Literature DB >> 23587933

A new dual-frequency stimulation method to increase the number of visual stimuli for multi-class SSVEP-based brain-computer interface (BCI).

Han-Jeong Hwang1, Dong Hwan Kim, Chang-Hee Han, Chang-Hwan Im.   

Abstract

In the present study, we introduce a new dual-frequency stimulation method that can produce more visual stimuli with limited number of stimulation frequencies for use in multiclass steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems. Methods for increasing the number of visual stimuli are necessary, particularly for the implementation of multi-class SSVEP-based BCI, as available stimulation frequencies are generally limited when visual stimuli are presented through a computer monitor. The new stimulation was based on a conventional black-white checkerboard pattern; however, unlike the conventional approach, ten visual stimuli eliciting distinct SSVEP responses at different frequencies could be generated by combining four different stimulation frequencies. Through the offline experiments conducted with eleven participants, we confirmed that all ten visual stimuli could evoke distinct and discriminable single SSVEP peaks, of which the signal-to-noise ratios were high enough to be used for practical SSVEP-based BCI systems. In order to demonstrate the possibility of the practical use of the proposed method, a mental keypad system was implemented and online experiments were conducted with additional ten participants. We achieved an average information transfer rate of 33.26 bits/min and an average accuracy of 87.23%, and all ten participants succeeded in calling their mobile phones using our online BCI system.
Copyright © 2013 Elsevier B.V. All rights reserved.

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Year:  2013        PMID: 23587933     DOI: 10.1016/j.brainres.2013.03.050

Source DB:  PubMed          Journal:  Brain Res        ISSN: 0006-8993            Impact factor:   3.252


  11 in total

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Authors:  M Jawad Khan; Keum-Shik Hong
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2.  A multi-day and multi-band dataset for a steady-state visual-evoked potential-based brain-computer interface.

Authors:  Ga-Young Choi; Chang-Hee Han; Young-Jin Jung; Han-Jeong Hwang
Journal:  Gigascience       Date:  2019-11-01       Impact factor: 6.524

3.  SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots.

Authors:  Jing Zhao; Wei Li; Xiaoqian Mao; Mengfan Li
Journal:  J Vis Exp       Date:  2015-11-24       Impact factor: 1.355

4.  Multi-phase cycle coding for SSVEP based brain-computer interfaces.

Authors:  Jijun Tong; Danhua Zhu
Journal:  Biomed Eng Online       Date:  2015-01-16       Impact factor: 2.819

5.  A SSVEP Stimuli Encoding Method Using Trinary Frequency-Shift Keying Encoded SSVEP (TFSK-SSVEP).

Authors:  Xing Zhao; Dechun Zhao; Xia Wang; Xiaorong Hou
Journal:  Front Hum Neurosci       Date:  2017-06-02       Impact factor: 3.169

6.  Development of a Brain-Computer Interface Toggle Switch with Low False-Positive Rate Using Respiration-Modulated Photoplethysmography.

Authors:  Chang-Hee Han; Euijin Kim; Chang-Hwan Im
Journal:  Sensors (Basel)       Date:  2020-01-08       Impact factor: 3.576

7.  Evaluation of Real-Time Endogenous Brain-Computer Interface Developed Using Ear-Electroencephalography.

Authors:  Soo-In Choi; Ji-Yoon Lee; Ki Moo Lim; Han-Jeong Hwang
Journal:  Front Neurosci       Date:  2022-03-24       Impact factor: 4.677

8.  SSVEP response is related to functional brain network topology entrained by the flickering stimulus.

Authors:  Yangsong Zhang; Peng Xu; Yingling Huang; Kaiwen Cheng; Dezhong Yao
Journal:  PLoS One       Date:  2013-09-09       Impact factor: 3.240

9.  Periodic Visual Stimulation Induces Resting-State Brain Network Reconfiguration.

Authors:  Daqing Guo; Fengru Guo; Yangsong Zhang; Fali Li; Yang Xia; Peng Xu; Dezhong Yao
Journal:  Front Comput Neurosci       Date:  2018-03-28       Impact factor: 2.380

10.  Use of Sine Shaped High-Frequency Rhythmic Visual Stimuli Patterns for SSVEP Response Analysis and Fatigue Rate Evaluation in Normal Subjects.

Authors:  Ahmadreza Keihani; Zahra Shirzhiyan; Morteza Farahi; Elham Shamsi; Amin Mahnam; Bahador Makkiabadi; Mohsen R Haidari; Amir H Jafari
Journal:  Front Hum Neurosci       Date:  2018-05-28       Impact factor: 3.169

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