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The role of the tutorials is to provide a platform for a more intensive scientific exchange amongst researchers interested in a particular topic and as a meeting point for the community. Tutorials complement the depth-oriented technical sessions by providing participants with broad overviews of emerging fields. A tutorial can be scheduled for 1.5 or 3 hours.


Noninvasive Brain Computer Interfaces  (IJCCI)
Lecturer(s): Petia Georgieva

Noninvasive Brain Computer Interfaces


Petia Georgieva
University of Aveiro
Brief Bio
Petia Georgieva (S’14) received the M.Sc. and PhD degrees in electrical engineering from Technical University of Sofia, Sofia, Bulgaria in 1989 and 2007, respectively. Since 2003 she has been a lecturer at the University of Aveiro, Portugal and researcher in the Institute of Electronics Engineering and Telematics of Aveiro (IEETA), Portugal. Dr. Georgieva was i) an invited professor in Rowan University, New Jersey in 2016; ii) a visiting faculty in Computer Science Department, Carnegie Mellon University (CMU), Pittsburgh, USA, 2012; iii) an invited researcher in Computer Science Department, University of Arkansas at Little Rock. USA, 2011 and iv) an invited researcher in the School of Computing and Communications, University of Lancaster, UK, 2011. Over the last ten years Dr. Georgieva works in the area of machine learning and data mining with strong focus on noninvasive Brain Computer Interfaces (BCI), brain neural activity recovering and affective neuro-computing based on EEG data. She has published more than 120 papers in peer reviewed journals and international conferences. Dr. Georgieva is a Senior member of IEEE, Senior Member of International Neural Network Society (INNS) and Elected Member of the Executive Committee of the European Neural Network Society (ENNS) for 2014-2016.

During the last decade advances in many scientific fields have supported the idea that a direct interface between the human brain and an artificial system, called Brain Computer Interface (BCI), is a viable concept, although a significant research and development effort has to be conducted before these technologies enter routine use. The principal reason for the BCI research is the potential benefits to those with severe motor disabilities, such as brainstem stroke, amyotrophic lateral sclerosis or severe cerebral palsy. However, recent advances in sensor technology and machine learning assert that using our brain for communication may have a significant impact in the way people will operate computers, wheelchairs, prostheses, robotic systems and other devices in the future. A promising way to analyze the brain physiological activity is the electroencephalogram (EEG) measurements from the cortex whose sources are the action potentials of the nerve cells in the brain. Over the last years, the interest in extracting knowledge hidden in the EEG signals is rapidly growing, as well as their applications. This tutorial will present the state of the art in the EEG-based Noninvasive BCI. The talk will highlight research on noninvasive BCI for motor control, reconstruction of brain active zones based on EEG and learning to decode human emotions with Echo State Networks.

Secretariat Contacts
e-mail: ijcci.secretariat@insticc.org