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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.

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. [ABSTRACT FROM AUTHOR]

In this study, adaptive pincer grasping of soft pneumatic grippers (SPGs) is considered, and we propose how the performance of soft pneumatic actuators (SPAs) and the stiffness of grasped objects can be accounted for in modeling and control. The grasping kinetics was analyzed. The connection between grasping quality and SPA performance is discussed. We also devised a subjective definition of grasping quality due to SPA performance. A modeling technique was established, which makes dominant factors of grasping quality due to the SPA performance predictable over the gripper input. Later, a control architecture was developed. This architecture demonstrates how the grasping is implemented. The modeling technique was used to forecast grasping quality due to the SPA performance and its factors. An experiment was conducted to obtain actual results. The predicted and actual results were correspondingly compared. The results show minute deviation, thereby validating the reliability of the grasping. This study clarifies the association between grasping quality and SPA performance and contributes an advancement toward modellable and controllable task-level variables, such as grasping quality, in SPG pincer grasping. [ABSTRACT FROM AUTHOR]

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.

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. [ABSTRACT FROM AUTHOR]

In this study, adaptive pincer grasping of soft pneumatic grippers (SPGs) is considered, and we propose how the performance of soft pneumatic actuators (SPAs) and the stiffness of grasped objects can be accounted for in modeling and control. The grasping kinetics was analyzed. The connection between grasping quality and SPA performance is discussed. We also devised a subjective definition of grasping quality due to SPA performance. A modeling technique was established, which makes dominant factors of grasping quality due to the SPA performance predictable over the gripper input. Later, a control architecture was developed. This architecture demonstrates how the grasping is implemented. The modeling technique was used to forecast grasping quality due to the SPA performance and its factors. An experiment was conducted to obtain actual results. The predicted and actual results were correspondingly compared. The results show minute deviation, thereby validating the reliability of the grasping. This study clarifies the association between grasping quality and SPA performance and contributes an advancement toward modellable and controllable task-level variables, such as grasping quality, in SPG pincer grasping.