A combination strategy based brain-computer interface for two-dimensional movement control

Bin Xia, Oladazimi Maysam, Sandra Veser, Lei Cao, Jie Li, Jie Jia, Hong Xie, Niels Birbaumer

Research output: Contribution to journalArticlepeer-review

Abstract

Objective. Two-dimensional (2D) movement control is an important issue in brain-computer interfaces (BCIs) research because being able to move, for example, a cursor with the brain will enable patients with motor disabilities to control their environment. However, it is still a challenge to continuously control 2D movement with a non-invasive BCI system. In this paper, we developed a 2D cursor control with motor imagery BCI tasks allowing users to move a cursor to any position by using a combination strategy. With this strategy, a user can combine multiple motor imagery tasks, alternatively or simultaneously, to control 2D movements. Approach. After a training session, six participants took part in the first control strategy experiment (the center-out experiment) to verify the effectiveness of the cursor control. Three of the six participants performed an additional experiment, in which they were required to move the cursor to hit five targets in a given sequence. Main results. The average hit rate was more than and the trajectories were close to the shortest path. The average hit rate was more than 95.6% and the trajectories were close to the shortest path in the center-out experiment. In the additional experiment, three participants achieved a 100% hit rate with a short trajectory. Significance. The results demonstrated that users were able to effectively control the 2D movement using the proposed strategy. The present system may be used as a tool to interact with the external world.

Original languageEnglish
Article number046021
JournalJournal of Neural Engineering
Volume12
Issue number4
DOIs
Publication statusPublished - Aug 1 2015

Keywords

  • 2-dimensional movement
  • brain-computer interface
  • motor imagery

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

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