Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Motor Imagery-Based Brain-Computer Interface with Dry Sensors and Multimodal Feedback: Towards Tele-Rehabilitation

Pasquale Arpaia
* ORCID logo ,
Damien Coyle
,
Antonio Esposito
,
Angela Natalizio
,
Marco Parvis
ORCID logo ,
Marisa Pesola
ORCID logo ,
Ersilia Vallefuoco
Version 1 : Received: 8 March 2023 / Approved: 9 March 2023 / Online: 9 March 2023 (09:20:51 CET)

A peer-reviewed article of this Preprint also exists.

Arpaia, P.; Coyle, D.; Esposito, A.; Natalizio, A.; Parvis, M.; Pesola, M.; Vallefuoco, E. Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System. Sensors 2023, 23, 5836. Arpaia, P.; Coyle, D.; Esposito, A.; Natalizio, A.; Parvis, M.; Pesola, M.; Vallefuoco, E. Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System. Sensors 2023, 23, 5836.

Abstract

The present study illustrates a brain-computer interface designed and developed to be wearable, portable, and user-friendly. Eight dry electroencephalographic sensors were adopted to acquire the brain activity associated with motor imagery. Multimodal feedback in extended reality was exploited to improve the detection of neurological phenomena. Twenty-seven healthy subjects used the proposed system in five sessions to investigate the effects of feedback on motor imagery. The sample was divided into two equal-sized groups: the "neurofeedback" group, which performed motor imagery while receiving feedback, and the "control" group, which performed motor imagery with no feedback. Several questionnaires were administrated to participants aiming to investigate the usability of the proposed system and individual’s ability to imagine movements. The highest mean classification accuracy across subjects of control group was about 62 % with 3 % associated type A uncertainty, and 69 % with 3 % uncertainty for neurofeedback group. Moreover, in some cases the results were significantly higher for the neurofeedback group. The perceived usability by all participants was high. Overall, the study highlights the advantages and the pitfalls of using a wearable brain-computer interface with dry sensors. Notably, the results and the perceived usability pave the way for the employment of the proposed system in tele-rehabilitation.

Keywords

eletroencephalograhy; dry sensors; motor imagery; brain-computer interfaces; extended reality; telerehabilitation

Subject

Engineering, Bioengineering

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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