title: A combination strategy based brain-computer interface for two-dimensional movement control.
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.
  
  
  METHODS
  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.
  
  
  RESULTS
  The average hit rate was more than [Formula: see text] 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Institute of Information Engineering, Shanghai Maritime University, Shanghai, China. Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen, Germany.
authors.forename: Bin
authors.initials: B
authors.lastname: Xia
authors.forename: Oladazimi
authors.initials: O
authors.lastname: Maysam
authors.forename: Sandra
authors.initials: S
authors.lastname: Veser
authors.forename: Lei
authors.initials: L
authors.lastname: Cao
authors.forename: Jie
authors.initials: J
authors.lastname: Li
authors.forename: Jie
authors.initials: J
authors.lastname: Jia
authors.forename: Hong
authors.initials: H
authors.lastname: Xie
authors.forename: Niels
authors.initials: N
authors.lastname: Birbaumer
mesh_terms: D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D062207:Brain-Computer Interfaces; D003143:Communication Devices for People with Disabilities; D004569:Electroencephalography / Q000379:methods; D005074:Evoked Potentials, Visual / Q000502:physiology*; D025461:Feedback, Physiological / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D009068:Movement / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013647:Task Performance and Analysis; D015443:Word Processing / Q000379:methods*; D055815:Young Adult