Spatial patterns in the control of human arm movement.

Haggard, Patrick; Richardson, James P.

doi:10.1037/0096-1523.22.1.42

Cited by 54 publications

(61 citation statements)

References 29 publications

(67 reference statements)

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“…First, when targets are specified for the hand, that is, in the absence of the kinematic transformation of the tool, hand paths are almost straight even in the absence of continuous visual feedback. Without the dynamic transformation of the tool, there is a slight concave curvature, consistent with findings of Haggard and Richardson (1996), Wolpert et al (1994), and Van Thiel et al (1998). With the dynamic transformation we found a slight convex curvature.…”

Section: Discussionsupporting

confidence: 78%

“…Consistent with previous observations, we expected almost straight movement paths or a slight concave curvature (Haggard and Richardson 1996;Wolpert et al 1994;Van Thiel et al 1998) and only little or no influence of the absence versus presence of the dynamic transformation . In the presence of the kinematic transformation targets were defined for the tip of the lever.…”

Section: Methodssupporting

confidence: 78%

“…Without the dynamic transformation curvature of hand paths was concave, corresponding to findings of Haggard and Richardson (1996), Wolpert et al (1994), and Van Thiel et al (1998). When the dynamic transformation was present, curvature of hand paths became convex.…”

Section: Methodsmentioning

confidence: 93%

See 2 more Smart Citations

Movement paths in operating hand-held tools: tests of distal-shift hypotheses

Sülzenbrück

Heuer

2013

Journal of Neurophysiology

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Section: Discussionsupporting

confidence: 78%

Section: Methodssupporting

confidence: 78%

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Movement paths in operating hand-held tools: tests of distal-shift hypotheses

Sülzenbrück

Heuer

2013

Journal of Neurophysiology

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“…10, 3 right panels) as well as Coriolis (thin solid line), centripetal (dashed line), and inertial interaction (dashed-dotted line) torque components of fast reaching movements to each target performed by 1 subject in the light condition. the computational complexity of executing the path (Haggard and Richardson 1996;Haggard et al 1995). In addition, biomechanical constraints (e.g., the hand coming in too close proximity to the trunk) may also partly explain the outward curvature of finger trajectories involving significant trunk contribution.…”

Section: Coriolis Force Magnitude and Reaching Errorsmentioning

confidence: 99%

Coordinated Turn-and-Reach Movements. I. Anticipatory Compensation for Self-Generated Coriolis and Interaction Torques

Pigeon

Bortolami

DiZio

et al. 2003

Journal of Neurophysiology

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Pigeon, Pascale, Simone B. Bortolami, Paul DiZio, and James R. Lackner. Coordinated turn-and-reach movements. I. Anticipatory compensation for self-generated Coriolis and interaction torques. J Neurophysiol 89: 276 -289, 2003; 10.1152/jn.00159.2001. When reaching movements involve simultaneous trunk rotation, additional interaction torques are generated on the arm that are absent when the trunk is stable. To explore whether the CNS compensates for such self-generated interaction torques, we recorded hand trajectories in reaching tasks involving various amplitudes and velocities of arm extension and trunk rotation. Subjects pointed to three targets on a surface slightly above waist level. Two of the target locations were chosen so that a similar arm configuration relative to the trunk would be required for reaching to them, one of these targets requiring substantial trunk rotation, the other very little. Significant trunk rotation was necessary to reach the third target, but the arm's radial distance to the body remained virtually unchanged. Subjects reached at two speeds-a natural pace (slow) and rapidly (fast)-under normal lighting and in total darkness. Trunk angular velocity and finger velocity relative to the trunk were higher in the fast conditions but were not affected by the presence or absence of vision. Peak trunk velocity increased with increasing trunk rotation up to a maximum of 200°/s. In slow movements, peak finger velocity relative to the trunk was smaller when trunk rotation was necessary to reach the targets. In fast movements, peak finger velocity was ϳ1.7 m/s for all targets. Finger trajectories were more curved when reaching movements involved substantial trunk rotation; however, the terminal errors and the maximal deviation of the trajectory from a straight line were comparable in slow and fast movements. This pattern indicates that the larger Coriolis, centripetal, and inertial interaction torques generated during rapid reaches were compensated by additional joint torques. Trajectory characteristics did not vary with the presence or absence of vision, indicating that visual feedback was unnecessary for anticipatory compensations. In all reaches involving trunk rotation, the finger movement generally occurred entirely during the trunk movement, indicating that the CNS did not minimize Coriolis forces incumbent on trunk rotation by sequencing the arm and trunk motions into a turn followed by a reach. A simplified model of the arm/trunk system revealed that additional interaction torques generated on the arm during voluntary turning and reaching were equivalent to Յ1.8 g (1 g ϭ 9.81 m/s 2 ) of external force at the elbow but did not degrade performance. In slow-rotation room studies involving reaching movements during passive rotation, Coriolis forces as small as 0.2 g greatly deflect movement trajectories and endpoints. We conclude that compensatory motor innervations are engaged in a predictive fashion to counteract impending self-generated interaction torques during voluntary reaching movem...

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“…Morasso (1981) observed that point-to-point aiming movements indeed tend to be performed along straight paths. Minimum torquechange trajectories, however, show systematic curvature variations, depending on where a particular aiming movement is performed in workspace, as experimentally con®rmed by Atkeson and Hollerbach (1985), Uno et al (1989), Haggard and Richardson (1996), Van Thiel et al (1998), and Boessenkool et al (1998). Although it has been demonstrated that curved movements can be accounted for by both models by presuming via points, i.e., intermediate locations through which the hand must move on its way to the prede®ned end location, it is not clear how these models account for systematic variations in curvature of the trajectory due to self-or externallyimposed end-point constraints such as the angle and speed with which a target area is approached.…”

Section: Introductionmentioning

confidence: 99%

End-point constraints in aiming movements: effects of approach angle and speed

2001

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Abstract. The present study focuses on two trajectoryformation models of point-to-point aiming movements, viz., the minimum-jerk and the minimum torque-change model. To date, few studies on minimum-jerk and minimum torque-change trajectories have incorporated self-or externally imposed end-point constraints, such as the direction and velocity with which a target area is approached. To investigate which model accounts best for the eects on movement trajectories of such ± in many circumstances ± realistic end-point constraints, we adjusted both the minimum-jerk and the minimum torque-change model so that they could generate trajectories of which the ®nal part has a speci®c direction and speed. The adjusted models yield realistic trajectories with a high curvature near movement completion.Comparison of simulated and measured movement trajectories show that pointing movements that are constrained with respect to ®nal movement direction and speed can be described in terms of minimization of joint-torque changes.

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Spatial patterns in the control of human arm movement.

Cited by 54 publications

References 29 publications

Movement paths in operating hand-held tools: tests of distal-shift hypotheses

Movement paths in operating hand-held tools: tests of distal-shift hypotheses

Coordinated Turn-and-Reach Movements. I. Anticipatory Compensation for Self-Generated Coriolis and Interaction Torques

End-point constraints in aiming movements: effects of approach angle and speed

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