Evidence map›Paper›PMID 35992731›Full record

ArticleIEEE robotics and automation letters2022

Dynamic Primitives Limit Human Force Regulation during Motion.

A Michael West, James Hermus, Meghan E Huber, Pauline Maurice, Dagmar Sternad, Neville Hogan

Abstract read
In one paragraph

Article in IEEE robotics and automation letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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  6. Article
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.

A Michael WestDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.
James HermusDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.
Meghan E HuberDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003 USA.
Pauline MauriceUniversité de Lorraine, CNRS, Inria, LORIA, 54000 Nancy, France.
Dagmar SternadDepartments of Biology, Electrical and Computer Engineering, and Physics, and the Institute of Experiential Robotics, Northeastern University, Boston, MA 02115.
Neville HoganDepartments of Mechanical Engineering and Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139.

Funding

Predictability in complex object controlR37HD087089 · NICHD · NORTHEASTERN UNIVERSITY · PI Dagmar Sternad · 2022 to 2026
$3.0M
CRCNS Research Proposal: Collaborative Research: Neural Basis of Motor ExpertiseR01NS120579 · NINDS · NORTHEASTERN UNIVERSITY · PI BATISTA, AARON PAUL, STERNAD, DAGMAR · 2020 to 2025
$2.0M
Predictability in Complex Object ControlR01HD087089 · NICHD · NORTHEASTERN UNIVERSITY · PI STERNAD, DAGMAR · 2015 to 2020
$1.8M
NICHD NIH HHS R01 HD087089NICHD NIH HHS R37 HD087089NINDS NIH HHS R01 NS120579
6 · The paper itself

Abstract

Humans excel at physical interaction despite long feedback delays and low-bandwidth actuators. Yet little is known about how humans manage physical interaction. A quantitative understanding of how they do is critical for designing machines that can safely and effectively interact with humans, e.g. amputation prostheses, assistive exoskeletons, therapeutic rehabilitation robots, and physical human-robot collaboration. To facilitate applications, this understanding should be in the form of a simple mathematical model that not only describes humans' capabilities but also their limitations. In robotics, hybrid control allows simultaneous, independent control of both motion and force and it is often assumed that humans can modulate force independent of motion as well. This paper experimentally tested that assumption. Participants were asked to apply a constant 5N force on a robot manipulandum that moved along an elliptical path. After initial improvement, force errors quickly plateaued, despite practice and visual feedback. Within-trial analyses revealed that force errors varied with position on the ellipse, rejecting the hypothesis that humans have independent control of force and motion. The findings are consistent with a feed-forward motion command composed of two primitive oscillations acting through mechanical impedance to evoke force.

Indexed as

Compliance and Impedance ControlForce ControlPhysical Human-Robot Interaction

Identifiers

PMID35992731
PMCPMC9390969

What OpenQuestion holds

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Registered trials

None linked

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.