Articles in PresS. J Neurophysiol (October 5, 2005). doi:10.1152/jn.00610.2005

Title: Haptic identification of surfaces as fields of force

Running Head: Haptic identification of surfaces

Authors:

Vikram S. Chib^1,2,3; James L. Patton^1,2, Kevin M. Lynch³, Ferdinando A. Mussa-Ivaldi1^,2,4

¹Sensory Motor Performance Program, Rehabilitation Institute of Chicago

²Department of Biomedical Engineering, Northwestern University

³Laboratory for Intelligent Mechanical Systems, Department of Mechanical Engineering, Northwestern University

⁴Department of Physiology, Northwestern University

 

Correspondence should be addressed to:

Vikram S. Chib

345 East Superior Street

Suite 1406

Chicago, IL 60611

Phone: 312.238.1232

email: v-chib@northwestern.edu

 

ABSTRACT

The ability to discriminate an object’s shape and mechanical properties from touch is one of the most fundamental somatosensory functions. When exploring physical properties of an object, such as stiffness and curvature, humans probe the object’s surface and obtain information from the many sensory receptors in their upper limbs.  This sensory information is critical for the guidance of actions. We investigated how humans acquire an internal representation of the shape and mechanical properties of surfaces and how this information affects the execution of trajectories over the surface. Experiments involved subjects executing trajectories while holding a planar manipulandum that renders planar virtual objects with variable shape and mechanical properties. Subjects were instructed to make reaching movements with the hand, between points on the boundary of a curved virtual disk of varying stiffness and curvature. The results suggest two classifications of adaptive responses: force perturbations and object boundaries. In the first case, a rectilinear hand movement is enforced by opposing the interaction forces. In the second case, the trajectory conforms to the object boundary so as to reduce interaction forces. While this dichotomy is evident for very rigid and very soft objects, the likelihood of an object boundary classification depended, in a smooth and monotonic way, on the average force experienced during the initial movements. Furthermore, the observed response across a variety of stiffness values lead to a constant average interaction force after adaptation. This suggests that the nervous system may select from the two responses via a mechanism that attempts to establish a constant interaction force.

 

Keywords: internal representation, motor learning, haptics, stiffness, virtual surface

Full article