Evidence map›Paper›PMID 28392098›Full record

ArticleHuman movement science2017

A soft-contact model for computing safety margins in human prehension.

Tarkeshwar Singh, Satyajit Ambike

Abstract read
In one paragraph

Article in Human movement science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Tarkeshwar SinghCollege of Health Professionals, Medical University of South Carolina, Charleston, SC 29425, United States. Electronic address: singht@musc.edu.
Satyajit AmbikeDepartment of Health and Kinesiology, Purdue University, West Lafayette, IN 47907, United States.

Funding

THE ORGANIZATION OF A SIMPLE SYNERGYR01NS035032 · NINDS · PENNSYLVANIA STATE UNIVERSITY-UNIV PARK · PI LATASH, MARK L · 1997 to 2015
$4.3M
PREHENSION SYNERGIESR01AR048563 · NIAMS · PENNSYLVANIA STATE UNIVERSITY-UNIV PARK · PI LATASH, MARK L · 2003 to 2014
$3.2M
FINGER COORDINATION IN ELDERLYR01AG018751 · NIA · PENNSYLVANIA STATE UNIVERSITY-UNIV PARK · PI LATASH, MARK L · 2001 to 2011
$2.5M
NIAMS NIH HHS R01 AR048563NIA NIH HHS R01 AG018751NINDS NIH HHS R01 NS035032
6 · The paper itself

Abstract

The soft human digit tip forms contact with grasped objects over a finite area and applies a moment about an axis normal to the area. These moments are important for ensuring stability during precision grasping. However, the contribution of these moments to grasp stability is rarely investigated in prehension studies. The more popular hard-contact model assumes that the digits exert a force vector but no free moment on the grasped object. Many sensorimotor studies use this model and show that humans estimate friction coefficients to scale the normal force to grasp objects stably, i.e. the smoother the surface, the tighter the grasp. The difference between the applied normal force and the minimal normal force needed to prevent slipping is called safety margin and this index is widely used as a measure of grasp planning. Here, we define and quantify safety margin using a more realistic contact model that allows digits to apply both forces and moments. Specifically, we adapt a soft-contact model from robotics and demonstrate that the safety margin thus computed is a more accurate and robust index of grasp planning than its hard-contact variant. Previously, we have used the soft-contact model to propose two indices of grasp planning that show how humans account for the shape and inertial properties of an object. A soft-contact based safety margin offers complementary insights by quantifying how humans may account for surface properties of the object and skin tissue during grasp planning and execution.

Indexed as

AdultFemaleFingersFrictionHand StrengthHealthy VolunteersHumansMaleModels, BiologicalPsychomotor PerformanceRoboticsSafetySkinSurface PropertiesFrictionGrasp planningPrehensionSafety marginsSoft-contact

Identifiers

PMID28392098
PMCPMC5610596

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.