Evidence map›Paper›PMID 30691482›Full record

ArticleJournal of neuroengineering and rehabilitation2019

A postural unloading task to assess fast corrective responses in the upper limb following stroke.

Catherine R Lowrey, Teige C Bourke, Stephen D Bagg, Sean P Dukelow, Stephen H Scott

Open access · goldAbstract 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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
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

7 citing papers in PubMed, 17 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Catherine R LowreyLaboratory of Integrative Motor Behaviour, Centre for Neuroscience Studies, Queen's University, 18 Stuart St, Kingston, ON, K7L 3N6, Canada. lowrey@queensu.ca.ORCID 0000-0002-8379-9924
Teige C BourkeLaboratory of Integrative Motor Behaviour, Centre for Neuroscience Studies, Queen's University, 18 Stuart St, Kingston, ON, K7L 3N6, Canada.
Stephen D BaggDepartment of Physical Medicine and Rehabilitation, Queen's University, Kingston, ON, Canada.
Sean P DukelowHotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
Stephen H ScottLaboratory of Integrative Motor Behaviour, Centre for Neuroscience Studies, Queen's University, 18 Stuart St, Kingston, ON, K7L 3N6, Canada.
Queen's University · CAUniversity of Calgary · CA

Funding

CIHR 201411MFECIHR MOP 106662Ontario Research Foundation RE-04-047
6 · The paper itself

Abstract

backgroundRobotic technologies to measure human behavior are emerging as a new approach to assess brain function. Recently, we developed a robot-based postural Load Task to assess corrective responses to mechanical disturbances to the arm and found impairments in many participants with stroke compared to a healthy cohort (Bourke et al, J NeuroEngineering Rehabil 12: 7, 2015). However, a striking feature was the large range and skewed distribution of healthy performance. This likely reflects the use of different strategies across the healthy control sample, making it difficult to identify impairments. Here, we developed an intuitive "Unload Task". We hypothesized this task would reduce healthy performance variability and improve the detection of impairment following stroke.

methodsPerformance on the Load and Unload Task in the KINARM exoskeleton robot was directly compared for healthy control (n = 107) and stroke (n = 31) participants. The goal was to keep a cursor representing the hand inside a virtual target and return "quickly and accurately" if the robot applied (or removed) an unexpected load to the arm (0.5-1.5 Nm). Several kinematic parameters quantified performance. Impairment was defined as performance outside the 95% of controls (corrected for age, sex and handedness). Task Scores were calculated using standardized parameter scores reflecting overall task performance.

resultsThe distribution of healthy control performance was smaller and less skewed for the Unload Task compared to the Load Task. Fewer task outliers (outside 99.9 percentile for controls) were removed from the Unload Task (3.7%) compared to the Load Task (7.4%) when developing normative models of performance. Critically, more participants with stroke failed the Unload Task based on Task Score with their affected arm (68%) compared to the Load Task (23%). More impairments were found at the parameter level for the Unload (median = 52%) compared to Load Task (median = 29%).

conclusionsThe Unload Task provides an improved approach to assess fast corrective responses of the arm. We found that corrective responses are impaired in persons living with stroke, often equally in both arms. Impairments in generating rapid motor corrections may place individuals at greater risk of falls when they move and interact in the environment.

Indexed as

Exoskeleton DeviceAdultAlgorithmsArmBiomechanical PhenomenaCohort StudiesFemaleHumansMaleMiddle AgedStrokeStroke RehabilitationExoskeletonProprioceptionRoboticsStrokeUpper limb

Identifiers

PMID30691482
PMCPMC6350318
OpenAlexW2911530918

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.