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Grip Forces when Passing an Object to a Partner

Overview
Journal Exp Brain Res
Specialty Neurology
Date 2005 Mar 12
PMID 15761722
Citations 14
Authors
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Abstract

The goal of the present study was to investigate how grip forces are applied when transferring stable control of an object from one person to another. We asked how grip forces would be modified by the passer to (1) control for inertial forces as the object was transported toward the receiver and (2) control for the impending perturbation when the receiver made contact with the object. Twelve volunteers worked in pairs during this experiment. One partner, playing the role of passer, transported an object with embedded load cells forward or held the object at an interception location. The second partner, playing the role of receiver, waited at an interception location or reached toward the passed object. Kinematic results indicated that while passers performed a stereotypical movement, receivers were sensitive to the motion of the object as they reached to make contact. Grip force results indicated that passers' grip forces and grip/load force ratios were variable on a trial-to-trial basis, suggesting that a refined internal model of the passing task was not achieved within the timeframe of the experiment. Furthermore, a decoupling of the temporal and magnitude characteristics of the grip and inertial forces was noted in conditions where passers transported the object toward the receiver. During object transfer, it was noted that passers used visual feedback-based anticipatory control to precisely time initial grip force release, while somatosensory control was used by both the passer and receiver to precisely coordinate transfer rate.

Citing Articles

Unveiling the invisible: receivers use object weight cues for grip force planning in handover actions.

Kopnarski L, Rudisch J, Kutz D, Voelcker-Rehage C Exp Brain Res. 2024; 242(5):1191-1202.

PMID: 38498154 PMC: 11078835. DOI: 10.1007/s00221-024-06813-y.


Measuring System for Synchronous Recording of Kinematic and Force Data during Handover Action of Human Dyads.

Kutz D, Kopnarski L, Puschel J, Rudisch J, Voelcker-Rehage C Sensors (Basel). 2023; 23(24).

PMID: 38139540 PMC: 10747505. DOI: 10.3390/s23249694.


Optimizing human-robot handovers: the impact of adaptive transport methods.

Kappler M, Mamaev I, Alagi H, Stein T, Deml B Front Robot AI. 2023; 10:1155143.

PMID: 37520939 PMC: 10373869. DOI: 10.3389/frobt.2023.1155143.


A systematic review of handover actions in human dyads.

Kopnarski L, Rudisch J, Voelcker-Rehage C Front Psychol. 2023; 14:1147296.

PMID: 37213382 PMC: 10192908. DOI: 10.3389/fpsyg.2023.1147296.


Handover Control for Human-Robot and Robot-Robot Collaboration.

Costanzo M, De Maria G, Natale C Front Robot AI. 2021; 8:672995.

PMID: 34026858 PMC: 8138472. DOI: 10.3389/frobt.2021.672995.


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