Electrode channel optimisation method for steady-state visual evoked potentials

被引:3
作者
Ma, Kang [1 ,2 ]
Wang, Shuai [3 ]
Zhang, Shuailei [1 ,2 ]
Sun, Ying [1 ]
Zheng, DeZhi [1 ,2 ]
机构
[1] Beihang Univ, Sch Instrumentat Sci & Optoelect Engn, Beijing, Peoples R China
[2] Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing, Peoples R China
[3] Beihang Univ, Sch Engn & Comp Sci, Beijing, Peoples R China
来源
JOURNAL OF ENGINEERING-JOE | 2019年 / 2019卷 / 23期
关键词
medical signal processing; neurophysiology; brain-computer interfaces; visual evoked potentials; electroencephalography; unsupervised target identification methods; different electrode channels; SSVEP-based BCIs; electrode channel optimisation method; electrode channel combination method; optimisation steady-state visual evoked potentials; high-performance brain-computer interface; occipital; parietal lobes; BCI performance; different electrode channel combinations; BRAIN-COMPUTER INTERFACE; STIMULATION; FREQUENCY;
D O I
10.1049/joe.2018.9071
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This article proposes an electrode channel combination method for optimisation steady-state visual evoked potentials (SSVEPs) towards a high-performance brain-computer interface (BCI). In SSVEP-based BCIs, the channels which lie in the area near the occipital and parietal lobes are always selected to improve the classification accuracy. Although the electrode channels which are selected in occipital and parietal lobes have significantly improved the accuracy and reduced the calculating time of algorithm, the effect of electrode channel combination for each subject have not been systematically explored. This study conducts a comparison of BCI performance between two subjects in different electrode channel combinations. The results show significant difference between two subjects when selecting different electrode channel combinations using unsupervised target identification methods. The results suggest that different electrode channels should be selected for different subjects in SSVEP-based BCIs.
引用
收藏
页码:8632 / 8636
页数:5
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