4.4 Article

A brain-computer interface method combined with eye tracking for 3D interaction

Journal

JOURNAL OF NEUROSCIENCE METHODS
Volume 190, Issue 2, Pages 289-298

Publisher

ELSEVIER
DOI: 10.1016/j.jneumeth.2010.05.008

Keywords

BCI (brain computer interface); Eye tracking; 3D interaction

Funding

  1. MKE (Ministry of Knowledge Economy) [10032108]
  2. Ministry of Education, Science and Technology [2009-0073315]
  3. Korea Institute of Industrial Technology(KITECH) [10032108] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
  4. National Research Council of Science & Technology (NST), Republic of Korea [nims-2010-1] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
  5. National Research Foundation of Korea [2009-0073315] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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With the recent increase in the number of three-dimensional (3D) applications, the need for interfaces to these applications has increased. Although the eye tracking method has been widely used as an interaction interface for hand-disabled persons, this approach cannot be used for depth directional navigation. To solve this problem, we propose a new brain computer interface (BCI) method in which the BCI and eye tracking are combined to analyze depth navigation, including selection and two-dimensional (2D) gaze direction, respectively. The proposed method is novel in the following five Ways compared to previous works. First, a device to measure both the gaze direction and an electroencephalogram (EEG) pattern is proposed with the sensors needed to measure the EEG attached to a head-mounted eye tracking device. Second, the reliability of the BCI interface is verified by demonstrating that there is no difference between the real and the imaginary movements for the same work in terms of the EEG power spectrum. Third, depth control for the 3D interaction interface is implemented by an imaginary arm reaching movement. Fourth, a selection method is implemented by an imaginary hand grabbing movement. Finally, for the independent operation of gazing and the BCI, a mode selection method is proposed that measures a user's concentration by analyzing the pupil accommodation speed, which is not affected by the operation of gazing and the BCI. According to experimental results, we confirmed the feasibility of the proposed 3D interaction method using eye tracking and a BCI. (C) 2010 Elsevier B.V. All rights reserved.

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