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The MindGame: a P300-based brain-computer interface game.

Andrea Finke¹, Alexander Lenhardt, Helge Ritter

¹Research Institute for Cognition and Robotics - CoR-Lab, Bielefeld University, Germany. afinke@cor-lab.uni-bielefeld.de

Neural Networks : the Official Journal of the International Neural Network Society

|July 29, 2009

Summary

This summary is machine-generated.

This study introduces MindGame, a Brain-Computer Interface (BCI) game using P300 potentials for character control. It achieves 65% single-trial classification accuracy, offering real-time player feedback.

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Area of Science:

Neuroscience
Human-Computer Interaction
Rehabilitation Engineering

Background:

Brain-Computer Interfaces (BCI) enable control via neural signals.
P300 event-related potentials are a common BCI signal.
Real-time feedback enhances BCI usability.

Purpose of the Study:

To develop and evaluate a BCI game (MindGame) utilizing P300 potentials.
To translate P300 events into character movements in a 3D environment.
To assess single-trial classification performance with gradual feedback.

Main Methods:

Implementation of the MindGame BCI system.
Utilizing a linear feature selection and classification scheme.
Online, single-trial P300 event detection and classification from scalp electrodes.

Main Results:

Successful translation of P300 events into character actions.
Achieved 0.65 classification accuracy on single trials during online operation.
Provided gradual feedback to the player based on classification outcomes.

Conclusions:

The MindGame demonstrates a viable BCI application for interactive entertainment.
Single-trial P300 classification is feasible for real-time BCI control.
Gradual feedback improves the player's interaction within the BCI game.