P300-based brain computer interface: Reliability and performance in healthy and paralysed participants

F. Piccione, F. Giorgi, P. Tonin, K. Priftis, S. Giove, S. Silvoni, G. Palmas, F. Beverina

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: This study aimed to describe the use of the P300 event-related potential as a control signal in a brain computer interface (BCI) for healthy and paralysed participants. Methods: The experimental device used the P300 wave to control the movement of an object on a graphical interface. Visual stimuli, consisting of four arrows (up, right, down, left) were randomly presented in peripheral positions on the screen. Participants were instructed to recognize only the arrow indicating a specific direction for an object to move. P300 epochs, synchronized with the stimulus, were analyzed on-line via Independent Component Analysis (ICA) with subsequent feature extraction and classification by using a neural network. Results: We tested the reliability and the performance of the system in real-time. The system needed a short training period to allow task completion and reached good performance. Nonetheless, severely impaired patients had lower performance than healthy participants. Conclusions: The proposed system is effective for use with healthy participants, whereas further research is needed before it can be used with locked-in syndrome patients. Significance: The P300-based BCI described can reliably control, in 'real time', the motion of a cursor on a graphical interface, and no time-consuming training is needed in order to test possible applications for motor-impaired patients.

Original languageEnglish
Pages (from-to)531-537
Number of pages7
JournalClinical Neurophysiology
Volume117
Issue number3
DOIs
Publication statusPublished - Mar 2006

Keywords

  • BCI
  • ERP
  • ICA
  • Locked-in syndrome
  • Neural network
  • P300

ASJC Scopus subject areas

  • Clinical Neurology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Sensory Systems
  • Physiology (medical)

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