Evidence map›Paper›PMID 40844828›Full record

ArticleJMIR research protocols2025

Platform Technology for Extended Reality Biofeedback Training Under Operant Conditioning for Functional Limb Weakness: Protocol for the Coproduction of an at-Home Solution (React2Home).

Anirban Dutta, Abhijit Das

Abstract read
In one paragraph

Article in JMIR research protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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

5 citing papers in PubMed.

  1. Unmet needs in functional neurological disorder related to digital healthcare.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026
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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

2 authors.

Anirban DuttaCentre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom.ORCID 0000-0002-7298-9773
Abhijit DasLancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom.ORCID 0000-0001-8800-8047

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFunctional neurological disorder (FND), including functional movement disorders (FMDs), arises from disruptions in the perception-action cycle, where maladaptive cognitive learning processes reduce the sense of agency and motor control. FND significantly impacts quality of life, with patients often experiencing physical disability and psychological distress. Extended reality (XR) technologies present a novel therapeutic opportunity by leveraging biofeedback training to target sensory attenuation and amplification mechanisms, aiming to restore motor function and the sense of agency.

objectiveThis study aims to coproduce and evaluate the usability of an XR technology platform for FND rehabilitation, focusing on functional limb weakness. The platform integrates biofeedback training with haptic and visual feedback to support motor relearning and control.

methodsWe propose to use an experience-based co-design framework to engage patients with FND, caregivers, and health care professionals in collaboratively designing the XR platform. Stakeholders can share their experiences through narrative interviews and co-design workshops, which can identify emotional touchpoints and prioritized patient-centered needs. Insights will be synthesized through qualitative analysis and used to guide the development of system requirements via quality function deployment, ensuring that the platform aligns with user needs. XR training tasks-virtual reality relaxation, XR position feedback, and XR force feedback-will be integrated as needed into a unified therapeutic game experience through 4-week Agile sprints. Usability will be assessed using the System Usability Scale and qualitative feedback, with themes analyzed in NVivo to identify key areas for subsequent improvement.

resultsHigh usability scores (>85) were recorded for the XR position feedback tasks in the predesign study, reflecting excellent usability and participant satisfaction. However, the virtual reality relaxation and XR force feedback tasks exhibited interindividual variability, underscoring the need for personalization. Key themes included customization, comfort, accessibility, and XR technological quality, ensuring that the XR platform effectively addressed diverse patient needs. The predesign study highlighted the potential of XR technology for FMD rehabilitation by integrating biofeedback training into a patient-centered game design framework. Approaches such as experience-based co-design and quality function deployment can support coproduction by systematically addressing usability and accessibility challenges. Brain-based metrics may further strengthen this evaluation. Accordingly, this study will use portable brain imaging to capture dynamic functional connectivity in key brain regions, enabling personalized interventions.

conclusionsThrough coproduction and iterative refinement, this study aims to demonstrate the promise of personalized XR gaming technology as a scalable, at-home solution for FMD rehabilitation. In this context, personalization and accessibility are critical for optimizing usability and long-term clinical outcomes, paving the way for at-home implementation within the FND stepped care model. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/70620.

Indexed as

Biofeedback, PsychologyConditioning, OperantMovement DisordersHumansQuality of LifeVirtual RealityAIartificial intelligencebiofeedback trainingcoproductionEBCDexperience-based co-designextended realityfunctional movement disorderfunctional neurological disorderQFDquality function deploymentrehabilitation

Identifiers

PMID40844828
PMCPMC12413572

What OpenQuestion holds

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LicenceCC BY
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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.