Human arm stiffness and equilibrium-point trajectory during multi-joint movement

Abstract

By using a newly designed high-performance manipulandum and a new estimation algorithm, we measured human multi-joint arm stiffness parameters during multi-joint point-to-point movements on a horizontal plane. This manipulandum allows us to apply a sufficient perturbation to subject's arm within a brief period during movement. Arm stiffness parameters were reliably estimated using a new algorithm, in which all unknown structural parameters could be estimated independent of arm posture (i.e., constant values under any arm posture). Arm stiffness during transverse movement was considerably greater than that during corresponding posture, but not during a longitudinal movement. Although the ratios of elbow, shoulder, and double-joint stiffness were varied in time, the orientation of stiffness ellipses during the movement did not change much. Equilibrium-point trajectories that were predicted from measured stiffness parameters and actual trajectories were slightly sinusoidally curved in Cartesian space and their velocity profiles were quite different from the velocity profiles of actual hand trajectories. This result contradicts the hypothesis that the brain does not take the dynamics into account in movement control depending on the neuromuscular servo mechanism; rather, it implies that the brain needs to acquire some internal models of controlled objects.

Learning the dynamics of reaching movements results in the modification of arm impedance and long-latency perturbation responses

“…This is similar to the approach taken by Dolan (1991) and Gomi and Kawato (1997). However, the approach suffers from uncertainties about the lengths of the links and non-rigidity of the muscle mass.…”

“…A number of previous reports have estimated human arm impedance during multi-joint voluntary movements (Gomi and Kawato 1997;Gomi and Osu 1998;Dolan et al 1993;Lacquaniti et al 1993). In these works, small perturbations were applied to the limb and the restoring forces were approximated as a function of displacement.…”

Motor learning through the combination of primitives

“…Katayama & Kawato (1993) and then Gomi & Kawato (1997) repeated Flash's simulation using lower values of sti¡ness and found, not surprisingly, that in order to reproduce the actual trajectory of the hand, the virtual trajectory had to follow a much more complicated pathway. The results obtained by Gomi & Kawato are at variance with those of Won & Hogan (1995), who were able to show that for relatively slow and low-amplitude arm trajectories the virtual equilibrium point was close to the actual trajectory.…”

Inter-joint coupling and joint angle synergies of human catching movements

“…In the context of human arm movements, PCA has been applied to the analysis of rhythmic juggling movements (Post, Daffertshofer, & Beek, 2000), object retrieval (Sabatini, 2002), and whole body reaching movements (Thomas, Corcos, & Hasan, 2005). Many studies use a setup related to the common "center-out task" (Galloway & Koshland, 2002;Gomi & Kawato, 1997;Morasso, 1981), in which participants are instructed to execute relatively slow, well-planned pointing or reach-to-grasp movements constrained to a horizontal plane. Sabatini (2002) found that such planar movements are effected by two types of muscle activity patterns, one for the outward and one for the inward part of the movement.…”