Grasping Performance Depends Upon the Richness of Hand Feedback

Overview

Journal Exp Brain Res

Specialty Neurology

Date 2021 Jan 6

PMID 33403432

Citations 1

Authors

Prajith Sivakumar

Derek J Quinlan

Kevin M Stubbs

Jody C Culham

Affiliations

Soon will be listed here.

Abstract

Although visual feedback of the hand allows fast and accurate grasping actions, little is known about whether the nature of feedback of the hand affects performance. We investigated kinematics during precision grasping (with the index finger and thumb) when participants received different levels of hand feedback, with or without visual feedback of the target. Specifically, we compared performance when participants saw (1) no hand feedback; (2) only the two critical points on the index finger and thumb tips; (3) 21 points on all digit tips and hand joints; (4) 21 points connected by a "skeleton", or (5) full feedback of the hand wearing a glove. When less hand feedback was available, participants took longer to execute the movement because they allowed more time to slow the reach and close the hand. When target feedback was unavailable, participants took longer to plan the movement and reached with higher velocity. We were particularly interested in investigating maximum grip aperture (MGA), which can reflect the margin of error that participants allow to compensate for uncertainty. A trend suggested that MGA was smallest when ample feedback was available (skeleton and full hand feedback, regardless of target feedback) and when only essential information about hand and target was provided (2-point hand feedback + target feedback) but increased when non-essential points were included (21-point feedback). These results suggest that visual feedback of the hand affects grasping performance and that, while more feedback is usually beneficial, this is not necessarily always the case.

Citing Articles

Quantifying Hand Strength and Isometric Pinch Individuation Using a Flexible Pressure Sensor Grid.

Conway B, Taquet L, Boerger T, Young S, Krucoff K, Schmit B Sensors (Basel). 2023; 23(13).

PMID: 37447773 PMC: 10346473. DOI: 10.3390/s23135924.

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