2019
DOI: 10.48550/arxiv.1905.09658
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Towards Artificial Learning Companions for Mental Imagery-based Brain-Computer Interfaces

Abstract: Mental Imagery based Brain-Computer Interfaces (MI-BCI) enable their users to control an interface, e.g., a prosthesis, by performing mental imagery tasks only, such as imagining a right arm movement while their brain activity is measured and processed by the system. Designing and using a BCI requires users to learn how to produce different and stable patterns of brain activity for each of the mental imagery tasks. However, current training protocols do not enable every user to acquire the skills required to u… Show more

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“…2020;Micoulaud-Franchi & Fovet, 2018;Garcia Pimenta et al, 2021). Moreover, various other psychological factors, whether related to the NF training or not, such as personality factors and negative affective states (of therapist guidance, family involvement, a robotic learning companion(Pillette et al, 2019), peer support, or even group sessions. On the other hand, NF training can be combined with other interventions that focus on improving psychological/social factors, for instance an intervention to enhance the psychological factor self-esteem(Niveau et al, 2021).…”
mentioning
confidence: 99%
“…2020;Micoulaud-Franchi & Fovet, 2018;Garcia Pimenta et al, 2021). Moreover, various other psychological factors, whether related to the NF training or not, such as personality factors and negative affective states (of therapist guidance, family involvement, a robotic learning companion(Pillette et al, 2019), peer support, or even group sessions. On the other hand, NF training can be combined with other interventions that focus on improving psychological/social factors, for instance an intervention to enhance the psychological factor self-esteem(Niveau et al, 2021).…”
mentioning
confidence: 99%