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



Medical and Biological Engineering and Computing – 2018
Publications in 2017
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 Congreso de Matemática Aplicada, Computacional e Industrial – may 2015
Publications in 2014
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 

Memorias del XVIII Congreso Argentino de Bioingeniería (SABI 2011) – set 2011
Publications in 2010
Proc. of the 32nd Annual International IEEE EMBS Conference, page 1711 – 2010
Publications in 2009
Detección de P300 en Interfaz Cerebro Computadora mediante Algoritmos Genéticos y Máquinas de Soporte Vectorial 

Memorias del XVII Congreso Argentino de Bioingenieria (SABI 2009), Number 146, page 51–55 – 2009