Effective execution of a manipulation task using prosthetic or robotic hands requires that the motion and the impedance profiles of the fingers be appropriately commanded. This, however, brings some design and control challenges regarding the individual planning and realization of the finger motion and stiffness trajectories. It appears that the central nervous system solves for this complexity in an effective and coordinated manner which has been well-recognized under
the concept of hand synergies. While the exploitation of this concept in kinematic coordinates has lead to the development of several successful robotic designs and control strategies, its extension to dynamic coordinates, such as coordinated stiffening of the fingers, remains to be investigated. Indeed, in this study we provide preliminary evidence on the existence of such coordinated stiffening patterns in human fingers and establish initial steps towards a real-time and effective modelling of the finger stiffness in a tripod grasp. To achieve this goal, the endpoint stiffness of the thumb, index and middle fingers of five healthy subjects are experimentally identified and correlated with the electromyography (EMG) signals recorded from a dominant antagonistic pair of the forearm muscles. Our findings suggest that:

i) the magnitude of the stiffness ellipses at the fingertips grows in a coordinated way, subsequent to the co-contraction of the forearm muscles;

ii) the length of the ellipses’ axes appears to have a nearly linear relationship with the co-contraction level of the antagonistic muscle pair.