Identification of hypoglycemic states for patients with T1DM using various parameters derived from EEG signals

UTSePress Research/Manakin Repository

Search UTSePress Research


Advanced Search

Browse

My Account

Show simple item record

dc.contributor.author Ling, Steve en_US
dc.contributor.author Jones, Timothy en_US
dc.contributor.author Nguyen, Hung en_US
dc.contributor.author Nguyen, Lien en_US
dc.contributor.editor Technical Committee en_US
dc.date.accessioned 2012-10-12T03:36:30Z
dc.date.available 2012-10-12T03:36:30Z
dc.date.issued 2011 en_US
dc.identifier 2011001911 en_US
dc.identifier.citation Nguyen Bich et al. 2011, 'Identification of hypoglycemic states for patients with T1DM using various parameters derived from EEG signals', , IEEE, Boston, Massachusetts, USA, , pp. 2760-2763. en_US
dc.identifier.issn 978-1-4244-4122-8 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/19260
dc.description.abstract For patients with Type 1 Diabetes Mellitus (T1DM), hypoglycemia is a very common but dangerous complication which can lead to unconsciousness, coma and even death. The variety of hypoglycemia symptoms is originated from the inadequate supply of glucose to the brain. In this study, we explore the connection between hypoglycemic episodes and the electrical activity of neurons within the brain or electroencephalogram (EEG) signals. By analyzing EEG signals from a clinical study of five children with T1DM, associated with hypoglycemia at night, we find that some EEG parameters change significantly under hypoglycemia condition. Based on these parameters, a method of detecting hypoglycemic episodes using EEG signals with a feed-forward multi-layer neural network is proposed. In our application, the classification results are 72% sensitivity and 55% specificity when the EEG signals are acquired from 2 electrodes C3 and O2. Furthermore, signals from different channels are also analyzed to observe the contributions of each channel to the performance of hypoglycemia classification. en_US
dc.language English en_US
dc.publisher IEEE en_US
dc.relation.hasversion Accepted manuscript version
dc.relation.isbasedon en_US
dc.title Identification of hypoglycemic states for patients with T1DM using various parameters derived from EEG signals en_US
dc.parent 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Boston, Massachusetts, USA en_US
dc.identifier.startpage 2760 en_US
dc.identifier.endpage 2763 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.for 090300 en_US
dc.personcode 106694 en_US
dc.personcode 0000023264 en_US
dc.personcode 840115 en_US
dc.personcode 112227 en_US
dc.percentage 100 en_US
dc.classification.name Biomedical Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom Annual International Conference of the IEEE Engineering in Medicine and Biology Society en_US
dc.date.activity 20110830 en_US
dc.location.activity Boston, Massachusetts, USA en_US
dc.description.keywords hypoglycemia, EEG en_US
dc.staffid 840115 en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record