Evidence map›Paper›PMID 39355516›Full record

ArticleBrain computer interfaces (Abingdon, England)2024

Large scale investigation of the effect of gender on mu rhythm suppression in motor imagery brain-computer interfaces.

Valentina Gamboa von Groll, Nikki Leeuwis, Sébastien Rimbert, Aline Roc, Léa Pillette, Fabien Lotte, Maryam Alimardani

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Article in Brain computer interfaces (Abingdon, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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0cells of the map it votes in
6citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Valentina Gamboa von GrollDepartment of Cognitive Science and AI, Tilburg University, Tilburg, Netherlands.
Nikki LeeuwisDepartment of Cognitive Science and AI, Tilburg University, Tilburg, Netherlands.
Sébastien RimbertInria Center at the University of Bordeaux / LaBRI, Talence, France.
Aline RocInria Center at the University of Bordeaux / LaBRI, Talence, France.
Léa PilletteDepartment of Virtual Reality, Virtual Humans, Interactions and Robotics, University of Rennes, Inria, CNRS, France.
Fabien LotteInria Center at the University of Bordeaux / LaBRI, Talence, France.
Maryam AlimardaniDepartment of Cognitive Science and AI, Tilburg University, Tilburg, Netherlands.ORCID https://orcid.org/0000-0003-3077-7657

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The utmost issue in Motor Imagery Brain-Computer Interfaces (MI-BCI) is the BCI poor performance known as 'BCI inefficiency'. Although past research has attempted to find a solution by investigating factors influencing users' MI-BCI performance, the issue persists. One of the factors that has been studied in relation to MI-BCI performance is gender. Research regarding the influence of gender on a user's ability to control MI-BCIs remains inconclusive, mainly due to the small sample size and unbalanced gender distribution in past studies. To address these issues and obtain reliable results, this study combined four MI-BCI datasets into one large dataset with 248 subjects and equal gender distribution. The datasets included EEG signals from healthy subjects from both gender groups who had executed a right- vs. left-hand motor imagery task following the Graz protocol. The analysis consisted of extracting the Mu Suppression Index from C3 and C4 electrodes and comparing the values between female and male participants. Unlike some of the previous findings which reported an advantage for female BCI users in modulating mu rhythm activity, our results did not show any significant difference between the Mu Suppression Index of both groups, indicating that gender may not be a predictive factor for BCI performance.

Indexed as

BCI inefficiencyBrain-computer interface (BCI)gendermotor imagery (MI)mu suppression

Identifiers

PMID39355516
PMCPMC11441392

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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.