Evidence map›Paper›PMID 37821970›Full record

ArticleJournal of neuroengineering and rehabilitation2023

A robot-based interception task to quantify upper limb impairments in proprioceptive and visual feedback after stroke.

Kayne Park, Benjamin R Ritsma, Sean P Dukelow, Stephen H Scott

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

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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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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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

4 authors.

Kayne ParkCentre for Neuroscience Studies, Queen's University, Botterell Hall, 18 Stuart St, Kingston, ON, K7L 3N6, Canada. a.kayne.park@queensu.ca.
Benjamin R RitsmaDepartment of Physical Medicine and Rehabilitation, Queen's University, Kingston, ON, Canada.
Sean P DukelowDepartment of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
Stephen H ScottCentre for Neuroscience Studies, Queen's University, Botterell Hall, 18 Stuart St, Kingston, ON, K7L 3N6, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA key motor skill is the ability to rapidly interact with our dynamic environment. Humans can generate goal-directed motor actions in response to sensory stimulus within ~ 60-200ms. This ability can be impaired after stroke, but most clinical tools lack any measures of rapid feedback processing. Reaching tasks have been used as a framework to quantify impairments in generating motor corrections for individuals with stroke. However, reaching may be inadequate as an assessment tool as repeated reaching can be fatiguing for individuals with stroke. Further, reaching requires many trials to be completed including trials with and without disturbances, and thus, exacerbate fatigue. Here, we describe a novel robotic task to quantify rapid feedback processing in healthy controls and compare this performance with individuals with stroke to (more) efficiently identify impairments in rapid feedback processing.

methodsWe assessed a cohort of healthy controls (n = 135) and individuals with stroke (n = 40; Mean 41 days from stroke) in the Fast Feedback Interception Task (FFIT) using the Kinarm Exoskeleton robot. Participants were instructed to intercept a circular white target moving towards them with their hand represented as a virtual paddle. On some trials, the arm could be physically perturbed, the target or paddle could abruptly change location, or the target could change colour requiring the individual to now avoid the target.

resultsMost participants with stroke were impaired in reaction time (85%) and end-point accuracy (83%) in at least one of the task conditions, most commonly with target or paddle shifts. Of note, this impairment was also evident in most individuals with stroke when performing the task using their unaffected arm (75%). Comparison with upper limb clinical measures identified moderate correlations with the FFIT.

conclusionThe FFIT was able to identify a high proportion of individuals with stroke as impaired in rapid feedback processing using either the affected or unaffected arms. The task allows many different types of feedback responses to be efficiently assessed in a short amount of time.

Indexed as

RoboticsStrokeStroke RehabilitationFeedback, SensoryHumansUpper ExtremityProprioceptive feedbackReaction timeRobotic exoskeletonStrokeUpper extremityVisual feedback

Identifiers

PMID37821970
PMCPMC10568927

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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.