Martel, A., Arvaneh, M., Taylor, A. et al. (2 more authors) (2017) Quantifying the maladaptive neurophysiological correlates leading to lapses of attention during the SART: towards real-time mental state monitoring of mind-wandering. In: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). The 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’17), 11-15 Jul 2017, Jeju Island, Korea. IEEE , pp. 1026-1029.
Abstract
Mind-wandering (MW) constitutes one of the most ubiquitous mental activity humans engage in but it comes at a significant cost. Internal distractions are believed to be a leading cause of performance errors and unhappiness. A brain computer interface (BCI) able to predict the disengagement of attention, e.g. lapses of attention resulting from mindwandering episodes, harbors numerous useful applications. In this study, the SART was applied to quantify EEG correlates of lapses of attention to assess the viability of a BCI able to monitor attentional states in real-time. Both spatio-temporal classification and filter bank common spatial patterns were applied on a single-trial basis with accuracy reaching 92%. This work represents a potential step towards enhanced human-machine systems and BCI-based treatments of perseverative disorders such as depression.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 May 2017 10:49 |
Last Modified: | 15 Dec 2023 13:10 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/EMBC.2017.8037001 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116450 |