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An asynchronous detection algorithm for SSVEP-based BCI using gradient boosting decision tree

  • Yongcheng Wu
  • , Guanghua Xu
  • , Yifan Wu
  • , Bo Wang
  • , Nan Duan
  • , Liang Zeng
  • , Zezhen Han
  • , Sicong Zhang
  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Asynchronous Brain-computer Interface (BCI) plays an essential role in practical applications, for it can detect intentional control (IC) states and non-control (NC) states directly, allowing users to send commands when they intend to do so. In this study, to achieve an efficient asynchronous BCI system, Gradient Boosting Decision Tree (GBDT) is applied to detect IC and NC states for the first time. Specifically, the steady-state visual evoked potentials (SSVEP) is chosen as the BCI paradigm. With the help of appropriate feature selection and optimization, the proposed method not only improved the recognition accuracy but also reduced the computational cost.

源语言英语
主期刊名ICCPR 2020 - Proceedings of 2020 9th International Conference on Computing and Pattern Recognition
出版商Association for Computing Machinery
101-105
页数5
ISBN(电子版)9781450387835
DOI
出版状态已出版 - 30 10月 2020
活动9th International Conference on Computing and Pattern Recognition, ICCPR 2020 - Virtual, Online, 中国
期限: 30 10月 20201 11月 2020

出版系列

姓名ACM International Conference Proceeding Series

会议

会议9th International Conference on Computing and Pattern Recognition, ICCPR 2020
国家/地区中国
Virtual, Online
时期30/10/201/11/20

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