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Enhancing single-trial mental workload estimation through xDAWN spatial filtering

Roy, Raphaëlle N. and Bonnet, Stéphane and Charbonnier, Sylvie and Campagne, Aurélie Enhancing single-trial mental workload estimation through xDAWN spatial filtering. (2015) In: International IEEE EMBS Conference on Neural Engineering, 22 April 2015 - 24 April 2015 (Montpellier, France).

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Official URL: http://dx.doi.org/10.1109/NER.2015.7146634


Mental state monitoring is a topical issue in neuroengineering, more particularly for passive brain-computer interface (pBCI) applications. One of the mental states that are currently under focus is mental workload. The level of workload can be estimated from electroencephalographic activity (EEG) and markers derived from this signal. In active BCI applications, a well-known neurophysiological marker, the event-related potential (ERP), is commonly enhanced using a spatial filtering step. In this study, we evaluated how a spatial filtering method such as the xDAWN algorithm could improve mental workload classification performance. Twenty participants performed a Sternberg memory task for 18 minutes with pseudo-randomized trials of low vs. high workload (2/6 digits to memorize). Three signal processing chains were compared on their performance to estimate mental workload from the single-trial ERPs of the test item (i.e. present/absent in the memorized list). All 3 included an FLDA classifier with a shrinkage covariance estimation and a 10-fold cross-validation. One chain used the ERPs of a relevant electrode for workload estimation (Cz) and the 2 others used the ERPs of the 32 electrodes and an xDAWN spatial filtering step with either 1 or 2 virtual electrodes kept for classification. Statistical analyses revealed that spatial filtering significantly improved mental workload estimation, with up to 98% of correct classification using the xDAWN algorithm and 2 virtual electrodes.

Item Type:Conference or Workshop Item (Poster)
Additional Information:Thanks to the IEEE (Institute of Electrical and Electronics Engineers). This paper is available at : https://ieeexplore.ieee.org/document/7146634/ “© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
Audience (conference):International conference proceedings
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Institution:French research institutions > Commissariat à l'Energie Atomique et aux énergies alternatives - CEA (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Université Grenoble Alpes - UGA (FRANCE)
Other partners > Université de Savoie Mont Blanc - USMB (FRANCE)
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Deposited On:12 Sep 2018 09:05

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