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 timeconsuming training is needed in order to test possible applications for motor-impaired patients.

P300-based brain computer interface: Reliability and performance in healty and paralhysed participants

GIOVE, Silvio;
2006

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 timeconsuming training is needed in order to test possible applications for motor-impaired patients.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/30035
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