A hybrid brain-computer interface control strategy in a virtual environment

Yu SU; Yu QI; Jian-xun LUO; Bian WU; Fan YANG; Yi LI; Yue-ting ZHUANG; Xiao-xiang ZHENG; Wei-dong CHEN

doi:10.1631/jzus.C1000208

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A hybrid brain-computer interface control strategy in a virtual environment

计算机与自动化 | Updated：2022-08-31

- A hybrid brain-computer interface control strategy in a virtual environment
- A hybrid brain-computer interface control strategy in a virtual environment
- 信息与电子工程前沿（英文） 2011年12卷第5期页码：351-361
- Affiliations：
  
  1.Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, China
  2.School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
  3.Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China
  4.Key Laboratory of Biomedical Engineering of the Ministry of Education, Hangzhou 310027, China
- Author bio：
  
  ‡Corresponding Author
- Funds：
- DOI：10.1631/jzus.C1000208
  中图分类号：
- 收稿：2010-06-18，
  
  修回：2011-03-15，
  
  录用：2010-11-10，
  
  纸质出版：2011-05
- Accepted：
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A hybrid brain-computer interface control strategy in a virtual environment[J]. 信息与电子工程前沿（英文）, 2011,12(5):351-361.

Yu SU, Yu QI, Jian-xun LUO, et al. A hybrid brain-computer interface control strategy in a virtual environment[J]. Frontiers of Information Technology & Electronic Engineering, 2011, 12(5): 351-361.
A hybrid brain-computer interface control strategy in a virtual environment[J]. 信息与电子工程前沿（英文）, 2011,12(5):351-361. DOI： 10.1631/jzus.C1000208.

Yu SU, Yu QI, Jian-xun LUO, et al. A hybrid brain-computer interface control strategy in a virtual environment[J]. Frontiers of Information Technology & Electronic Engineering, 2011, 12(5): 351-361. DOI： 10.1631/jzus.C1000208.

摘要

Abstract

This paper presents a hybrid brain-computer interface (BCI) control strategy

the goal of which is to expand control functions of a conventional motor imagery or a P300 potential based BCI in a virtual environment. The hybrid control strategy utilizes P300 potential to control virtual devices and motor imagery related sensorimotor rhythms to navigate in the virtual world. The two electroencephalography (EEG) patterns serve as source signals for different control functions in their corresponding system states

and state switch is achieved in a sequential manner. In the current system

imagination of left/right hand movement was translated into turning left/right in the virtual apartment continuously

while P300 potentials were mapped to discrete virtual device control commands using a five-oddball paradigm. The combination of motor imagery and P300 patterns in one BCI system for virtual environment control was tested and the results were compared with those of a single motor imagery or P300-based BCI. Subjects obtained similar performances in the hybrid and single control tasks

which indicates the hybrid control strategy works well in the virtual environment.

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