Literature DB >> 25264791

[Characterization of electrical brain activity related to hand motor imagery in healthy subjects].

Jessica Cantillo-Negrete, Josefina Gutiérrez-Martínez1, Teodoro B Flores-Rodríguez, Rubén I Cariño-Escobar, David Elías-Viñas.   

Abstract

Brain computer interface systems (BCI) translate the intentions of patients affected with locked-in syndrome through the EEG signal characteristics, which are converted into commands used to control external devices. One of the strategies used, is to decode the motor imagery of the subject, which can modify the neuronal activity in the sensory-motor areas in a similar way to which it is observed in real movement. The present study shows the activation patterns that are registered in motor and motor imagery tasks of right and left hand movement in a sample of young healthy subjects of Mexican nationality. By means of frequency analysis it was possible to determine the difference conditions of motor imagery and movement. Using U Mann- Whitney tests, differences with statistical significance (p < 0.05) where obtained, in the EEG channels C3, Cz, C4, T3 and P3 in the mu and beta rhythms, for subjects with similar characteristics (age, gender, and education). With these results, it would be possible to define a classifier or decoder by gender that improves the performance rate and diminishes the training time, with the goal of designing a functional BCI system that can be transferred from the laboratory to the clinical application in patients with motor disabilities.

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Year:  2014        PMID: 25264791

Source DB:  PubMed          Journal:  Rev Invest Clin        ISSN: 0034-8376            Impact factor:   1.451


  2 in total

1.  An approach to improve the performance of subject-independent BCIs-based on motor imagery allocating subjects by gender.

Authors:  Jessica Cantillo-Negrete; Josefina Gutierrez-Martinez; Ruben I Carino-Escobar; Paul Carrillo-Mora; David Elias-Vinas
Journal:  Biomed Eng Online       Date:  2014-12-04       Impact factor: 2.819

2.  Motor Imagery-Based Brain-Computer Interface Coupled to a Robotic Hand Orthosis Aimed for Neurorehabilitation of Stroke Patients.

Authors:  Jessica Cantillo-Negrete; Ruben I Carino-Escobar; Paul Carrillo-Mora; David Elias-Vinas; Josefina Gutierrez-Martinez
Journal:  J Healthc Eng       Date:  2018-04-03       Impact factor: 2.682

  2 in total

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