A high-ITR SSVEP-based BCI speller

被引：218

作者：

Chen, Xiaogang ^{[1
]}

Chen, Zhikai ^{[1
]}

Gao, Shangkai ^{[1
]}

Gao, Xiaorong ^{[1
]}

机构：

[1] Tsinghua Univ, Sch Med, Dept Biomed Engn, Beijing 100084, Peoples R China

来源：

BRAIN-COMPUTER INTERFACES | 2014年 / 1卷 / 3-4期

基金：

中国国家自然科学基金;

关键词：

EEG; BCI; SSVEP; speller; ITR;

D O I：

10.1080/2326263X.2014.944469

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Spelling is an important application of brain-computer interfaces (BCIs). Previous BCI spellers were not suited for widespread use due to their low information transfer rate (ITR). In this study, we constructed a high-ITR BCI speller based on the steady-state visual evoked potential (SSVEP). A 45-target BCI speller was implemented with a frequency resolution of 0.2 Hz. A sampled sinusoidal stimulation method was used to present visual stimuli on a conventional LCD screen. The online results revealed that the proposed BCI speller had a good performance, reaching a high average accuracy (84.1% for 2 s stimulation time; 90.2% for 3 s stimulation time) and the corresponding high ITR (105 bits/min for 2 s stimulation time, 82 bits/min for 3 s stimulation time) during the low-frequency stimuli, while 88.7% and 61 bits/min were achieved for a 4 s time window during the high-frequency stimuli.

引用

页码：181 / 191

页数：11

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