Brain Computer Interfaces

A Brain Computer Interface (BCI) is a system that provides direct communication pathways between the brain and an external device. These interfaces are a communication alternative, particularly interesting for people with severe motor disabilities. The use of this technology in concrete real-world applications still presents several challenges that have hindered its effective implementation.

Objetive

In this line of research, the most recent paradigms are explored and new algorithms are developed to improve the performance and usability of BCIs.

Director

Leonardo Rufiner

Publications

A comparison of feature extraction strategies using Wavelet dictionaries and feature selection methods for single trial P300-based BCI

R. C. Acevedo, Y. Atum, I. E. Gareis, J. Biurrun, V. Medina Bañuelos, H. L. Rufiner

Medical and Biological Engineering and Computing – 2018

Publications in 2017

OpenBCI & OpenVIBE for P300 speller paradigm: a quick starting guide.

V. Peterson

Technical Report , Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional, sinc(i) (UNL-CONICET), Instituto de Matemática Aplicada del Litoral, IMAL (UNL-CONICET) – 2017

Publications in 2015

L1-Norm Regularization for Sparse Representation and P300 Wave Detection in Brain-Computer Interfaces

V. Peterson, H. L. Rufiner, R. Spies

V Congreso de Matemática Aplicada, Computacional e Industrial – may 2015

Publications in 2014

Genetic Feature Selection for a P300 Brain Computer Interface

Y. Atum, J. Biurrun, H. L. Rufiner, R. C. Acevedo

Anales del VI Congreso Latinoamericano de Ingeniería Biomédica (CLAIB 2014), page 165 – oct 2014

Publications in 2011

On the use of LDA performance as a metric of feature extraction methods for a P300 BCI classification task

I. E. Gareis, Y. Atum, G. Gentiletti, R. C. Acevedo, V. Medina Bañuelos, H. L. Rufiner

Memorias del XVIII Congreso Argentino de Bioingeniería (SABI 2011) – set 2011