Title :
Automated visualization for epilepsy surgical evaluation
Author :
Rasheed, Waqas ; Tong Boon Tang ; Hamid, Nor Hisham ; Idris, Zamzuri ; Abdullah, Jafri Malin
Author_Institution :
Electr. & Electron. Eng. Dept., Univ. Teknol. PETRONAS, Tronoh, Malaysia
Abstract :
Epilepsy is a neurological illness which may be controlled by medication but not fully cured. In the case of pharmacoresistant epilepsy, seizures may prove fatal and surgery becomes an option. Compared with EEG (electro-encephalography), MEG (magenetoencephalography) offers greater accuracy in epilepsy localization owing to higher spatial resolution. However, streaming data from MEG system for surgical evaluation involves cumbersome processes, e.g. down-sampling, artifact removal (via Independent Component Analysis most of the time) and time/frequency plotting. This paper proposes an automated framework using open-source solutions to visualize epilepsy. The capability of the framework is demonstrated with a case of epilepsy surgery.
Keywords :
diseases; electroencephalography; independent component analysis; magnetoencephalography; medical signal processing; neurophysiology; EEG; MEG system; artifact removal; automated visualization; data streaming; down-sampling; electroencephalography; epilepsy localization; epilepsy surgical evaluation; independent component analysis; magenetoencephalography; medication; neurological illness; open-source solutions; pharmacoresistant epilepsy; seizures; spatial resolution; time-frequency plotting; Brain modeling; Computational modeling; Epilepsy; Magnetic resonance imaging; Mathematical model; Surgery;
Conference_Titel :
Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on
Conference_Location :
San Diego, CA
DOI :
10.1109/NER.2013.6695992