Robotic orthosis compared to virtual hand for Brain–Computer Interface feedback

Jessica Cantillo-Negrete, Ruben I. Carino-Escobar, Paul Carrillo-Mora, José A. Barraza-Madrigal, Oscar Arias-Carrión

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Brain–Computer Interfaces (BCI) allow the control of external devices by decoding the users’ intentions from their central nervous system. Feedback, one of the main elements of a closed-loop BCI, is used to enhance the user's performance. The present work aimed to compare the effect of two different feedback sources; congruent anatomical visual hand representation and passive hand movement on BCI performance and cortical activations. Electroencephalography of 12 healthy right-handed subjects was recorded to set a BCI activated by right-hand motor imagery. Afterward, the subjects were asked to control the system by imagining the movement. The system provided either visual feedback, shown on a computer screen or kinesthetic feedback, provided by a robotic hand orthosis. Differences in performance and cortical activations were assessed, using classification accuracy and event-related desynchronization/synchronization in μ and β bands, respectively. Performance was significantly better with kinesthetic feedback as it allowed for higher correct classification of motor imagery. Cortical activations in the ipsilateral central channel in μ were different between the two feedback modalities. Our results imply that healthy subjects can achieve a greater degree of control using a motor imagery-based BCI with kinesthetic feedback than with anatomically congruent visual feedback. Furthermore, cortical activation differences show that kinesthetic feedback seems to elicit higher recruitment of sensorimotor cortex brain cells, which probably reflects enhanced local information modulation related to fine motor processing. Therefore, kinesthetic feedback provided by a robotic orthosis could be a more suitable feedback strategy for BCI systems designed for neuromodulation and neurorehabilitation.

Original languageEnglish
Pages (from-to)263-272
Number of pages10
JournalBiocybernetics and Biomedical Engineering
Volume39
Issue number2
DOIs
StatePublished - 1 Apr 2019
Externally publishedYes

Keywords

  • BCI
  • ERD
  • Kinesthetic
  • Motor imagery
  • Neurofeedback
  • Visual

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