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Changing the P300 brain computer interface.

作者信息

Bayliss Jessica D, Inverso Samuel A, Tentler Aleksey

机构信息

Computer Science Department, Rochester Institute of Technology, Rochester, New York, USA.

出版信息

Cyberpsychol Behav. 2004 Dec;7(6):694-704. doi: 10.1089/cpb.2004.7.694.

Abstract

Brain-computer interfaces (BCIs) are now feasible for use as an alternative control option for those with severe motor impairments. The P300 component of the evoked potential has proven useful as a control signal. Individuals do not need to be trained to produce the signal, and it is fairly stable and has a large evoked potential. Even with recent signal classification advances, on-line experiments with P300-based BCIs remain far from perfect. We present two potential methods for improving control accuracy. Experimental results in an evoked potential BCI, used to control items in a virtual apartment, show a reduced response exists when items are accidentally controlled. The presence of a P300-like signal in response to goal items means that it can be used for automatic error correction. Preliminary results from an interface experiment using three different button configurations for a yes/no BCI task show that the configuration of buttons may affect on-line signal classification. These results will be discussed in light of the special considerations needed when working with an amyotrophic lateral sclerosis (ALS) patient.

摘要

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