Evidence map›Paper›PMID 33707935›Full record

ArticleConference proceedings. IEEE International Conference on Systems, Man, and Cybernetics2020

Technology Integration Methods for Bi-directional Brain-computer Interfaces and XR-based Interventions.

Kei Landin, Moaad Benjaber, Fawad Jamshed, Charlotte Stagg, Timothy Denison

Abstract read
In one paragraph

Article in Conference proceedings. IEEE International Conference on Systems, Man, and Cybernetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Kei LandinMRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
Moaad BenjaberMRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
Fawad JamshedMRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
Charlotte StaggWellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
Timothy DenisonMRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.

Funding

Medical Research Council MC_UU_00003/3Wellcome Trust 102584
6 · The paper itself

Abstract

Brain stimulation therapies have been established as effective treatments for Parkinson's disease, essential tremor, and epilepsy, as well as having high diagnostic and therapeutic potential in a wide range of neurological and psychiatric conditions. Novel interventions such as extended reality (XR), video games and exergames that can improve physiological and cognitive functioning are also emerging as targets for therapeutic and rehabilitative treatments. Previous studies have proposed specific applications involving non-invasive brain stimulation (NIBS) and virtual environments, but to date these have been uni-directional and restricted to specific applications or proprietary hardware. Here, we describe technology integration methods that enable invasive and non-invasive brain stimulation devices to interface with a cross-platform game engine and development platform for creating bi-directional brain-computer interfaces (BCI) and XR-based interventions. Furthermore, we present a highly-modifiable software framework and methods for integrating deep brain stimulation (DBS) in 2D, 3D, virtual and mixed reality applications, as well as extensible applications for BCI integration in wireless systems. The source code and integrated brain stimulation applications are available online at https://github.com/oxfordbioelectronics/brain-stim-game.

Indexed as

brain-computer interfacesDBStimDyNeuMoMRneurorehabilitationSummit RC+Svirtual realityXR

Identifiers

PMID33707935
PMCPMC7116886

What OpenQuestion holds

Textmetadata
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.