Objective and Subjective Evaluation of Online Error Correction during P300-Based Spelling

Perrin Margaux,Mattout Jérémie,Daligault Sébastien,Maby Emmanuel,Bertrand Olivier

doi:10.1155/2012/578295

Abstract

Error potentials (ErrP) are alterations of EEG traces following the subject’s perception of erroneous feedbacks. They provide a way to recognize misinterpreted commands in brain-computer interfaces (BCI). However, this has been evaluated online in only a couple of studies and mostly with very few subjects. In this study, we implemented a P300-based BCI, including not only online error detection but also, for the first time, automatic correction. We evaluated it in 16 healthy volunteers. Whenever an error was detected, a new decision was made based on the second best guess of a probabilistic classifier. At the group level, correction did neither improve nor deteriorate spelling accuracy. However, automatic correction yielded a higher bit rate than a respelling strategy. Furthermore, the fine examination of interindividual differences in the efficiency of error correction and spelling clearly distinguished between two groups who differed according to individual specificity in ErrP detection. The high specificity group had larger evoked responses and made fewer errors which were corrected more efficiently, yielding a 4% improvement in spelling accuracy and a higher bit rate. Altogether, our results suggest that the more the subject is engaged into the task, the more useful and well accepted the automatic error correction.

Highlights

A brain-computer interface (BCI) is a system that connects the brain to a computer directly and avoids the need for peripheral nerve and muscle activities to execute user’s actions
We evaluated the efficiency of this automatic correction through the computation of the good correction rate (GCR)
Our analysis revealed that those two groups differ in terms of specificity and in terms of electrophysiological responses, initial spelling accuracy, θ values, and spelling accuracy gain as well as in their subjective perception of the BCI experience

Summary

Introduction

A brain-computer interface (BCI) is a system that connects the brain to a computer directly and avoids the need for peripheral nerve and muscle activities to execute user’s actions. In a recent P300-Speller study, healthy and motor-impaired participants increased their bitrate by 0.52 (in bits/trial) using online error detection during copy spelling [14]. We achieved a very high specificity (above 0.9) and a fairly good sensitivity (up to 0.6), which yielded a significant improvement in offline spelling accuracy in about half of the participants considering an automatic correction based on the second best guess of the classifier. It turned out that, for about 50% of the error trials, the second best guess of the classifier corresponded to the true target This good correction rate (GCR) correlated with the spelling accuracy over subjects, suggesting that more attentive subjects would produce more distinguishable feedback response signals and should be more prone to benefit from automatic correction. Results are exposed and discussed in the final section of the paper

Methods

Experimental Design

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Results

Summary

Discussion