Motion-Based Rapid Serial Visual Presentation for Gaze-Independent Brain-Computer Interfaces

Dong Ok Won, Han Jeong Hwang, Dong Min Kim, Klaus Robert Müller, Seong Whan Lee

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90 Citations (Scopus)


Most event-related potential (ERP)-based brain-computer interface (BCI) spellers primarily use matrix layouts and generally require moderate eye movement for successful operation. The fundamental objective of this paper is to enhance the perceptibility of target characters by introducing motion stimuli to classical rapid serial visual presentation (RSVP) spellers that do not require any eye movement, thereby applying them to paralyzed patients with oculomotor dysfunctions. To test the feasibility of the proposed motion-based RSVP paradigm, we implemented three RSVP spellers: 1) fixed-direction motion (FM-RSVP); 2) random-direction motion (RM-RSVP); and 3) (the conventional) non-motion stimulation (NM-RSVP), and evaluated the effect of the three different stimulation methods on spelling performance. The two motion-based stimulation methods, FM- and RM-RSVP, showed shorter P300 latency and higher P300 amplitudes (i.e., 360.4-379.6 ms; 5.5867- 5.7662μ V) than the NM-RSVP (i.e., 480.4 ms; 4.7426μ V). This led to higher and more stable performances for FM- and RM-RSVP spellers than NM-RSVP speller (i.e., 79.06±6.45% for NM-RSVP, 90.60±2.98% for RM-RSVP, and 92.74±2.55% for FM-RSVP). In particular, the proposed motion-based RSVP paradigm was significantly beneficial for about half of the subjects who might not accurately perceive rapidly presented static stimuli. These results indicate that the use of proposed motion-based RSVP paradigm is more beneficial for target recognition when developing BCI applications for severely paralyzed patients with complex ocular dysfunctions.

Original languageEnglish
Article number8008839
Pages (from-to)334-343
Number of pages10
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Issue number2
Publication statusPublished - 2018 Feb

Bibliographical note

Funding Information:
Manuscript received May 4, 2016; revised November 7, 2016, March 14, 2017, and July 23, 2017; accepted July 24, 2017. Date of publication August 11, 2017; date of current version February 9, 2018. This work was supported in part by the Institute for Information and Communications Technology Promotion (IITP) through the Korea Government (MSIT) under Grant 2017-0-00451, in part by the Development of BCI-based Brain and Cognitive Computing Technology for Recognizing User’s Intentions using Deep Learning) and the MSIT, South Korea, under the SW Starlab support program supervised by the IITP under Grant IITP-2015-1107. (Corresponding author: Seong-Whan Lee.) D.-O. Won, D.-M. Kim, and S.-W. Lee are with the Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea (e-mail:;;

Publisher Copyright:
© 2001-2011 IEEE.


  • Brain-computer interface (BCI)
  • event-related potential (ERP)
  • gaze-independent
  • rapid serial visual presentation (RSVP)

ASJC Scopus subject areas

  • Internal Medicine
  • General Neuroscience
  • Biomedical Engineering


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