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. 2008 Jan 15;167(1):15-21.
doi: 10.1016/j.jneumeth.2007.07.017. Epub 2007 Aug 1.

Toward enhanced P300 speller performance

Affiliations

Toward enhanced P300 speller performance

D J Krusienski et al. J Neurosci Methods. .

Abstract

This study examines the effects of expanding the classical P300 feature space on the classification performance of data collected from a P300 speller paradigm [Farwell LA, Donchin E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroenceph Clin Neurophysiol 1988;70:510-23]. Using stepwise linear discriminant analysis (SWLDA) to construct a classifier, the effects of spatial channel selection, channel referencing, data decimation, and maximum number of model features are compared with the intent of establishing a baseline not only for the SWLDA classifier, but for related P300 speller classification methods in general. By supplementing the classical P300 recording locations with posterior locations, online classification performance of P300 speller responses can be significantly improved using SWLDA and the favorable parameters derived from the offline comparative analysis.

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Figures

Fig. 1
Fig. 1
The 6×6 matrix used in the current study. A row or column intensifies for 100 ms every 175 ms. The letter in parentheses at the top of the window is the current target letter “D.” A P300 should be elicited when the fourth column or first row is intensified. After the intensification sequence for a character epoch, the result is classified and online feedback is provided directly below the character to be copied.
Fig. 2
Fig. 2
The 64-channel electrode montage and the channel sets. Set 0 is a subset defined purely for illustration purposes, sets 1 through 4 were used in the analysis.
Fig. 3
Fig. 3
Performance curves at each level of the 4 factors for all 15 stimulus intensification sequences. Each of the 4 rows of plots indicates a single factor for each participant. The rightmost column of plots shows the average for each factor across participants.
Fig. 4
Fig. 4
Online Performance for each participant using the best set of feature weights (solid line) or Set 1 weights (Fz, Cz, and Pz only) (dashed line). Each participant completed two sessions. Half of each session was conducted with the best weights and half with Set 1 weights, in counterbalanced order.

References

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