DocumentCode :
3012940
Title :
Diagnostic Implications of EEG Analysis in Patients with Dementia
Author :
Hudson, D.L. ; Cohen, M.E. ; Kramer, M. ; Szeri, A. ; Chang, F.L.
Author_Institution :
California Univ., San Francisco, CA
fYear :
2005
fDate :
16-19 March 2005
Firstpage :
629
Lastpage :
632
Abstract :
New methods of electroencephalogram (EEG) analysis show promise in differentiating among types of dementia. While these measures alone are useful, their diagnostic contribution increases when combined with clinical parameters using higher order decision models such as neural network models and hybrid systems. Three categories of patients are included in the current study, Alzheimer´s patients (AD), minimal cognitive impairment (MCI), and normal controls. Results show that patients can be categorized accurately using the combination of EEG synchronization results and selected clinical parameters
Keywords :
diseases; electroencephalography; medical signal processing; neural nets; patient diagnosis; synchronisation; Alzheimer patients; EEG analysis; EEG synchronization; dementia; diagnostic implications; hybrid systems; minimal cognitive impairment; neural network models; Alzheimer´s disease; Biological neural networks; Brain modeling; Dementia; Electroencephalography; Parkinson´s disease; Scalp; Signal analysis; Spatial resolution; Wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering, 2005. Conference Proceedings. 2nd International IEEE EMBS Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-8710-4
Type :
conf
DOI :
10.1109/CNE.2005.1419703
Filename :
1419703
Link To Document :
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