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From Brain Science to Intelligent Machines

Challenges in simple and hybrid brain computer interfaces.

Date: Thursday 1/3/2012
Venue: MS020
Time: 1.00 pm
Speaker: Dr. Shahjahan Shahid
Affiliation: Intelligent Systems Engineering Centre (ISRC), University Of Ulster

Challenges in simple and hybrid brain computer interfaces.


By Dr. Shahjahan Shahid
Intelligent Systems Engineering Centre (ISRC), University Of Ulster


People who are totally paralysed (e.g., by amyotrophic lateral sclerosis (ALS) or brain-stem stroke) or have other severe movement disorders need alternative methods for communication to express their wishes and control. These individuals need an alternative communication channel that does not rely on the brain's normal output pathways of peripheral nerves and muscles. A brain-computer interface (BCI) is a communication system that can help these users to interact with the outside environment by translating brain signals into machine commands. Since over one decade, the use of electroencephalographic (EEG) signals has become the most common approach for BCI implementation. BCIs are normally categorized on the nature of EEGs (e.g., in terms of the stimulation features for EEG generation and the electrode placement area above brain/skull). These BCIs (here it is addressed as 'simple BCI') basically try to figure out the subject's voluntary intentions and decisions from the measurements of multichannel EEG. Advanced multivariate signal processing algorithms along with artificial intelligent techniques are mainly used in developing these interfaces. Recently, researchers introduce a new type of BCI (known as hybrid BCI) that comprises of multiple type of simple BCIs or a simple BCI and other interface driven by any electro-physiological signal (such as ECG, EMG, EOG, eye-tracker). The main intention of introducing this type of hybrid BCI was to get improved performance in interfacing system. However, in spite of extensive corpus effort for almost two decade, there still exist a number of not-well solved problems in BCI designing these include subjects inability to produce effective EEG signals, signal recoding techniques, nonlinear characteristics of EEG, slow information transfer rate and signal processing techniques.
This presentation will cover the basic principle of simple and hybrid BCI, useful signal processing techniques for BCIs design. A discussion will follow on the challenges in designing these BCIs for rehabilitation..

Short biography:

Dr Shahjahan Shahid is a Research Associate in the Cognitive Robotics Group of Intelligent System Research Centre at Londonderry. He obtained his BSc. And MSc in Applied Physics and Electronics. After completion of his postgraduate degree, he worked for Bangladesh Atomic Energy Commission where he was responsible to repair-maintenance and up-gradation of Nucleonic equipments. After nine years of service, he returned to university for higher studies and completed his PhD in 2004 from University of Limerick, Ireland. His research interests are in electrophysiological signal processing, higher order statistics techniques for time series analysis. Dr. Shahid worked at many laboratories in Singapore, Malaysia Hungary, Austria and UK.