Journal of Control Engineering and Applied Informatics
Studying Epileptic Activity Propagation: From Robust But Time-Consuming To Intelligent Information Processing Methodologies
Abstract
In this study intelligent biomedical information processing techniques are used in
tracking epileptic activity propagation in patients with epilepsy. Although identification and
detection of epileptic signatures from epileptic signals is also important and well managed by such
techniques, reasons are given herein, that discuss why the above is not the most important issue in
this field, but rather is the study of the propagation and development of epileptic activity itself. In
this context, Independent Component Analysis (ICA) is utilised to study averaged epileptic signals
from temporal lobe epileptics. The results are compared to those previously obtained by Magnetic
Field Tomography (MFT) methodologies, and important findings are verified. Finally, the
prospect of obtaining such sets of findings in a more intelligent and automatic methodology, so
that they may, in future, become a blind procedure is discussed.
tracking epileptic activity propagation in patients with epilepsy. Although identification and
detection of epileptic signatures from epileptic signals is also important and well managed by such
techniques, reasons are given herein, that discuss why the above is not the most important issue in
this field, but rather is the study of the propagation and development of epileptic activity itself. In
this context, Independent Component Analysis (ICA) is utilised to study averaged epileptic signals
from temporal lobe epileptics. The results are compared to those previously obtained by Magnetic
Field Tomography (MFT) methodologies, and important findings are verified. Finally, the
prospect of obtaining such sets of findings in a more intelligent and automatic methodology, so
that they may, in future, become a blind procedure is discussed.