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Brain–Computer Interface Based on Steady-State Visual Evoked Potential Using Quick-Response Code Pattern for Wheelchair Control.

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Název: Brain–Computer Interface Based on Steady-State Visual Evoked Potential Using Quick-Response Code Pattern for Wheelchair Control.
Autoři: Siribunyaphat, Nannaphat, Punsawad, Yunyong
Zdroj: Sensors (14248220); Feb2023, Vol. 23 Issue 4, p2069, 18p
Témata: ELECTRIC wheelchairs, BRAIN-computer interfaces, VISUAL evoked potentials, WHEELCHAIRS, REAL-time control, PEOPLE with disabilities, TWO-dimensional bar codes
Abstrakt: Brain–computer interfaces (BCIs) are widely utilized in control applications for people with severe physical disabilities. Several researchers have aimed to develop practical brain-controlled wheelchairs. An existing electroencephalogram (EEG)-based BCI based on steady-state visually evoked potential (SSVEP) was developed for device control. This study utilized a quick-response (QR) code visual stimulus pattern for a robust existing system. Four commands were generated using the proposed visual stimulation pattern with four flickering frequencies. Moreover, we employed a relative power spectrum density (PSD) method for the SSVEP feature extraction and compared it with an absolute PSD method. We designed experiments to verify the efficiency of the proposed system. The results revealed that the proposed SSVEP method and algorithm yielded an average classification accuracy of approximately 92% in real-time processing. For the wheelchair simulated via independent-based control, the proposed BCI control required approximately five-fold more time than the keyboard control for real-time control. The proposed SSVEP method using a QR code pattern can be used for BCI-based wheelchair control. However, it suffers from visual fatigue owing to long-time continuous control. We will verify and enhance the proposed system for wheelchair control in people with severe physical disabilities. [ABSTRACT FROM AUTHOR]
Copyright of Sensors (14248220) is the property of MDPI 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.)
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  Data: Brain–Computer Interface Based on Steady-State Visual Evoked Potential Using Quick-Response Code Pattern for Wheelchair Control.
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  Data: <searchLink fieldCode="AR" term="%22Siribunyaphat%2C+Nannaphat%22">Siribunyaphat, Nannaphat</searchLink><br /><searchLink fieldCode="AR" term="%22Punsawad%2C+Yunyong%22">Punsawad, Yunyong</searchLink>
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  Data: Sensors (14248220); Feb2023, Vol. 23 Issue 4, p2069, 18p
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  Data: <searchLink fieldCode="DE" term="%22ELECTRIC+wheelchairs%22">ELECTRIC wheelchairs</searchLink><br /><searchLink fieldCode="DE" term="%22BRAIN-computer+interfaces%22">BRAIN-computer interfaces</searchLink><br /><searchLink fieldCode="DE" term="%22VISUAL+evoked+potentials%22">VISUAL evoked potentials</searchLink><br /><searchLink fieldCode="DE" term="%22WHEELCHAIRS%22">WHEELCHAIRS</searchLink><br /><searchLink fieldCode="DE" term="%22REAL-time+control%22">REAL-time control</searchLink><br /><searchLink fieldCode="DE" term="%22PEOPLE+with+disabilities%22">PEOPLE with disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22TWO-dimensional+bar+codes%22">TWO-dimensional bar codes</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Brain–computer interfaces (BCIs) are widely utilized in control applications for people with severe physical disabilities. Several researchers have aimed to develop practical brain-controlled wheelchairs. An existing electroencephalogram (EEG)-based BCI based on steady-state visually evoked potential (SSVEP) was developed for device control. This study utilized a quick-response (QR) code visual stimulus pattern for a robust existing system. Four commands were generated using the proposed visual stimulation pattern with four flickering frequencies. Moreover, we employed a relative power spectrum density (PSD) method for the SSVEP feature extraction and compared it with an absolute PSD method. We designed experiments to verify the efficiency of the proposed system. The results revealed that the proposed SSVEP method and algorithm yielded an average classification accuracy of approximately 92% in real-time processing. For the wheelchair simulated via independent-based control, the proposed BCI control required approximately five-fold more time than the keyboard control for real-time control. The proposed SSVEP method using a QR code pattern can be used for BCI-based wheelchair control. However, it suffers from visual fatigue owing to long-time continuous control. We will verify and enhance the proposed system for wheelchair control in people with severe physical disabilities. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Sensors (14248220) is the property of MDPI 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.)
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        Value: 10.3390/s23042069
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        Text: English
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        PageCount: 18
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      – SubjectFull: ELECTRIC wheelchairs
        Type: general
      – SubjectFull: BRAIN-computer interfaces
        Type: general
      – SubjectFull: VISUAL evoked potentials
        Type: general
      – SubjectFull: WHEELCHAIRS
        Type: general
      – SubjectFull: REAL-time control
        Type: general
      – SubjectFull: PEOPLE with disabilities
        Type: general
      – SubjectFull: TWO-dimensional bar codes
        Type: general
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      – TitleFull: Brain–Computer Interface Based on Steady-State Visual Evoked Potential Using Quick-Response Code Pattern for Wheelchair Control.
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              M: 02
              Text: Feb2023
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