Is Stress State an Important Factor in the BCI-P300 Speller Performance?

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Abstract

Brain-Computer Interface (BCI) is an advanced human–machine interaction technology requiring higher-order cognitive functions for an efficient task execution. The relation between cognition, human performance and psychological state has been studied for many years. Nevertheless, the effect of acute stress on cognitive performance involving BCI systems has never been studied. Nowadays, people are more and more affected by stressful situations. Stress is an important human factor which can impact the ability to appropriately process cognitive information related to language, working memory, attention, or executive control. Individuals are continuously interacting with technology to execute daily actions. BCI represent an alternative way to allow any individual, even with motor disabilities, to interact with that technology. BCI-P300 Speller is driven by EEG signals and enables communication without physical intervention. It is used in both clinical investigations and fundamental research. In this work, we study the impact of acute stress effects on cognitive ability to control a BCI-P300 speller. Although we have observed a broad spectrum of response to stress, analyses show a correlation between BCI-speller performance and user’s stress state. We have also noted that BCI performance seems to be improved if users have a good cognitive engagement in the task and if they showed an ability to develop efficient strategies, such as selective attention or increased effort, in order to cope with the stressful situations. In conclusion, these preliminary results performed on a small sample (n = 7) show that BCI-P300 Speller is a robust and reliable tool and suggest that an optimal utilization of BCI systems could be assured despite the fluctuations of users’ state. We assume that neural mechanisms involved in the BCI task, may set the brain in an adequate level of generalized arousal, which allows establishment of compensatory mechanisms in stressful states.

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Garcia, L., Zak, M., Grenier, C., Hanrio, S., Henry, D., Randriamanantena, R., … Ron-Angevin, R. (2019). Is Stress State an Important Factor in the BCI-P300 Speller Performance? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11506 LNCS, pp. 442–454). Springer Verlag. https://doi.org/10.1007/978-3-030-20521-8_37

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