Evidence map›Paper›PMID 40181338›Full record

SynthesisJournal of neuroengineering and rehabilitation2025

Can motion capture improve task-based fMRI studies of motor function post-stroke? A systematic review.

Zakaria Belkacemi, Liesjet E H van Dokkum, Andon Tchechmedjiev, Matthieu Lepetit-Coiffe, Denis Mottet, Emmanuelle Le Bars

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of neuroengineering and rehabilitation, 2025. 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.

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

Zakaria BelkacemiSiemens Healthcare SAS, Courbevoie, France. zakaria.belkacemi@etu.umontpellier.fr.ORCID 0000-0003-0968-8406
Liesjet E H van DokkumMontpellier University Hospital, Montpellier, France.
Andon TchechmedjievEuromov Digital Health in Motion, University of Montpellier, IMT Mines Alès, Montpellier, France.
Matthieu Lepetit-CoiffeSiemens Healthcare SAS, Courbevoie, France.
Denis MottetEuromov Digital Health in Motion, University of Montpellier, IMT Mines Alès, Montpellier, France.
Emmanuelle Le BarsMontpellier University Hospital, Montpellier, France.

Funding

LabEx NUMEV within the I-SITE MUSE ANR-10-LABX-0020Occitanie Region, Regional Research and Innovation Platform 20020194
6 · The paper itself

Abstract

backgroundVariability in motor recovery after stroke represents a major challenge in its understanding and management. While functional MRI has been used to unravel interactions between stroke motor function and clinical outcome, fMRI alone cannot clarify any relation between brain activation and movement characteristics.

objectivesWe aimed to identify fMRI and kinematic coupling approaches and to evaluate their potential contribution to the understanding of motor function post-stroke.

methodA systematic literature review was performed according to PRISMA guidelines on studies using fMRI and kinematics in post-stroke individuals. We assessed the internal, external, statistical, and technological validity of each study. Data extraction included study design and analysis procedures used to couple brain activity with movement characteristics.

resultsOf the 404 studies found, 23 were included in the final review. The overall study quality was moderate (0.6/1). Thirteen studies used kinematic information either parallel to the fMRI results, or as a real-time input to external devices, for instance to provide feedback to the patient. Ten studies performed a statistical analysis between movement and brain activity by either using kinematics as variables during group or individual level regression or correlation. This permitted establishing links between movement characteristics and brain activity, unraveling cortico-kinematic relationships. For instance, increased activity in the ipsilesional Premotor Cortex was related to less smooth movements, whereas trunk compensation was expressed by increased activity in the contralesional Primary Motor Cortex.

conclusionOur review suggests that the coupling of fMRI and kinematics may provide valuable insight into cortico-kinematic relationships. The optimization and standardization of both data measurement and treatment procedures may help the field to move forward and to fully use the potential of multimodal cortico-kinematic integration to unravel the complexity of post-stroke motor function and recovery.

Indexed as

BrainMagnetic Resonance ImagingStrokeStroke RehabilitationBiomechanical PhenomenaHumansMotion CaptureMovementRecovery of FunctionfMRIKinematicsMotion captureMotor functionMultimodalNeuroimagingReviewStroke

Identifiers

PMID40181338
PMCPMC11966795

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.