Evidence map›Paper›PMID 37300318›Full record

ArticleNeurorehabilitation and neural repair2023

Measuring Arm and Hand Joint Kinematics to Estimate Impairment During a Functional Reach and Grasp Task after Stroke.

Preeya Khanna, Tomas Oppenheim, Adelyn Tu-Chan, Gary Abrams, Karunesh Ganguly

Abstract read
In one paragraph

Article in Neurorehabilitation and neural repair, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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.

Preeya KhannaDepartment of Neurology, University of California, San Francisco, CA, USA.
Tomas OppenheimDepartment of Mechanical Engineering, California Maritime Academy, Vallejo, CA, USA.
Adelyn Tu-ChanDepartment of Neurology, University of California, San Francisco, CA, USA.
Gary AbramsDepartment of Neurology, University of California, San Francisco, CA, USA.ORCID 0000-0001-5377-0373
Karunesh GangulyDepartment of Neurology, University of California, San Francisco, CA, USA.ORCID 0000-0002-2570-9943

Funding

Optimizing peripheral stimulation parameters to modulate the sensorimotor cortex for post-stroke motor recoveryR01MH111871 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GANGULY, KARUNESH · 2016 to 2019
$2.0M
Neural dynamics of somatosensory guidance of dexterous movement in intact and stroke-injured networksK99NS124748 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KHANNA, PREEYA · 2021 to 2022
$222k
NIMH NIH HHS R01 MH111871NINDS NIH HHS K99 NS124748
6 · The paper itself

Abstract

backgroundCurrent approaches to characterizing deficits in upper limb movements after stroke typically focus either on changes in a functional measure, for example, how well a patient can complete a task, or changes in impairment, for example, isolated measurements of joint range of motion. However, there can be notable dissociations between static measures of impairment versus those of function.

objectiveWe develop a method to measure upper limb joint angles during performance of a functional task and use measurements to characterize joint impairment in the context of a functional task.

methodsWe developed a sensorized glove that can precisely measure select finger, hand, and arm joints while participants complete a functional reach-to-grasp task involving manipulation of a sensorized object.

resultsWe first characterized the accuracy and precision of the glove's joint angle measurements. We then measured joint angles in neurologically intact participants (n = 4 participants, 8 limbs) to define the expected distribution of joint angle variation during task execution. These distributions were used to normalize finger, hand, and arm joint angles in stroke participants (n = 6) as they performed the task. We present a participant-specific visualization of functional joint angle variance which illustrated that stroke participants with nearly identical clinical scores exhibited unique patterns of joint angle variation.

conclusionsOverall, measuring individual joint angles in the context of a functional task may inform whether changes in functional scores over recovery or rehabilitation are driven by changes in impairment or the development of compensatory strategies, and provide a quantified path toward personalized rehabilitative therapy.

Indexed as

Hand JointsStrokeStroke RehabilitationArmBiomechanical PhenomenaHand StrengthHumansMovementUpper Extremitykinematicsmovementstroke rehabilitationupper extremity

Identifiers

PMID37300318
PMCPMC10330436

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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.