The Efficiency of the Brain-Computer Interfaces Based on Motor Imagery with Tactile and Visual Feedback


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Resumo

In this study we compared tactile and visual feedbacks for the motor imagery-based brain–computer interface (BCI) in five healthy subjects. A vertical green bar from the center of the fixing cross to the edge of the screen was used as visual feedback. Vibration motors that were placed on the forearms of the right and the left hands and on the back of the subject’s neck were used as tactile feedback. A vibration signal was used to confirm the correct classification of the EEG patterns of the motor imagery of right and left hand movements and the rest task. The accuracy of recognition in the classification of the three states (right hand movement, left hand movement, and rest) in the BCI without feedback exceeded the random level (33% for the three states) for all the subjects and was rather high (67.8% ± 13.4% (mean ± standard deviation)). Including the visual and tactile feedback in the BCI did not significantly change the mean accuracy of recognition of mental states for all the subjects (70.5% ± 14.8% for the visual feedback and 65.9% ± 12.4% for the tactile feedback). The analysis of the dynamics of the movement imagery skill in BCI users with the tactile and visual feedback showed no significant differences between these types of feedback. Thus, it has been found that the tactile feedback can be used in the motor imagery-based BCI instead of the commonly used visual feedback, which greatly expands the possibilities of the practical application of the BCI.

Sobre autores

M. Lukoyanov

Lobachevskii Nizhny Novgorod State University; Nizhny Novgorod State Medical Academy

Email: gordleeva@neuro.nnov.ru
Rússia, Nizhny Novgorod; Nizhny Novgorod

S. Gordleeva

Lobachevskii Nizhny Novgorod State University

Autor responsável pela correspondência
Email: gordleeva@neuro.nnov.ru
Rússia, Nizhny Novgorod

A. Pimashkin

Lobachevskii Nizhny Novgorod State University

Email: gordleeva@neuro.nnov.ru
Rússia, Nizhny Novgorod

N. Grigor’ev

Lobachevskii Nizhny Novgorod State University

Email: gordleeva@neuro.nnov.ru
Rússia, Nizhny Novgorod

A. Savosenkov

Lobachevskii Nizhny Novgorod State University

Email: gordleeva@neuro.nnov.ru
Rússia, Nizhny Novgorod

A. Motailo

Lobachevskii Nizhny Novgorod State University

Email: gordleeva@neuro.nnov.ru
Rússia, Nizhny Novgorod

V. Kazantsev

Lobachevskii Nizhny Novgorod State University

Email: gordleeva@neuro.nnov.ru
Rússia, Nizhny Novgorod

A. Kaplan

Lobachevskii Nizhny Novgorod State University; Moscow State University

Email: gordleeva@neuro.nnov.ru
Rússia, Nizhny Novgorod; Moscow

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