Details of Grant 

EPSRC Reference:	GR/R32888/01
Title:	Decomposing EEG signals for the analysis of epileptic data
Principal Investigator:	Brown, Dr J
Other Investigators:	Mulgrew, Professor B Unsworth, Dr C
Researcher Co-Investigators:
Project Partners:
Department:	Reproductive and Developmental Sciences
Organisation:	University of Edinburgh
Scheme:	Postdoctoral Mobility PreFEC
Starts:	01 May 2001	Ends:	30 June 2002	Value (£):	76,247
EPSRC Research Topic Classifications:	Digital Signal Processing
EPSRC Industrial Sector Classifications:	Communications Healthcare
Related Grants:
Panel History:
Summary on Grant Application Form
A typical electroencephalogram (EEG) consists of roughly 16 electrical recordings from sensors at different locations on the scalp. Each recording, represents a mixture of signals which are responsible for various brain activities.Thus, at present a consultant has to interpret 16 channels of data, all of which consist of complex mixed signals. Depending upon the patient's activity such signals could become very complicated to interpret. In the case of epilepsy, it is particulary hard to locate the epileptiform discharges which occur in run up to an epileptic attack. What would be more desirable would be if each recording actually consisted of a single signal that corresponded to an actual event occurring in the brain (e.g. muscle movement, impulse). This proposal will exploit the techinique of linear independent component analysis (ICA) and its extended form nonlinear ICA which allows for suchra decomposition to be realised. It is intended to apply these techniques to a large sample size of patients with different forms of epilepsy and from varied EEG monitors. From this research, it is hoped to simplify the EEG to a form which is more interpretable for the consultant whilst providing a deeper insight into the activities of the brain during epilepsy. In addition, it is hoped to try and predict the onset of an epileptic attack by applying prediction algorithms to the simplified EEG. This project reflects the goals of EPSRC's mission in the advancement of knowledge, possibilty of improving quality of life and allowing a cross-fertilization of ideas and dessemination of knowledge between the medical, engineering and physical communities.
Key Findings
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Potential use in non-academic contexts
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Impacts
Description This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk Summary Date Materialised
Sectors submitted by the Researcher
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Project URL:
Further Information:
Organisation Website:	http://www.ed.ac.uk