Evidence map›Paper›PMID 38177151›Full record

ArticleScientific data2024

Multi-frequency steady-state visual evoked potential dataset.

Jing Mu, Shuo Liu, Anthony N Burkitt, David B Grayden

Abstract readDataset
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. [Performance evaluation of a wearable steady-state visual evoked potential based brain-computer interface in real-life scenario].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. 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.

Jing MuDepartment of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia. jing.mu@unimelb.edu.au.ORCID 0000-0002-3289-2002
Shuo LiuDepartment of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia.ORCID 0009-0008-6671-0140
Anthony N BurkittDepartment of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia.ORCID 0000-0001-5672-2772
David B GraydenDepartment of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia.ORCID 0000-0002-5497-7234

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Steady-State Visual Evoked Potential (SSVEP) is a widely used modality in Brain-Computer Interfaces (BCIs). Existing research has demonstrated the capabilities of SSVEP that use single frequencies for each target in various applications with relatively small numbers of commands required in the BCI. Multi-frequency SSVEP has been developed to extend the capability of single-frequency SSVEP to tasks that involve large numbers of commands. However, the development on multi-frequency SSVEP methodologies is falling behind compared to the number of studies with single-frequency SSVEP. This dataset was constructed to promote research in multi-frequency SSVEP by making SSVEP signals collected with different frequency stimulation settings publicly available. In this dataset, SSVEPs were collected from 35 participants using single-, dual-, and tri-frequency stimulation and with three different multi-frequency stimulation variants.

Indexed as

Brain-Computer InterfacesEvoked Potentials, VisualAlgorithmsHumans

Identifiers

PMID38177151
PMCPMC10766626

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.