Self-calibration algorithm in an asynchronous P300-based brain-computer interface.
OBJECTIVE
Reliability is a desirable characteristic of brain-computer interface (BCI) systems when they are intended to be used under non-experimental operating conditions. In addition, their overall usability is influenced by the complex and frequent procedures that are required for configuration and calibration. Earlier studies examined the issue of asynchronous control in P300-based BCIs, introducing dynamic stopping and automatic control suspension features. This report proposes and evaluates an algorithm for the automatic recalibration of the classifier's parameters using unsupervised data.


METHODS
Ten healthy subjects participated in five P300-based BCI sessions throughout a single day. First, we examined whether continuous adaptation of control parameters improved the accuracy of the asynchronous system over time. Then, we assessed the performance of the self-calibration algorithm with respect to the no-recalibration and supervised calibration conditions with regard to system accuracy and communication efficiency.


RESULTS
Offline tests demonstrated that continuous adaptation of the control parameters significantly increased the communication efficiency of asynchronous P300-based BCIs. The self-calibration algorithm correctly assigned labels to unsupervised data with 95% accuracy, effecting communication efficiency that was comparable with that of supervised repeated calibration.


CONCLUSIONS
Although additional online tests that involve end-users under non-experimental conditions are needed, these preliminary results are encouraging, from which we conclude that the self-calibration algorithm is a promising solution to improve P300-based BCI usability and reliability.
Neuroelectrical Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Rome, Italy. Department of Computer, Control, and Management Engineering, University of Rome 'Sapienza', Rome, Italy.
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Schettini
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Aloise
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Aricò
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Salinari
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Mattia
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Cincotti
D000328:Adult; D000465:Algorithms; D062207:Brain-Computer Interfaces / Q000592:standards*; D002138:Calibration; D003143:Communication Devices for People with Disabilities / Q000592:standards*; D004569:Electroencephalography / Q000295:instrumentation* / Q000592:standards*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D005071:Evoked Potentials / Q000502:physiology; D005260:Female; D006801:Humans; D007558:Italy; D008297:Male; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface