Evidence map›Paper›PMID 36905004›Full record

SynthesisSensors (Basel, Switzerland)2023

EEG-Based BCIs on Motor Imagery Paradigm Using Wearable Technologies: A Systematic Review.

Aurora Saibene, Mirko Caglioni, Silvia Corchs, Francesca Gasparini

Full text readSystematic Review
In one paragraph

Synthesis in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 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

29 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Wrinkle-Adaptive Kirigami Wearables With Anisotropic Deformability for Sleep EEG Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. [Technical maturity and bubble risks of brain-computer interface (BCI): Considerations from research to industrial translation].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
    Article
  20. 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

4 authors.

Aurora SaibeneDepartment of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy.ORCID 0000-0002-4405-8234
Mirko CaglioniDepartment of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy.
Silvia CorchsNeuroMI, Milan Center for Neuroscience, Piazza dell'Ateneo Nuovo 1, 20126 Milano, Italy.ORCID 0000-0002-1739-8110
Francesca GaspariniDepartment of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy.ORCID 0000-0002-6279-6660

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent decades, the automatic recognition and interpretation of brain waves acquired by electroencephalographic (EEG) technologies have undergone remarkable growth, leading to a consequent rapid development of brain-computer interfaces (BCIs). EEG-based BCIs are non-invasive systems that allow communication between a human being and an external device interpreting brain activity directly. Thanks to the advances in neurotechnologies, and especially in the field of wearable devices, BCIs are now also employed outside medical and clinical applications. Within this context, this paper proposes a systematic review of EEG-based BCIs, focusing on one of the most promising paradigms based on motor imagery (MI) and limiting the analysis to applications that adopt wearable devices. This review aims to evaluate the maturity levels of these systems, both from the technological and computational points of view. The selection of papers has been performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), leading to 84 publications considered in the last ten years (from 2012 to 2022). Besides technological and computational aspects, this review also aims to systematically list experimental paradigms and available datasets in order to identify benchmarks and guidelines for the development of new applications and computational models.

Indexed as

Brain-Computer InterfacesBrain WavesWearable Electronic DevicesElectroencephalographyHumansImagery, Psychotherapybrain–computer interface (BCI)electroencephalogram (EEG)motor imagery (MI)wearable devices

Identifiers

PMID36905004
PMCPMC10007053

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read9
measurements read33
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.