A previously introduced variation of a conventional P300 speller, consisting on a modifiable image background and asymmetrically arranged stimulation markers for controlling wheelchair navigation, was used in this study. Five commonly used classifiers for solving P300 speller-like tasks, namely, Linear-SVM, RBF-SVM, LASSO-LDA, Shrinkage-LDA and SWLDA, were designed and trained and their performances contrasted, seeking the classifier with highest performance on our proposed screen. 19 able-bodied subjects participated in this study. The highest median sensitivity and specificity were respectively 1.00 (IQR = 0.61-1.00) and 1.00 (IQR = 0.96-1.00), which were obtained with the LASSO approach. These performances are suitable for the planned application and they are comparable with the conventional P300 speller performances reported, despite of our speller variation. Friedman tests showed that there are no statistical differences on the sensitivity and specificity performances among the five classifiers evaluated. However, the customized selection of the classifier approach improves the sensitivity by 66.7% in some cases.