title: Quantifying feedforward control: a linear scaling model for fingertip forces and object weight.
abstract: The ability to predict the optimal fingertip forces according to object properties before the object is lifted is known as feedforward control, and it is thought to occur due to the formation of internal representations of the object's properties. The control of fingertip forces to objects of different weights has been studied extensively by using a custom-made grip device instrumented with force sensors. Feedforward control is measured by the rate of change of the vertical (load) force before the object is lifted. However, the precise relationship between the rate of change of load force and object weight and how it varies across healthy individuals in a population is not clearly understood. Using sets of 10 different weights, we have shown that there is a log-linear relationship between the fingertip load force rates and weight among neurologically intact individuals. We found that after one practice lift, as the weight increased, the peak load force rate (PLFR) increased by a fixed percentage, and this proportionality was common among the healthy subjects. However, at any given weight, the level of PLFR varied across individuals and was related to the efficiency of the muscles involved in lifting the object, in this case the wrist and finger extensor muscles. These results quantify feedforward control during grasp and lift among healthy individuals and provide new benchmarks to interpret data from neurologically impaired populations as well as a means to assess the effect of interventions on restoration of feedforward control and its relationship to muscular control.
authors: Center for the Promotion of Research Involving Innovative Statistical Methodology, Steinhardt School of Culture, Education and Human Development, New York University; New York, New York;
authors: Ying
authors: Y
authors: Lu
authors: Department of Rehabilitation Medicine, New York University School of Medicine, New York, New York; and.
authors: Seda
authors: S
authors: Bilaloglu
authors: Department of Rehabilitation Medicine, New York University School of Medicine, New York, New York; and.
authors: Viswanath
authors: V
authors: Aluru
authors: Department of Rehabilitation Medicine, New York University School of Medicine, New York, New York; and Department of Physical Therapy, Steinhardt School of Culture, Education and Human Development, New York University, New York, New York preeti.raghavan@nyumc.org.
authors: Preeti
authors: P
authors: Raghavan
mesh_terms: D000328:Adult; D005260:Female; D005385:Fingers / Q000502:physiology*; D018737:Hand Strength / Q000502:physiology*; D006801:Humans; D007858:Learning / Q000502:physiology; D016014:Linear Models; D008297:Male; D008959:Models, Neurological; D009043:Motor Activity / Q000502:physiology*
keywords: electromyography; feedforward and feedback control; motor control and learning; precision grasp; sensorimotor adaptation