Research institute for
signals, systems and
computational intelligence

Research 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. A BCI can be based on different physiological phenomena and it is highly dependent on brain activity signals, classification and feature extraction methods used to predict the user’s intention. The use of this technology in concrete real-world applications still presents several challenges that have hindered its effective implementation. In this line of research, the most recent paradigms are explored and new algorithms are developed to improve the performance and usability of BCIs.

Team members

Nicolás Nieto
Iván Gareis
Leonardo Rufiner

Databases

EEG signals recording during Inner Speech
EEG signals recorded during Imagined Speech

Selected publications

Extreme Learning Machine design for dealing with unrepresentative features   sinc_NIPRS21.doi sinc_NIPRS21.pdf
N. Nieto, F. Ibarrola, V. Peterson, H. L. Rufiner, R. Spies
Neuroinformatics, Springer – 2021
Preliminary feasibility analysis of inner speech as a control paradigm for brain-computer interfaces sinc_NRS21.pdf
N. Nieto, H. L. Rufiner, R. Spies
50º Jornadas Argentinas de Informática, Simposio Argentino de Inteligencia Artificial, ASAI 2021. – oct 2021
Procesamiento cognitivo del habla e interfaces cerebro computadora   sinc_Ruf21b.pdf
H. L. Rufiner
Technical Report , Córdoba Tech Week – sep 2021
Procesamiento cognitivo del habla e interfaces cerebro computadora   sinc_Ruf21a.pdf
H. L. Rufiner
Technical Report , XVI Jornadas de Informática en Salud, Hospital Italiano, – nov 2021
“Thinking out loud”: an open-access EEG-based BCI dataset for inner speech recognition  sinc_AAGBMR18.doi sinc_NPRKS21.pdf
N. Nieto V. Peterson H. L. Rufiner J. Kamienkoski R. Spies
bioRxiv – 2021
Automatic scoring of apnea and hypopnea events using blood oxygen saturation signals   sinc_RGLDSR20.doi sinc_RGLDSR20.pdf
R.E. Rolon, I. E. Gareis, L. Larrateguy, L. Di Persia, R. Spies, H. L. Rufiner
Biomedical Signal Processing and Control, Volume 62, page 1–9 – 2020
A comparison of feature extraction strategies using Wavelet dictionaries and feature selection methods for single trial P300-based BCI   sinc_AAGBMR18.doi sinc_AAGBMR18.pdf
R. C. Acevedo, Y. Atum, I. E. Gareis, J. Biurrun, V. Medina Bañuelos, H. L. Rufiner
Medical and Biological Engineering and Computing – 2018
Complexity-based discrepancy measures applied to detection of apnea-hypopnea events   sinc_RGDSR18.doi sinc_RGDSR18.pdf
R.E. Rolon, I. E. Gareis, L. Di Persia, R. Spies, H. L. Rufiner
Complexity, Volume 2018 – 2018
Podado pre-entrenamiento de máquinas de aprendizaje extremo   sinc_NBGR18.pdf
N. Nieto, G. Bracalenti, I. E. Gareis, H. L. Rufiner
Anales del Simposio Argentino de Inteligencia Artificial (ASAI 2018 / 47 JAIIO) – 2018
OpenBCI & OpenVIBE for P300 speller paradigm: a quick starting guide.   Pet17.http sinc_Pet17.pdf
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
Coherent averaging estimation autoencoders applied to evoked potentials processing   sinc_GVSR17.doi sinc_GVSR17.pdf
I. E. Gareis, L. D. Vignolo, R. Spies, H. L. Rufiner
Neurocomputing, Volume 240, page 47 – 58 – March 2017
Implementación de un framework para la construcción de redes neuronales con aprendizaje profundo. Caso de aplicación: clasificación de señales cerebrales. (Undergraduate project)   sinc_FRG17.pdf
L. J. Ferrado, H. L. Rufiner, I. E. Gareis
Master thesis from Facultad de Ingeniería y Ciencias Hídricas – Universidad Nacional del Litoral – 2017
Diseño y elaboración de una base de datos pública de registros electroencefalográficos orientados a la clasificación de habla imaginada. (Undergraduate project)   sinc_PRG16.pdf
G. Pressel-Coreto, H. L. Rufiner, I. E. Gareis
Master thesis from Universidad Nacional de Entre Ríos – Facultad de Ingeniería – 2016
Open Access database of EEG signals recorded during imagined speech   sinc_PGR16.pdf
G. Pressel-Coreto, I. E. Gareis, H. L. Rufiner
12th International Symposium on Medical Information Processing and Analysis (SIPAIM) – 2016
L1-Norm Regularization for Sparse Representation and P300 Wave Detection in Brain-Computer Interfaces   sinc_PRS15a.pdf
V. Peterson, H. L. Rufiner, R. Spies
V Congreso de Matemática Aplicada, Computacional e Industrial – may 2015
Genetic Feature Selection for a P300 Brain Computer Interface sinc_ABRA14.pdf
Y. Atum, J. Biurrun, H. L. Rufiner, R. C. Acevedo
Anales del VI Congreso Latinoamericano de Ingeniería Biomédica (CLAIB 2014), page 165 – oct 2014
Detección de potenciales evocados relacionados a eventos en interfaces cerebro-computadora mediante transformada wavelet   sinc_PAJGAR13.pdf
V. Peterson, Y. Atum, F. Jauregui, I. E. Gareis, R. C. Acevedo, H. L. Rufiner
Revista Ingeniería Biomédica, Volume 7, Number 14, page 50–58 – 2013
Extracción de características en Interfaces cerebro computadoras basadas en transformaciones ortogonales: resultados preliminaries   sinc_PAJGRA12.pdf
V. Peterson, Y. Atum, F. Jauregui, I. E. Gareis, H. L. Rufiner, R. C. Acevedo
Proc. 3rd Chilean Meeting on Biomedical Engineering (JCIB 2012) – sep 2012
Determination of an optimal training strategy for a BCI classification task with LDA   sinc_GAAGMR11.pdf
I. E. Gareis, R. C. Acevedo, Y. Atum, G. Gentiletti, V. Medina Bañuelos, H. L. Rufiner
Proc. of the 5th International IEEE EMBS Conference on Neural Engineering – 2011
Efecto de la cantidad y dimensión de los patrones en una interfaz cerebro computadora basada en discriminante lineal de Fisher   sinc_GAAMRG11.pdf
I. E. Gareis, R. C. Acevedo, Y. Atum, V. Medina Bañuelos, H. L. Rufiner, G. Gentiletti
Memorias del V Congreso Latinoamericano de Ingeniería Biomédica (CLAIB2011) – 2011
Evaluation of LDA Ensembles Classifiers for Brain Computer Interface   sinc_APGAGAR11.pdf
C. Arjona, J. Pentácolo, I. E. Gareis, Y. Atum, G. Gentiletti, R. C. Acevedo, H. L. Rufiner
Memorias del XVIII Congreso Argentino de Bioingeniería (SABI 2011) – set 2011
Feature extraction on Brain Computer Interfaces using Discrete Dyadic Wavelet Transform: Preliminary results   GGAR11.doi sinc_GGAR11.pdf
I. E. Gareis, G. Gentiletti, R. C. Acevedo, H. L. Rufiner
Journal of Physics: Conference Series (IOP), Volume 313, Number 12011, page 1–7 – apr 2011
On the use of LDA performance as a metric of feature extraction methods for a P300 BCI classification task   sinc_GAGAMR11.pdf
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
On the use of LDA performance as a metric of feature extraction methods for a P300 BCI classification task   sinc_GAGAMR11.pdf
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
Genetic Feature Selection to Optimally Detect P300 in Brain Computer Interfaces   sinc_AGGAR10.pdf
Y. Atum, I. E. Gareis, G. Gentiletti, R. C. Acevedo, H. L. Rufiner
Proc. of the 32nd Annual International IEEE EMBS Conference, page 1711 – 2010
Detección de P300 en Interfaz Cerebro Computadora mediante Algoritmos Genéticos y Máquinas de Soporte Vectorial   sinc_AGAR09.pdf
Y. Atum, G. Gentiletti, R. C. Acevedo, H. L. Rufiner
Memorias del XVII Congreso Argentino de Bioingenieria (SABI 2009), Number 146, page 51–55 – 2009
Extracción de características en interfaces cerebro computadoras mediante transformada wavelet discreta: Resultados preliminares   sinc_GGAR09.pdf
I. E. Gareis, G. Gentiletti, R. C. Acevedo, H. L. Rufiner
Memorias del XVII Congreso Argentino de Bioingenieria (SABI 2009), Number 167, page 58–62 – 2009
All publications