Evidence map›Paper›PMID 36551100›Full record

SynthesisBiosensors2022

A Systematic Review of Virtual Reality and Robot Therapy as Recent Rehabilitation Technologies Using EEG-Brain-Computer Interface Based on Movement-Related Cortical Potentials.

Ramadhan Rashid Said, Md Belal Bin Heyat, Keer Song, Chao Tian, Zhe Wu

Abstract readSystematic Review
In one paragraph

Synthesis in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
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  5. Review
  6. Review
  7. Efficacy and classification ofFrontiers in chemistry · 2024
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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.

Ramadhan Rashid SaidSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0000-0002-6211-2740
Md Belal Bin HeyatIoT Research Center, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China.ORCID 0000-0001-5307-9582
Keer SongFranklin College of Arts and Science, University of Georgia, Athens, GA 30602, USA.
Chao TianDepartment of Women's Health, Sichuan Cancer Hospital, Chengdu 610044, China.
Zhe WuSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.

Funding

National Science and Technology Ministry of China 2019YFE0196700Science & Technology Department of Sichuan Province 2022YFH0046
6 · The paper itself

Abstract

To enhance the treatment of motor function impairment, patients' brain signals for self-control as an external tool may be an extraordinarily hopeful option. For the past 10 years, researchers and clinicians in the brain-computer interface (BCI) field have been using movement-related cortical potential (MRCP) as a control signal in neurorehabilitation applications to induce plasticity by monitoring the intention of action and feedback. Here, we reviewed the research on robot therapy (RT) and virtual reality (VR)-MRCP-based BCI rehabilitation technologies as recent advancements in human healthcare. A list of 18 full-text studies suitable for qualitative review out of 322 articles published between 2000 and 2022 was identified based on inclusion and exclusion criteria. We used PRISMA guidelines for the systematic review, while the PEDro scale was used for quality evaluation. Bibliometric analysis was conducted using the VOSviewer software to identify the relationship and trends of key items. In this review, 4 studies used VR-MRCP, while 14 used RT-MRCP-based BCI neurorehabilitation approaches. The total number of subjects in all identified studies was 107, whereby 4.375 ± 6.3627 were patient subjects and 6.5455 ± 3.0855 were healthy subjects. The type of electrodes, the epoch, classifiers, and the performance information that are being used in the RT- and VR-MRCP-based BCI rehabilitation application are provided in this review. Furthermore, this review also describes the challenges facing this field, solutions, and future directions of these smart human health rehabilitation technologies. By key items relationship and trends analysis, we found that motor control, rehabilitation, and upper limb are important key items in the MRCP-based BCI field. Despite the potential of these rehabilitation technologies, there is a great scarcity of literature related to RT and VR-MRCP-based BCI. However, the information on these rehabilitation methods can be beneficial in developing RT and VR-MRCP-based BCI rehabilitation devices to induce brain plasticity and restore motor impairment. Therefore, this review will provide the basis and references of the MRCP-based BCI used in rehabilitation applications for further clinical and research development.

Indexed as

Brain-Computer InterfacesRoboticsVirtual RealityBrainElectroencephalographyHumansbiomedical signalbrain–computer interfaceelectroencephalographyhuman healthcaremachine learningneurological diseasesrobot therapyvirtual reality

Identifiers

PMID36551100
PMCPMC9776155

What OpenQuestion holds

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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.