Evidence map›Paper›PMID 31729840›Full record

ArticleBrain and behavior2019

Happy emotion cognition of bimodal audiovisual stimuli optimizes the performance of the P300 speller.

Zhaohua Lu, Qi Li, Ning Gao, Jingjing Yang, Ou Bai

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Article in Brain and behavior, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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10citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Acoustic and Subjective Basis of Emotional Perception in Comatose Patients: A Comparative Study.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2023
    Article
  4. [A design and evaluation of wearable p300 brain-computer interface system based on Hololens2].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zhaohua LuSchool of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China.
Qi LiSchool of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China.ORCID 0000-0002-2716-449X
Ning GaoSchool of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China.
Jingjing YangSchool of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China.
Ou BaiDepartment of Electrical and Computer Engineering, Florida International University, Miami, FL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePrior studies of emotional cognition have found that emotion-based bimodal face and voice stimuli can elicit larger event-related potential (ERP) amplitudes and enhance neural responses compared with visual-only emotional face stimuli. Recent studies on brain-computer interface have shown that emotional face stimuli have significantly improved the performance of the traditional P300 speller system, but its performance needs to be further improved for practical applications. Therefore, we herein propose a novel audiovisual P300 speller based on bimodal emotional cognition to further improve the performance of the P300 system.

methodsThe audiovisual P300 speller we proposed is based on happy emotions, with visual and auditory stimuli that consist of several pairs of smiling faces and audible chuckles (E-AV spelling paradigm) of different ages and sexes. The control paradigm was the visual-only emotional face P300 speller (E-V spelling paradigm).

resultsWe compared the ERP amplitudes, accuracy, and raw bit rate between the E-AV and E-V spelling paradigms. The target stimuli elicited significantly increased P300 amplitudes (p < .05) and P600 amplitudes (p < .05) in the E-AV spelling paradigm compared with those in the E-V paradigm. The E-AV spelling paradigm also significantly improved the spelling accuracy and the raw bit rate compared with those in the E-V paradigm at one superposition (p < .05) and at two superpositions (p < .05). SIGNIFICANCE: The proposed emotion-based audiovisual spelling paradigm not only significantly improves the performance of the P300 speller, but also provides a basis for the development of various bimodal P300 speller systems, which is a step forward in the clinical application of brain-computer interfaces.

Indexed as

Brain-Computer InterfacesHappinessAcoustic StimulationAdultCognitionElectroencephalographyEmotionsEvent-Related Potentials, P300HumansMaleMental ProcessesPhotic Stimulationaudiovisualbrain-computer interfaceemotional cognitionfaceP300 spellervoice

Identifiers

PMID31729840
PMCPMC6908870

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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.