Online use of error-related potentials in healthy users and people with severe motor impairment increases performance of a P300-BCI

Spüler, Martin; Bensch, Michael; Kleih, Sonja C.; Rosenstiel, Wolfgang; Bogdan, Martin; Kübler, Andrea

doi:10.1016/j.clinph.2011.11.082

Cited by 123 publications

(155 citation statements)

References 19 publications

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“…The feasibility of performing single-trial recognition of ErrPs has been demonstrated in different paradigms and setups, including P300 spellers [7], Motor-imagery BCI [6], human-robot interaction [9], [8], and car driving [10]. Noticeably these signals, linked to cognitive monitoring processes, have also been reported to be rather stable across different recording days [11], and feedback characteristics [12], [9].…”

Section: Introductionmentioning

confidence: 99%

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Spatial filters yield stable features for error-related potentials across conditions

Iwane

Chavarriaga

Iturrate

et al. 2016

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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Abstract-Error-related potentials (ErrP) have been increasingly studied in psychophysical experiments as well as for brainmachine interfacing. In the latter case, the generalisation capabilities of ErrP decoders is a crucial element to avoid frequent recalibration processes, thus increasing their usability. Previous studies have suggested that ErrP signals are rather stable across recording sessions. Also, studies using protocols of serial stimuli presentation show that these potentials do not change significantly with the presentation rate. Here we complement these studies by analysing the decoding generalisation capabilities. Using data from monitoring experiments, we evaluate how much the performance degrades when tested in a condition different than the one the decoder was trained with. Moreover, we compare different spatial filtering techniques to see which preprocessing steps yield less-sensitive features for ErrP decoding.

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Section: Introductionmentioning

confidence: 99%

“…These Error-related potentials, ErrPs are particularly interesting in the field of brain-machine interfaces [5]. Specifically, their decoding has been proposed as a mean of improving reliability by correcting erroneous commands [6], [7] or as a mean to adapt the BCI system [8].…”

Section: Introductionmentioning

confidence: 99%

Spatial filters yield stable features for error-related potentials across conditions

Iwane

Chavarriaga

Iturrate

et al. 2016

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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“…However, this was not sufficient to improve the information transfer rate [13]. Finally, 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]. However, these studies implemented and evaluated automatic error detection but not automatic error correction.…”

Section: Introductionmentioning

confidence: 99%

“…However, these studies implemented and evaluated automatic error detection but not automatic error correction. In other words, they could eventually suppress a wrong letter by detecting the ensuing ErrP but did not attempt to immediately replace this letter by another highly probable one [13,14]. In the current study, we evaluated both error detection and correction, where correction was based on the second best guess of a probabilistic classifier.…”

Section: Introductionmentioning

confidence: 99%

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

Margaux

Maby

Daligault

et al. 2012

Advances in Human-Computer Interaction

109

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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.

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The Brain Computer Interface: Barriers to Becoming Pervasive

Lightbody

Galway

McCullagh

2014

Human–Computer Interaction Series

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Online use of error-related potentials in healthy users and people with severe motor impairment increases performance of a P300-BCI

Cited by 123 publications

References 19 publications

Spatial filters yield stable features for error-related potentials across conditions

Spatial filters yield stable features for error-related potentials across conditions

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

The Brain Computer Interface: Barriers to Becoming Pervasive

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