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Journal Articles International Journal of Human-Computer Studies Year : 2021

Experimenters Influence on Mental-Imagery based Brain-Computer Interface User Training


Context Motor Imagery based Brain-Computer Interfaces (MI-BCIs) enable their users to interact with digital technologies, e.g., neuroprosthesis, by performing motor imagery tasks only, e.g., imagining hand movements, while their brain activity is recorded. To control MI-BCIs, users must train to control their brain activity. During such training, experimenters have a fundamental role, e.g., they motivate participants. However, their influence had never been formally assessed for MI-BCI user training. In other fields, e.g., social psychology, experimenters’ gender was found to influence experimental outcomes, e.g., behavioural or neurophysiological measures. Objective Our aim was to evaluate if the experimenters’ gender influenced MI-BCI user training outcomes, i.e., performances and user-experience. Methods We performed an experiment involving 6 experimenters (3 women) each training 5 women and 5 men (60 participants) to perform right versus left hand MI-BCI tasks over one session. We then studied the training outcomes, i.e., MI-BCI performances and user-experience, according to the experimenters' and subjects' gender. Results A significant interaction between experimenters’ and participants' gender was found on the evolution of trial-wise performances. Another interaction was found between participants’ tension and experimenters’ gender on the average performances. Conclusion Experimenters’ gender could influence MI-BCI performances depending on participants’ gender and tension. Significance Experimenters’ influence on MI-BCI user training outcomes should be better controlled, assessed and reported to further benefit from it while preventing any bias.
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hal-03142448 , version 1 (16-02-2021)



Léa Pillette, Aline Roc, Bernard N'Kaoua, Fabien Lotte. Experimenters Influence on Mental-Imagery based Brain-Computer Interface User Training. International Journal of Human-Computer Studies, 2021, pp.102603. ⟨10.1016/j.ijhcs.2021.102603⟩. ⟨hal-03142448⟩
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