SSVEP-Based Brain-Computer Interface with a Limited Number of Frequencies based on Dual-Frequency Biased Coding

Ge，Sheng1; Jiang，Yichuan2; Zhang，Mingming3; Wang，Ruimin4; Iramina，Keiji5; Lin，Pan6; Leng，Yue7; Wanga，Haixian7; Zheng，Wenming7

2021

10.1109/TNSRE.2021.3073134

IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING   影响因子和分区

1534-4320

1558-0210

How to encode as many targets as possible with a limited-frequency resource is a difficult problem in the practical use of a steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) speller. To solve this problem, this study developed a novel method called dual-frequency biased coding (DFBC) to tag targets in a SSVEP-based 48-character virtual speller, in which each target is encoded with a permutation sequence consisting of two permuted flickering periods that flash at different frequencies. The proposed paradigm was validated by 11 participants in an offline experiment and 7 participants in an online experiment. Three occipital channels (O1, Oz, and O2) were used to obtain the SSVEP signals for identifying the targets. Based on the coding characteristics of the DFBC method, the proposed approach has the ability of self-correction and thus achieves an accuracy of 76.6% and 79.3% for offline and online experiments, respectively, which outperforms the traditional multiple frequencies sequential coding (MFSC) method. This study demonstrates that DFBC is an efficient method for coding a high number of SSVEP targets with a small number of available frequencies.

Brain-computer interface EEG Encoding Frequency division multiaccess Frequency modulation Signal to noise ratio speller steady-state visual evoked potential Time division multiple access Time-frequency analysis Visualization

SCI ; EI

英语

其他

WOS:000645048500003

20211610232218

Interface states

Computer Peripheral Equipment:722.2 ; Classical Physics; Quantum Theory; Relativity:931 ; High Energy Physics; Nuclear Physics; Plasma Physics:932

ENGINEERING

2-s2.0-85104261300

Scopus

1.Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China. (e-mail: shengge@seu.edu.cn)
2.Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China and Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
3.Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
4.Research Center for Brain Communication, Kochi University of Technology, Kochi 7828502, Japan.
5.Graduate School of Systems Life Sciences, Kyushu University, Fukuoka 8190395, Japan.
6.Cognition and Human Behavior Key Laboratory of Hunan Province, Department of Psychology, Hunan Normal University, Changsha 410081, China.
7.Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.

Ge，Sheng,Jiang，Yichuan,Zhang，Mingming,et al. SSVEP-Based Brain-Computer Interface with a Limited Number of Frequencies based on Dual-Frequency Biased Coding[J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,2021,29:760-769.

Ge，Sheng.,Jiang，Yichuan.,Zhang，Mingming.,Wang，Ruimin.,Iramina，Keiji.,...&Zheng，Wenming.(2021).SSVEP-Based Brain-Computer Interface with a Limited Number of Frequencies based on Dual-Frequency Biased Coding.IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,29,760-769.

Ge，Sheng,et al."SSVEP-Based Brain-Computer Interface with a Limited Number of Frequencies based on Dual-Frequency Biased Coding".IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 29(2021):760-769.