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

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