Multirapid Serial Visual Presentation Framework for EEG-Based Target Detection.

Target image detection based on a rapid serial visual presentation (RSVP) paradigm is a typical brain-computer interface system with various applications, such as image retrieval. In an RSVP paradigm, a P300 component is detected to determine target images. This strategy requires high-precision sing...

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Published in:BioMed Research International Vol. 2017; pp. 1 - 13
Main Authors: Lin, Zhimin, Zeng, Ying, Gao, Hui, Tong, Li, Zhang, Chi, Wang, Xiaojuan, Wu, Qunjian, Yan, Bin
Format: equations & formulas pictorial research tables/charts Journal Article
Published: Wiley-Blackwell 7/20/2017
Online Access:View this record in EBSCOhost
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      dt: 7/20/2017
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2017/2049094
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        atl: Multirapid Serial Visual Presentation Framework for EEG-Based Target Detection.
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        au:
          Lin, Zhimin
          Zeng, Ying
          Gao, Hui
          Tong, Li
          Zhang, Chi
          Wang, Xiaojuan
          Wu, Qunjian
          Yan, Bin
        affil: China National Digital Switching System Engineering and Technological Research Center, Zhengzhou, China
      sug:
        subj:
          Electroencephalography
          Diagnostic Imaging
          Human
          Brain Physiology
          Visual Acuity
          Data Analysis Software
      ab: Target image detection based on a rapid serial visual presentation (RSVP) paradigm is a typical brain-computer interface system with various applications, such as image retrieval. In an RSVP paradigm, a P300 component is detected to determine target images. This strategy requires high-precision single-trial P300 detection methods. However, the performance of single-trial detection methods is relatively lower than that of multitrial P300 detection methods. Image retrieval based on multitrial P300 is a new research direction. In this paper, we propose a triple-RSVP paradigm with three images being presented simultaneously and a target image appearing three times. Thus, multitrial P300 classification methods can be used to improve detection accuracy. In this study, these mechanisms were extended and validated, and the characteristics of the multi-RSVP framework were further explored. Two different P300 detection algorithms were also utilized in multi-RSVP to demonstrate that the scheme is universally applicable. Results revealed that the detection accuracy of the multi-RSVP paradigm was higher than that of the standard RSVP paradigm. The results validate the effectiveness of the proposed method, and this method can provide a whole new idea in the field of EEG-based target detection.
      pubtype: Academic Journal
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        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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