Evidence map›Paper›PMID 36455078›Full record

ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2023

Novel Platform for Quantitative Assessment of Functional Object Interactions After Stroke.

Rashida Nayeem, Won Joon Sohn, Julie A DiCarlo, Perman Gochyyev, David J Lin, Dagmar Sternad

Abstract read
In one paragraph

Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

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

  1. Pooled it
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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.

Rashida Nayeem
Won Joon Sohn
Julie A DiCarlo
Perman Gochyyev
David J Lin
Dagmar Sternad

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

Many persons with stroke exhibit upper extremity motor impairments. These impairments often lead to dysfunction and affect performance in activities of daily living, where successful manipulation of objects is essential. Hence, understanding how upper extremity motor deficits manifest in functional interactions with objects is critical for rehabilitation. However, quantifying skill in these tasks has been a challenge. Traditional rehabilitation assessments require highly trained clinicians, are time-consuming, and yield subjective scores. This paper introduces a custom-designed device, the "MAGIC Table", that can record real-time kinematics of persons with stroke during interaction with objects, specifically a 'cup of coffee'. The task and its quantitative assessments were derived from previous basic-science studies. Six participants after stroke and six able-bodied participants moved a 3D-printed cup with a rolling ball inside, representing sloshing coffee, with 3 levels of difficulty. Movements were captured via a high-resolution camera above the table. Conventional kinematic metrics (movement time and smoothness) and novel kinematic metrics accounting for object interaction (risk and predictability) evaluated performance. Expectedly, persons with stroke moved more slowly and less smoothly than able-bodied participants, in both simple reaches and during transport of the cup-and-ball system. However, the more sensitive metric was mutual information, which captured the predictability of interactions, essential in cup transport as shown in previous theoretical research. Predictability sensitively measured differences in performance with increasing levels of difficulty. It also showed the best intraclass consistency, promising sensitive differentiation between different levels of impairment. This study highlights the feasibility of this new device and indicates that examining dynamic object interaction may provide valuable insights into upper extremity function after stroke useful for assessment and rehabilitation.

Indexed as

StrokeStroke RehabilitationActivities of Daily LivingBiomechanical PhenomenaHumansUpper Extremity

Identifiers

PMID36455078
PMCPMC10079607

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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.