北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2023, Vol. 46 ›› Issue (6): 15-0.

• 智慧医疗 • 上一篇    下一篇

面向SSVEP-BCI的最大后验准则异步检测算法

张洪欣,王俊淞,杨晨   

  1. 北京邮电大学
  • 收稿日期:2023-01-02 修回日期:2023-03-10 出版日期:2023-12-28 发布日期:2023-12-29
  • 通讯作者: 张洪欣 E-mail:hongxinzhang@bupt.edu.cn
  • 基金资助:
    国家自然科学基金项目(62006024); 航空科学基金项目(2019ZG073001)

A Asynchronous Detection Algorithm of SSVEP-BCI Based on Maximum Posterior Criterion

  • Received:2023-01-02 Revised:2023-03-10 Online:2023-12-28 Published:2023-12-29

摘要: 面向非等概先验概率的实际脑机接口应用场景,提出了一种基于最大后验准则的稳态视觉诱发电位脑机接口(SSVEP-BCI)异步检测算法。利用空-时均衡多窗算法并通过引入最大后验准则,设计了一种基于序贯检测的动态窗异步算法,充分利用了先验信息以提高异步脑机接口系统的性能。实验结果表明,相比于传统的空-时均衡多窗算法,所提算法的目标识别准确率和平均实用比特率提升较明显,而平均指令时间和平均虚警率显著减少,验证了所提算法的有效性与实用性。

关键词: 稳态视觉诱发电位, 脑机接口, 最大后验准则;异步

Abstract:

Considering the prior probability of EEG signals is non-equal in some application scenario of brain-computer interface, we propose a asynchronous detection algorithm of steady-state visual evoked potential brain-computer interface (SSVEP-BCI) based on maximum posterior criterion. Using spatio-temporal equalization multi-window technology, a dynamic window algorithm based on sequential detection is designed by introducing maximum posterior criterion, which makes full use of prior information to improve the performance of brain-computer interface systems. Experiments show that compared with the traditional spatio-temporal equalization multi-window algorithm, the target recognition accuracy of the proposed algorithm is increased, and the average practical bit rate has a substantial improvement. Besides, the instruction time and the average false alarm rate are significantly reduced. Thus the effectiveness and practicability of the proposed algorithm are verified.

Key words: steady-state visual evoked potential, brain-computer interface, maximum posterior criterion; asynchronous detection algorithm

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