Evidence map›Paper›PMID 36501860›Full record

ArticleSensors (Basel, Switzerland)2022

Classification Strategies for P300-Based BCI-Spellers Adopting the Row Column Paradigm.

Sofien Gannouni, Kais Belwafi, Nourah Alangari, Hatim AboAlsamh, Abdelfettah Belghith

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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.

Sofien GannouniDepartment of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.ORCID 0000-0002-6026-4257
Kais BelwafiDepartment of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.ORCID 0000-0003-1455-439X
Nourah AlangariDepartment of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.
Hatim AboAlsamhDepartment of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.ORCID 0000-0002-8000-5105
Abdelfettah BelghithDepartment of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.ORCID 0000-0002-4937-7453

Funding

National Plan for Science, Technology and Innovation (MAARIFAH), King Abdulaziz City for Science and Technology 14-INF3139-02
6 · The paper itself

Abstract

Acknowledging the importance of the ability to communicate with other people, the researcher community has developed a series of BCI-spellers, with the goal of regaining communication and interaction capabilities with the environment for people with disabilities. In order to bridge the gap in the digital divide between the disabled and the non-disabled people, we believe that the development of efficient signal processing algorithms and strategies will go a long way towards achieving novel assistive technologies using new human-computer interfaces. In this paper, we present various classification strategies that would be adopted by P300 spellers adopting the row/column paradigm. The presented strategies have obtained high accuracy rates compared with existent similar research works.

Indexed as

Brain-Computer InterfacesElectroencephalographyEvent-Related Potentials, P300HumansSignal Processing, Computer-AssistedUser-Computer Interfacebrain–computer interfaceensemble classifiersn-class classificationP300 row/column paradigmP300 spellers

Identifiers

PMID36501860
PMCPMC9738959

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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.