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  • 教师姓名: 谢俊
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  • 所在单位: 机械工程学院
  • 学历: 博士研究生毕业
  • 办公地点: 西安交通大学曲江校区西五楼A209室;
    西安交通大学创新港校区2号巨构3175室。
  • 性别: 男
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Electroencephalogram-based brain-computer interface for the Chinese spelling system: a survey

发布时间:2025-04-30
点击次数:
发布时间:
2025-04-30
论文名称:
Electroencephalogram-based brain-computer interface for the Chinese spelling system: a survey
发表刊物:
Frontiers of Information Technology & Electronic Engineering
摘要:
Electroencephalogram (EEG) based brain-computer interfaces allow users to communicate with the external environment by means of their EEG signals, without relying on the brain’s usual output pathways such as muscles. A popular application for EEGs is the EEG-based speller, which translates EEG signals into intentions to spell particular words, thus benefiting those suffering from severe disabilities, such as amyotrophic lateral sclerosis. Although the EEG-based English speller (EEGES) has been widely studied in recent years, few studies have focused on the EEG-based Chinese speller (EEGCS). The EEGCS is more difficult to develop than the EEGES, because the English alphabet contains only 26 letters. By contrast, Chinese contains more than 11 000 logographic characters. The goal of this paper is to survey the literature on EEGCS systems. First, the taxonomy of current EEGCS systems is discussed to get the gist of the paper. Then, a common framework unifying the current EEGCS and EEGES systems is proposed, in which the concept of EEG-based choice acts as a core component. In addition, a variety of current EEGCS systems are investigated and discussed to highlight the advances, current problems, and future directions for EEGCS.
合写作者:
Minghui Shi, Changle Zhou, Jun Xie, Shaozi Li, Qingyang Hong, Min Jiang, et al.
是否译文:
发表时间:
2018-03-10