Bimanual Grasping Adheres to Weber's Law

Weber's law states that our ability to detect changes in stimulus attributes decreases linearly with their magnitude. This principle holds true for many attributes across sensory modalities but appears to be violated in grasping. One explanation for the failure to observe Weber's law in grasping is that its effect is masked by biomechanical constraints of the hand. We tested this hypothesis using a bimanual task that eliminates biomechanical constraints. Participants either grasped differently sized boxes that were comfortably within their arm span (action task) or estimated their width (perceptual task). Within each task, there were two conditions: One where the hands’ start positions remained fixed for all object sizes (meaning the distance between the initial and final hand-positions varied with object size), and one in which the hands’ start positions adapted with object size (such that the distance between the initial and final hand-position remained constant). We observed adherence to Weber's law in bimanual estimation and grasping across both conditions. Our results conflict with a previous study that reported the absence of Weber's law in bimanual grasping. We discuss potential explanations for these divergent findings and encourage further research on whether Weber's law persists when biomechanical constraints are reduced.

Transfer and generalization of learned manipulation between unimanual and bimanual tasks

Successful object manipulation, such as preventing object roll, relies on the modulation of forces and centers of pressure (point of application of digits on each grasp surface) prior to lift onset to generate a compensatory torque. Whether or not generalization of learned manipulation can occur after adding or removing effectors is not known. We examined this by recruiting participants to perform lifts in unimanual and bimanual grasps and analyzed results before and after transfer. Our results show partial generalization of learned manipulation occurred when switching from a (1) unimanual to bimanual grasp regardless of object center of mass, and (2) bimanual to unimanual grasp when the center of mass was on the thumb side. Partial generalization was driven by the modulation of effectors’ center of pressure, in the appropriate direction but of insufficient magnitude, while load forces did not contribute to torque generation after transfer. In addition, we show that the combination of effector forces and centers of pressure in the generation of compensatory torque differ between unimanual and bimanual grasping. These findings highlight that (1) high-level representations of learned manipulation enable only partial learning transfer when adding or removing effectors, and (2) such partial generalization is mainly driven by modulation of effectors’ center of pressure.

Anthropomorphism Index of Mobility for Artificial Hands

The increasing development of anthropomorphic artificial hands makes necessary quick metrics that analyze their anthropomorphism. In this study, a human grasp experiment on the most important grasp types was undertaken in order to obtain an Anthropomorphism Index of Mobility (AIM) for artificial hands. The AIM evaluates the topology of the whole hand, joints and degrees of freedom (DoFs), and the possibility to control these DoFs independently. It uses a set of weighting factors, obtained from analysis of human grasping, depending on the relevance of the different groups of DoFs of the hand. The computation of the index is straightforward, making it a useful tool for analyzing new artificial hands in early stages of the design process and for grading human-likeness of existing artificial hands. Thirteen artificial hands, both prosthetic and robotic, were evaluated and compared using the AIM, highlighting the reasons behind their differences. The AIM was also compared with other indexes in the literature with more cumbersome computation, ranking equally different artificial hands. As the index was primarily proposed for prosthetic hands, normally used as nondominant hands in unilateral amputees, the grasp types selected for the human grasp experiment were the most relevant for the human nondominant hand to reinforce bimanual grasping in activities of daily living. However, it was shown that the effect of using the grasping information from the dominant hand is small, indicating that the index is also valid for evaluating the artificial hand as dominant and so being valid for bilateral amputees or robotic hands.