Universiti Teknologi Malaysia Institutional Repository

Spatial analysis of signal during epileptic seizure on plat electroencephalography

Goh, Chien Yong (2017) Spatial analysis of signal during epileptic seizure on plat electroencephalography. PhD thesis, Universiti Teknologi Malaysia, Faculty of Science.


Official URL: http://dms.library.utm.my:8080/vital/access/manage...


The human brain is the most complex structure in the universe. It is made up of billions of nerve cells called neurons. Studies on human brain were started centuries ago whereby various diagnosis instruments and techniques have been developed to understand it. Epilepsy is the second most common brain disorder. Electroencephalogram (EEG) was invented and widely used for recording human brain electrical activities. It is considered as the best tool which has been used in epileptic analysis. However, the best visual inspection still highly relies on experienced electroencephalographers or neurophysiologists. Due to this restriction, extraction of the hidden information from EEG signal during epileptic seizure is important. In this work, a new spatial interaction model which is based on basic gravity model is developed and applied on flat Electroencephalography (fEEG). The model is used to study the interaction among clusters on fEEG. The images of these interactions are then verified and compared to interaction images of spherical domain model of charges in the brain. The strength of interaction force inside the spherical domain of charges’ path is calculated. The results showed that the interaction of the clusters are not directly proportional to distance, potential difference of cluster and size of cluster’s charge. This study concurs the chaotic behavior of epileptic seizure as advocated by Iasemidis and his fellow researchers.

Item Type:Thesis (PhD)
Additional Information:Thesis (Ph.D (Matematik)) - Universiti Teknologi Malaysia, 2017; Supervisor : Assoc. Prof. Dr.Tahir Ahmad, Assoc. Prof. Dr. Normah Maan
Subjects:Q Science > QA Mathematics
ID Code:84037
Deposited By: Fazli Masari
Deposited On:31 Oct 2019 18:10
Last Modified:05 Nov 2019 12:35

Repository Staff Only: item control page