Evidence map›Paper›PMID 31248426›Full record

ArticleJournal of neuroengineering and rehabilitation2019

Coordination of reach-to-grasp in physical and haptic-free virtual environments.

Mariusz P Furmanek, Luis F Schettino, Mathew Yarossi, Sofia Kirkman, Sergei V Adamovich, Eugene Tunik

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

17 citing papers in PubMed.

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  7. Involvement of aSPOC in the Online Updating of Reach-to-Grasp to Mechanical Perturbations of Hand Transport.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  8. CKATool: A clinical kinematic analysis toolbox for upper limb rehabilitation.Computational and structural biotechnology journal · 2025
    Article
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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

6 authors.

Mariusz P FurmanekDepartment of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, USA. m.furmanek@northeastern.edu.ORCID 0000-0002-8797-1154
Luis F SchettinoPsychology Department, Lafayette College, Easton, PA, 18042, USA.
Mathew YarossiDepartment of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, USA.
Sofia KirkmanDepartment of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, USA.
Sergei V AdamovichDepartment of Biomedical Engineering, NJIT, 323 Dr. Martin Luther King Jr. Boulevard, Newark, NJ, 07102, USA.
Eugene TunikDepartment of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, USA.

Funding

Optimizing Hand Rehabilitation Post-Stroke Using Interactive Virtual EnvironmentsR01HD058301 · NICHD · NEW JERSEY INSTITUTE OF TECHNOLOGY · PI ADAMOVICH, SERGEI V, MERIANS, ALMA S · 2009 to 2021
$4.7M
Planning and Updating in Frontoparietal Networks for GraspingR01NS085122 · NINDS · RBHS-SCHOOL/ HEALTH RELATED PROFESSIONS · PI ADAMOVICH, SERGEI V, TUNIK, EUGENE · 2014 to 2025
$3.2M
ACL HHS 90RE5021NICHD NIH HHS R01 HD058301NIH HHS R01HD53801NINDS NIH HHS R01 NS085122
6 · The paper itself

Abstract

backgroundVirtual reality (VR) offers unprecedented opportunity as a scientific tool to study visuomotor interactions, training, and rehabilitation applications. However, it remains unclear if haptic-free hand-object interactions in a virtual environment (VE) may differ from those performed in the physical environment (PE). We therefore sought to establish if the coordination structure between the transport and grasp components remain similar whether a reach-to-grasp movement is performed in PE and VE.

methodReach-to-grasp kinematics were examined in 13 healthy right-handed young adults. Subjects were instructed to reach-to-grasp-to-lift three differently sized rectangular objects located at three different distances from the starting position. Object size and location were matched between the two environments. Contact with the virtual objects was based on a custom collision detection algorithm. Differences between the environments were evaluated by comparing movement kinematics of the transport and grasp components.

resultsCorrelation coefficients, and the slope of the regression lines, between the reach and grasp components were similar for the two environments. Likewise, the kinematic profiles of the transport velocity and grasp aperture were strongly correlated across the two environments. A rmANOVA further identified some similarities and differences in the movement kinematics between the two environments - most prominently that the closure phase of reach-to-grasp movement was prolonged when movements were performed in VE.

conclusionsReach-to-grasp movement patterns performed in a VE showed both similarities and specific differences compared to those performed in PE. Additionally, we demonstrate a novel approach for parsing the reach-to-grasp movement into three phases- initiation, shaping, closure- based on established kinematic variables, and demonstrate that the differences in performance between the environments are attributed to the closure phase. We discuss this in the context of how collision detection parameters may modify hand-object interactions in VE. Our study shows that haptic-free VE may be a useful platform to study reach-to-grasp movements, with potential implications for haptic-free VR in neurorehabilitation.

Indexed as

Virtual RealityBiomechanical PhenomenaFemaleHand StrengthHumansMalePsychomotor PerformanceYoung AdultCollision detectionKinematicsPrehensionReach-to-grasp phasesVirtual reality

Identifiers

PMID31248426
PMCPMC6598288

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LicenceCC BY
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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.