NDLI: Blind Source Separation of Concurrent Disease-Related Patterns from EEG in Creutzfeldt–Jakob Disease for Assisting Early Diagnosis

Content Provider	Springer Nature Link
Author	Hung, Chih I Wang, Po Shan Soong, Bing Wen Teng, Shin Hsieh, Jen Chuen Wu, Yu Te
Copyright Year	2007
Abstract	Creutzfeldt–Jakob disease (CJD) is a rare, transmissible and fatal prion disorder of brain. Typical electroencephalography (EEG) patterns, such as the periodic sharp wave complexes (PSWCs), do not clearly emerge until the middle stage of CJD. To reduce transmission risks and avoid unnecessary treatments, the recognition of the hidden PSWCs forerunners from the contaminated EEG signals in the early stage is imperative. In this study, independent component analysis (ICA) was employed on the raw EEG signals recorded at the first admissions of five patients to segregate the co-occurrence of multiple disease-related features, which were difficult to be detected from the smeared EEG. Clear CJD-related waveforms, i.e., frontal intermittent rhythmical delta activity (FIRDA), fore PSWCs (triphasic waves) and periodic lateralized epileptiform discharges (PLEDs), have been successfully and simultaneously resolved from all patients. The ICA results elucidate the concurrent appearance of FIRDA and PLEDs or triphasic waves within the same EEG epoch, which has not been reported in the previous literature. Results show that ICA is an objective and effective means to extract the disease-related patterns for facilitating the early diagnosis of CJD.
Starting Page	2168
Ending Page	2179
Page Count	12
File Format	PDF
ISSN	00906964
Journal	Annals of Biomedical Engineering
Volume Number	35
Issue Number	12
e-ISSN	15739686
Language	English
Publisher	Springer US
Publisher Date	2007-09-22
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Frontal intermittent rhythmical delta activity (FIRDA) Periodic sharp wave complexes (PSWCs) Periodic lateralized epileptiform discharges (PLEDs) Biochemistry Mechanics Biophysics/Biomedical Physics Biomedical Engineering Biomedicine general
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

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