Evidence for Dynamic Primitives in a Constrained Motion Task

Abstract

Ten right-handed male subjects turned a crank (radius 10 cm) in two directions at three constant instructed speeds (fast, medium, very slow) with visual speed feedback. They completed 23 trials at each speed. While the hand was constrained to move in a circle, forces against the constraint were non-zero. To disentangle the influences of biomechanics and neural control we estimated a neurally-determined motion underlying the observed movements and forces. Assuming a plausible mathematical model of interactive dynamics the peripheral neuromechanics could be 'subtracted', revealing an underlying motion that reflects neural influences. We called this data-driven construct the zero-force trajectory. The observed zero-force trajectory was approximately elliptical, with systematic changes of speed with curvature, and its orientation changed with turning direction. Its major axis, estimated by the principal eigenvector of its covariance matrix, differed significantly for different directions, but not with speed. As peripheral neuromuscular compliance (i.e. low mechanical impedance) mitigates the consequences of imperfect execution, the required precision of motion commands is reduced. To produce circular hand motions, this control strategy requires an oscillatory zero-force trajectory that leads hand motion. Due to non-isotropic dynamics, that lead differs between degrees of freedom resulting in an elliptical zero-force trajectory. The ellipses' orientations differ with direction of rotation, as observed in the experimental data. As elliptical motion is generated by two orthogonal sinusoids with non-zero phase difference, these results support our hypothesis that humans simplify this constrainedmotion task by exploiting primitive dynamic actions, oscillations and impedance.

Dynamic Primitives Limit Human Force Regulation During Motion

“…Previous studies of crank turning suggest that during physical interaction humans generate an elliptical zero-force trajectory which exhibits a coincidence of speed and curvature extrema [28]. These observations are also consistent with the work of [17], [25], [29], [30]. The smallest force errors in [17] were observed when the velocity profile of the robot followed the two-thirds power-law relation.…”

Finding the rhythm: Humans exploit nonlinear intrinsic dynamics of compliant systems in periodic interaction tasks

“…This implies that humans must be able to estimate the dynamics of external objects through haptic interactions. This idea is also supported by recent works from the research groups of Hogan and Sternad [1,2,[6][7][8].…”

Behavioral Consequences of Velocity Commands: Brownian Processes in Human Motor Tasks

“…Reaching with the upper limb has been studied widely in motor neuroscience [20][21][22][23][24]. Crank turning has been less widely studied [25][26][27][28], despite it being the most common activity of daily living [13]. The crank-turning task occupies a finite region of the arm's workspace; as a result, the displacement of the hand relative to the thorax is bounded.…”

“…Two different human subject experiments were conducted at MIT: crank turning (10 right-handed collegeaged male subjects), and static hand posture control (4 males and 6 females, ages[23][24][25][26][27][28][29][30][31][32][33][34][35][36]. All participants gave informed, written consent before the experiment.…”