus is increased by more than 50%. These results prove that the lateral band and extensor hood are critical components for maintaining grasping quality. The dexterity and grasping quality of robotic and prosthetic hands could be improved by integrating these two components. There is also no need to use very stiff tendon material as it won’t help to effectively enhance the grasping quality.
Original languageEnglish
Pages (from-to)360-368
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume30
Early online date27 Jan 2022
DOIs
Publication statusPublished - 27 Jan 2022

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