Conferencia: “Designing Brain Computer Interfaces Using Visually Evoked Potentials” 12 de julio 2013 – 11:00 2ª Planta, Edificio CITIC- Sala Grande (Campus de Elviña) Objetivo We will discuss the design of brain computer interfaces for applications including robot control and text input using brain signals evoked by visual stimulation and sensed via electroencephalogram (EEG). Specifically, we will discuss statistical signal processing and classification algorithm design, especially focusing on the use of pseudorandom binary sequences for steady state visual evoked potentials (SSVEP), and the use of language models that are tightly coupled in text entry. We will demonstrate real-time performance for these applications on healthy and locked-in subjects. Ponente: Deniz Erdogmus (Northeastern University, Boston, EEUU) Graduated with B.S. in Electrical & Electronics Engineering (EEE), and the B.S. in Mathematics in 1997, and M.S. in EEE in 1999 from the Middle East Technical University, Ankara, Turkey. He received his Ph.D. in Electrical & Computer Engineering from the University of Florida in 2002, where he stayed as a postdoctoral research associate until 2004. Prior to joining the Northeastern faculty in 2008, he held an Assistant Professor position at the Oregon Health and Science University. His expertise is in information theoretic and nonparametric machine learning and adaptive signal processing, specifically focusing on cognitive signal processing including brain interfaces and assistive technologies. Deniz has been serving as an associate editor IEEE Transactions on Signal Processing, Transactions on Neural Networks, Signal Processing Letters, and Elsevier Neurocomputing. He is a member of the IEEE-SPS Machine Learning for Signal Processing Technical Committee. Organiza: Área de Inteligencia Artificial del Centro de Investigación CITIC

1. Conferencia: “Designing Brain Computer
Interfaces Using Visually Evoked Potentials”
12 de julio 2013 – 11:00
2ª Planta, Edificio CITIC- Sala Grande (Campus de Elviña)
Objetivo
We will discuss the design of brain computer interfaces for applications including robot control and text input using brain signals evoked by
visual stimulation and sensed via electroencephalogram (EEG). Specifically, we will discuss statistical signal processing and classification
algorithm design, especially focusing on the use of pseudorandom binary sequences for steady state visual evoked potentials (SSVEP), and the
use of language models that are tightly coupled in text entry. We will demonstrate real-time performance for these applications on healthy and
locked-in subjects.
Ponente: Deniz Erdogmus (Northeastern University, Boston, EEUU)
Graduated with B.S. in Electrical & Electronics Engineering (EEE), and the B.S. in Mathematics in 1997, and M.S. in EEE in 1999 from the
Middle East Technical University, Ankara, Turkey. He received his Ph.D. in Electrical & Computer Engineering from the University of Florida
in 2002, where he stayed as a postdoctoral research associate until 2004. Prior to joining the Northeastern faculty in 2008, he held an
Assistant Professor position at the Oregon Health and Science University. His expertise is in information theoretic and nonparametric
machine learning and adaptive signal processing, specifically focusing on cognitive signal processing including brain interfaces and assistive
technologies. Deniz has been serving as an associate editor IEEE Transactions on Signal Processing, Transactions on Neural Networks,
Signal Processing Letters, and Elsevier Neurocomputing. He is a member of the IEEE-SPS Machine Learning for Signal Processing Technical
Committee.
Organiza: Financiado por:
Área de Inteligencia Artificial del Centro de Investigación CITIC Ayudas del programa de consolidación y estructuración de unidades de
investigación competitivas de Agrupación Estratégica CITIC (CN2012/211).