Literature DB >> 16365511

A novel multiple frequency stimulation method for steady state VEP based brain computer interfaces.

T M Srihari Mukesh1, V Jaganathan, M Ramasubba Reddy.   

Abstract

The objective is to increase the number of selections in brain computer interfaces (BCI) by recording and analyzing the steady state visual evoked potential response to dual stimulation. A BCI translates the VEP signals into user commands. The frequency band from which stimulation frequency can be selected is limited for SSVEP. This paper discusses a method to increase the number of commands by using a suitable combination of frequencies for stimulation. A biopotential amplifier based on the driven right leg circuit (DRL) is used to record 60 s epochs of the SSVEP (O(z)-A(1)) on 15 subjects using simultaneous overlapped stimulation (6, 7, 12, 13 and 14 Hzs and corresponding half frequencies). The power spectrum of each recording is obtained by frequency domain averaging of 400 ms SSVEPs and the spectral peaks were normalized. The spectral peaks of the combination frequencies of stimulation are predominant compared to individual stimulating frequencies. This method increases the number of selections by using a limited number of stimulating frequencies in BCI. For example, six selections are possible by generating only three frequencies.

Mesh:

Year:  2005        PMID: 16365511     DOI: 10.1088/0967-3334/27/1/006

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  10 in total

Review 1.  A survey of stimulation methods used in SSVEP-based BCIs.

Authors:  Danhua Zhu; Jordi Bieger; Gary Garcia Molina; Ronald M Aarts
Journal:  Comput Intell Neurosci       Date:  2010-03-07

2.  Square or sine: finding a waveform with high success rate of eliciting SSVEP.

Authors:  Fei Teng; Yixin Chen; Aik Min Choong; Scott Gustafson; Christopher Reichley; Pamela Lawhead; Dwight Waddell
Journal:  Comput Intell Neurosci       Date:  2011-09-15

3.  Multiple frequencies sequential coding for SSVEP-based brain-computer interface.

Authors:  Yangsong Zhang; Peng Xu; Tiejun Liu; Jun Hu; Rui Zhang; Dezhong Yao
Journal:  PLoS One       Date:  2012-03-06       Impact factor: 3.240

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.  Decoding of top-down cognitive processing for SSVEP-controlled BMI.

Authors:  Byoung-Kyong Min; Sven Dähne; Min-Hee Ahn; Yung-Kyun Noh; Klaus-Robert Müller
Journal:  Sci Rep       Date:  2016-11-03       Impact factor: 4.379

6.  Brain response to luminance-based and motion-based stimulation using inter-modulation frequencies.

Authors:  Xin Zhang; Guanghua Xu; Jun Xie; Xun Zhang
Journal:  PLoS One       Date:  2017-11-15       Impact factor: 3.240

7.  A novel multiple time-frequency sequential coding strategy for hybrid brain-computer interface.

Authors:  Zan Yue; Qiong Wu; Shi-Yuan Ren; Man Li; Bin Shi; Yu Pan; Jing Wang
Journal:  Front Hum Neurosci       Date:  2022-07-29       Impact factor: 3.473

8.  Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard.

Authors:  Felix Gembler; Piotr Stawicki; Ivan Volosyak
Journal:  Front Neurosci       Date:  2015-12-22       Impact factor: 4.677

9.  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

10.  A Light Spot Humanoid Motion Paradigm Modulated by the Change of Brightness to Recognize the Stride Motion Frequency.

Authors:  Xin Zhang; Guanghua Xu; Xun Zhang; Qingqiang Wu
Journal:  Front Hum Neurosci       Date:  2018-10-15       Impact factor: 3.169

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.