Literature DB >> 23744702

Adaptive SSVEP-based BCI system with frequency and pulse duty-cycle stimuli tuning design.

Kuo-Kai Shyu, Yun-Jen Chiu, Po-Lei Lee, Jia-Ming Liang, Shao-Hwo Peng.   

Abstract

This study aims to design a steady state visual evoked potentials (SSVEP) based brain-computer interface (BCI) system with only three electrodes. It is known that low frequency flickering induces more intensive SSVEP, but might cause users feel uncomfortable and easily tired. Therefore, this paper proposes a novel middle/high frequency flickering stimulus. However, users show different SSVEP responses when gazing at the same stimuli. It is improper to design fixed frequency flickering stimuli for all users. This study firstly proposes a strategy to adjust the stimuli frequency for each user that could cause better SSVEP. Moreover, to further enhance the SSVEP, this study incorporates flickering duty-cycle for stimuli design, which has been discussed less for SSVEP-based BCI systems. The proposed system consists of two modes, flicker frequency/duty-cycle selection mode and application mode. The flicker frequency/duty-cycle selection mode obtains two best frequencies between 24 and 36 Hz with their related optimal duty-cycle. Then the system goes into the application mode to control the devices. A new fact that has been found is that the optimal flicker frequency and duty-cycle do not vary with time. It means once the optical flicker frequency and duty-cycle is determined the first time, flicker frequency/duty-cycle selection mode does not need to operate the next time. Furthermore, the phase coding technology is used to extend the one command/one frequency to multi command/one frequency. Experimental results show the proposed system has good performance with average accuracy 95% and average command transfer interval 4.4925 s per command.

Mesh:

Year:  2013        PMID: 23744702     DOI: 10.1109/TNSRE.2013.2265308

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  7 in total

1.  Novel non-contact control system of electric bed for medical healthcare.

Authors:  Chi-Chun Lo; Shang-Ho Tsai; Bor-Shyh Lin
Journal:  Med Biol Eng Comput       Date:  2016-06-15       Impact factor: 2.602

2.  Optimising the classification of feature-based attention in frequency-tagged electroencephalography data.

Authors:  Angela I Renton; David R Painter; Jason B Mattingley
Journal:  Sci Data       Date:  2022-06-13       Impact factor: 8.501

3.  A Prototype SSVEP Based Real Time BCI Gaming System.

Authors:  Ignas Martišius; Robertas Damaševičius
Journal:  Comput Intell Neurosci       Date:  2016-03-09

4.  Stimulator Selection in SSVEP-Based Spatial Selective Attention Study.

Authors:  Songyun Xie; Chang Liu; Klaus Obermayer; Fangshi Zhu; Linan Wang; Xinzhou Xie; Wei Wang
Journal:  Comput Intell Neurosci       Date:  2016-12-01

5.  Sinc-Windowing and Multiple Correlation Coefficients Improve SSVEP Recognition Based on Canonical Correlation Analysis.

Authors:  Valeria Mondini; Anna Lisa Mangia; Luca Talevi; Angelo Cappello
Journal:  Comput Intell Neurosci       Date:  2018-04-12

Review 6.  Artificial Intelligence Algorithms in Visual Evoked Potential-Based Brain-Computer Interfaces for Motor Rehabilitation Applications: Systematic Review and Future Directions.

Authors:  Josefina Gutierrez-Martinez; Jorge A Mercado-Gutierrez; Blanca E Carvajal-Gámez; Jorge L Rosas-Trigueros; Adrian E Contreras-Martinez
Journal:  Front Hum Neurosci       Date:  2021-11-25       Impact factor: 3.169

7.  EEG-Controlled Wall-Crawling Cleaning Robot Using SSVEP-Based Brain-Computer Interface.

Authors:  Lei Shao; Longyu Zhang; Abdelkader Nasreddine Belkacem; Yiming Zhang; Xiaoqi Chen; Ji Li; Hongli Liu
Journal:  J Healthc Eng       Date:  2020-01-11       Impact factor: 2.682

  7 in total

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