Conference paper
Detection of attention shift for asynchronous P300-based BCI
Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), v 2012, pp 3850-3853
2012
PMID: 23366768
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Brain-computer interface (BCI) provides patients suffering from severe neuromuscular disorders an alternative way of interacting with the outside world. The P300-based BCI is among the most popular paradigms in the field and most current versions operate in synchronous mode and assume participant engagement throughout operation. In this study, we demonstrate a new approach for assessment of user engagement through a hybrid classification of ERP and band power features of EEG signals that could allow building asynchronous BCIs. EEG signals from nine electrode locations were recorded from nine participants during controlled engagement conditions when subjects were either engaged with the P3speller task or not attending. Statistical analysis of band power showed that there were significant contrasts of attending only for the delta and beta bands as indicators of features for user attendance classification. A hybrid classifier using ERP scores and band power features yielded the best overall performance of 0.98 in terms of the area under the ROC curve (AUC). Results indicate that band powers can provide additional discriminant information to the ERP for user attention detection and this combined approach can be used to assess user engagement for each stimulus sequence during BCI use.
Metrics
Details
- Title
- Detection of attention shift for asynchronous P300-based BCI
- Creators
- Yichuan Liu - Drexel University, School of Biomedical Engineering, Science, and Health SystemsHasan Ayaz - Drexel University, School of Biomedical Engineering, Science, and Health SystemsAdrian Curtin - Drexel University, School of Biomedical Engineering, Science, and Health SystemsPatricia A Shewokis - Drexel University, College of Nursing and Health ProfessionsBanu Onaral - Drexel University, School of Biomedical Engineering, Science, and Health Systems
- Publication Details
- Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), v 2012, pp 3850-3853
- Conference
- 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (San Diego, California, United States, 28 Aug 2012–01 Sep 2012)
- Publisher
- IEEE; United States
- Number of pages
- 4
- Resource Type
- Conference paper
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems; Nutrition Sciences; Health Sciences Division
- Web of Science ID
- WOS:000313296504019
- Scopus ID
- 2-s2.0-84870795701
- Other Identifier
- 9781457717871; 1457717875; 991014878030804721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Biomedical
- Engineering, Electrical & Electronic