View in EDS HTML Full Text PDF Full Text

The influence of paradigm interface guided by different visual types on MI-BCI performance.

Saved in:
Bibliographic Details
Title: The influence of paradigm interface guided by different visual types on MI-BCI performance.
Authors: Shao, Jiang, Bai, Yuxin, Yao, Jun, Zhang, Ying, Tian, Fangyuan, Xue, Chengqi
Source: Behaviour & Information Technology. Jan2025, Vol. 44 Issue 1, p120-130. 11p.
Subjects: Arm physiology, Scale analysis (Psychology), Brain-computer interfaces, Electroencephalography, Visual evoked response, Evoked potentials (Electrophysiology), Neuroplasticity, Descriptive statistics, Signal processing, Paradigms (Social sciences), Cerebral cortex, Support vector machines, Frontal lobe, Communication, Body movement, Comparative studies
Abstract: Visual paradigms of Brain-Computer Interfaces (BCI) for motor imagery (MI) tasks are the basis for communication through (electroencephalogram) EEG signals. During the MI-BCI user training process, this study analyzes and summarises four different visual paradigms and compares their impact on the outcomes of MI-BCI training. Four different visual paradigms are experimentally compared through classification outcomes and subjective evaluation. EEG features were extracted via Common Spatial Patterns (CSP) and passed to a Support Vector Machine (SVM) model for their classification. The results show that all four types of visual paradigms have a significant impact on the outcomes of MI-BCI training, with Paradigm Set II having the most significant impact. This is because paradigm set II offers a paradigm interface with relatively low visual complexity on the basis of action observation, and visual guidance with more clarity and more accurate EEG classification. [ABSTRACT FROM AUTHOR]
Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 182326294
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The influence of paradigm interface guided by different visual types on MI-BCI performance.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Shao%2C+Jiang%22">Shao, Jiang</searchLink><br /><searchLink fieldCode="AR" term="%22Bai%2C+Yuxin%22">Bai, Yuxin</searchLink><br /><searchLink fieldCode="AR" term="%22Yao%2C+Jun%22">Yao, Jun</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Ying%22">Zhang, Ying</searchLink><br /><searchLink fieldCode="AR" term="%22Tian%2C+Fangyuan%22">Tian, Fangyuan</searchLink><br /><searchLink fieldCode="AR" term="%22Xue%2C+Chengqi%22">Xue, Chengqi</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Behaviour+%26+Information+Technology%22">Behaviour & Information Technology</searchLink>. Jan2025, Vol. 44 Issue 1, p120-130. 11p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Arm+physiology%22">Arm physiology</searchLink><br /><searchLink fieldCode="DE" term="%22Scale+analysis+%28Psychology%29%22">Scale analysis (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Brain-computer+interfaces%22">Brain-computer interfaces</searchLink><br /><searchLink fieldCode="DE" term="%22Electroencephalography%22">Electroencephalography</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+evoked+response%22">Visual evoked response</searchLink><br /><searchLink fieldCode="DE" term="%22Evoked+potentials+%28Electrophysiology%29%22">Evoked potentials (Electrophysiology)</searchLink><br /><searchLink fieldCode="DE" term="%22Neuroplasticity%22">Neuroplasticity</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Paradigms+%28Social+sciences%29%22">Paradigms (Social sciences)</searchLink><br /><searchLink fieldCode="DE" term="%22Cerebral+cortex%22">Cerebral cortex</searchLink><br /><searchLink fieldCode="DE" term="%22Support+vector+machines%22">Support vector machines</searchLink><br /><searchLink fieldCode="DE" term="%22Frontal+lobe%22">Frontal lobe</searchLink><br /><searchLink fieldCode="DE" term="%22Communication%22">Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Body+movement%22">Body movement</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+studies%22">Comparative studies</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Visual paradigms of Brain-Computer Interfaces (BCI) for motor imagery (MI) tasks are the basis for communication through (electroencephalogram) EEG signals. During the MI-BCI user training process, this study analyzes and summarises four different visual paradigms and compares their impact on the outcomes of MI-BCI training. Four different visual paradigms are experimentally compared through classification outcomes and subjective evaluation. EEG features were extracted via Common Spatial Patterns (CSP) and passed to a Support Vector Machine (SVM) model for their classification. The results show that all four types of visual paradigms have a significant impact on the outcomes of MI-BCI training, with Paradigm Set II having the most significant impact. This is because paradigm set II offers a paradigm interface with relatively low visual complexity on the basis of action observation, and visual guidance with more clarity and more accurate EEG classification. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=182326294
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/0144929X.2024.2312436
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 120
    Subjects:
      – SubjectFull: Arm physiology
        Type: general
      – SubjectFull: Scale analysis (Psychology)
        Type: general
      – SubjectFull: Brain-computer interfaces
        Type: general
      – SubjectFull: Electroencephalography
        Type: general
      – SubjectFull: Visual evoked response
        Type: general
      – SubjectFull: Evoked potentials (Electrophysiology)
        Type: general
      – SubjectFull: Neuroplasticity
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Signal processing
        Type: general
      – SubjectFull: Paradigms (Social sciences)
        Type: general
      – SubjectFull: Cerebral cortex
        Type: general
      – SubjectFull: Support vector machines
        Type: general
      – SubjectFull: Frontal lobe
        Type: general
      – SubjectFull: Communication
        Type: general
      – SubjectFull: Body movement
        Type: general
      – SubjectFull: Comparative studies
        Type: general
    Titles:
      – TitleFull: The influence of paradigm interface guided by different visual types on MI-BCI performance.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Shao, Jiang
      – PersonEntity:
          Name:
            NameFull: Bai, Yuxin
      – PersonEntity:
          Name:
            NameFull: Yao, Jun
      – PersonEntity:
          Name:
            NameFull: Zhang, Ying
      – PersonEntity:
          Name:
            NameFull: Tian, Fangyuan
      – PersonEntity:
          Name:
            NameFull: Xue, Chengqi
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Text: Jan2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 0144929X
          Numbering:
            – Type: volume
              Value: 44
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Behaviour & Information Technology
              Type: main
ResultId 1