University of Malta
 

Modelling of EEG Data
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Modelling the dynamics of EEG signals allows a better understanding of the underlying process and the model itself can be used either for predictive purposes or for feature extraction to identify the modeled process.  As part of our contribution to the BIOPATTERN Network of Excellence, autoregressive moving average (ARMA) modeling has been applied to the diagnosis of epileptic children as compared to a sex and age matched control group during a rest task.  ARMA extracted spectral features have been found to be a suitable biomarker to classify children with mild epilepsy even in scenarios where the visual inspection of their EEG data has labeled them as being normal.  Epileptic children were found to have significantly higher spectral power in all frequency bands up to 45Hz and recordings from electrodes placed across the whole brain area gave similar results.  When compared to nonparametric spectral feature extraction techniques like Fourier transform and Wavelets, the ARMA modeling technique was found to be superior with classification scores reaching as high as 100% classification over most channels.
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Funding Award for BrainApp
CBC awarded research funding under the FUSION Technology Development Programme (TDP) 2017

Closing date for MSc course applications

 

The deadline for late applications for the MSc in Signals, Systems and Control is the 31st August 2017. Click here for more information.


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Postdoctoral Position in Robotics and Control

 

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The Department of Systems and Control Engineering and the Centre for Biomedical Cybernetics are seeking students who are interested in pursuing studies leading to an MSc in Engineering degree (mainly by research) on any of the topics detailed here.


Postdoctoral Research Position in EEG

 

[CLOSED] Postdoctoral Research Position in EEG Signal Processing with the Centre for Bionedical Cybernetics. Click here for more information.


 
 
Last Updated: 10 November 2008

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