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Biomechanical analysis of the effect of finger joint configuration on hand grasping performance: rigid vs flexible

Wei, Y; Zou, Z; Qian, Z; Ren, L; Wei, G

Biomechanical analysis of the effect of finger joint configuration on hand grasping performance: rigid vs flexible Thumbnail


Authors

Y Wei

Z Zou

Z Qian

L Ren



Abstract

Human finger joints are conventionally simplified as rigid joints in robotic hand design and biomechanical hand modelling, due to their anatomic and morphologic complexity. However, our understanding of the effect of the finger joint configuration on the resulting hand performance is still primitive. In this study, we systematically investigate the grasping performance of the hands with the conventional rigid joints and the biomechanical flexible joints based on a computational human hand model. The measured muscle electromyography (EMG) and hand kinematic data during grasping are used as inputs for the grasping simulations. The results show that the rigid joint configuration currently used in most robotic hands leads to large reductions in hand contact force, contact pressure and contact area, compared to the flexible joint configuration. The grasping quality could be reduced up to 40% and 36% by the rigid joint configuration in terms of algebraic properties of grasping matrix and finger force limit respectively. Further investigation reveals that these reductions are caused by the weak rotational stiffness of the rigid joint configuration. This study implies that robotic/prosthetic hand performance could be improved by exploiting flexible finger joint design. Hand contact parameters and grasping performance may be underestimated by the rigid joint simplification in human hand modelling.

Citation

Wei, Y., Zou, Z., Qian, Z., Ren, L., & Wei, G. (2022). Biomechanical analysis of the effect of finger joint configuration on hand grasping performance: rigid vs flexible. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 1-1. https://doi.org/10.1109/tnsre.2022.3229165

Journal Article Type Article
Acceptance Date Nov 1, 2022
Publication Date Dec 14, 2022
Deposit Date Jan 13, 2023
Publicly Available Date Jan 13, 2023
Journal IEEE Transactions on Neural Systems and Rehabilitation Engineering
Print ISSN 1534-4320
Publisher Institute of Electrical and Electronics Engineers
Pages 1-1
DOI https://doi.org/10.1109/tnsre.2022.3229165
Publisher URL https://doi.org/10.1109/TNSRE.2022.3229165

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