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Can the MIQ-RS questionnaire be used to estimate the performance of a MI-based BCI?

Sébastien Rimbert 1 Nathalie Gayraud 2 Maureen Clerc 2 Stéphanie Fleck 3 Laurent Bougrain 3, 1
1 NEUROSYS - Analysis and modeling of neural systems by a system neuroscience approach
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
2 ATHENA - Computational Imaging of the Central Nervous System
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Predicting a subject's ability to use the interface with good accuracy is one of the major issues in the motor Brain-Computer interface (BCI) domain. A few recent studies show that subjective questionnaires could be used to predict the performance of motor imagery (MI) based BCI. Indeed, the Kinesthetic and Visual Imagery Questionnaire (KVIQ), could allow a better predictability of BCI-illiterate cases [1]. Another more recent questionnaire called the Motor Imagery Questionnaire Revised-Second Edition (MIQ-RS) is a suitable option for examining MI ability [2]. In 2016, Marchesotti et al. found that the representation of subjective behaviour, calculated using the MIQ-RS questionnaire, and the control of the BCI were intimately linked [3]. However, in these studies [1, 3], the performance of the classifier was calculated for a right-hand MI versus a left-hand MI task. In this abstract, we classify between resting state and imagined movement, which is a relevant classification task in BCI research [4]. The aim of this study is to answer the following question for a resting state versus MI classification task: can the MIQ-RS be used to estimate the performance of an MI-based BCI?
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Submitted on : Monday, October 8, 2018 - 10:07:06 AM
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Can the MIQ-RS questionnaire b...
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  • HAL Id : hal-01889864, version 1


Sébastien Rimbert, Nathalie Gayraud, Maureen Clerc, Stéphanie Fleck, Laurent Bougrain. Can the MIQ-RS questionnaire be used to estimate the performance of a MI-based BCI?. 2018 Seventh International BCI Meeting, May 2018, Pacific Grove, United States. ⟨hal-01889864⟩



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