Diagnostic implications of EEG analysis in patients with dementia

D. L. Hudson, M. E. Cohen, M. Kramer, A. Szeri, F. L. Chang

Research output: Contribution to conferencePaper

8 Scopus citations

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.

Original languageEnglish (US)
Pages629-632
Number of pages4
DOIs
StatePublished - Dec 1 2005
Externally publishedYes
Event2nd International IEEE EMBS Conference on Neural Engineering, 2005 - Arlington, VA, United States
Duration: Mar 16 2005Mar 19 2005

Other

Other2nd International IEEE EMBS Conference on Neural Engineering, 2005
CountryUnited States
CityArlington, VA
Period3/16/053/19/05

Keywords

  • EEG analysis
  • Neural network models
  • Neural signal processing
  • Synchronization

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'Diagnostic implications of EEG analysis in patients with dementia'. Together they form a unique fingerprint.

  • Cite this

    Hudson, D. L., Cohen, M. E., Kramer, M., Szeri, A., & Chang, F. L. (2005). Diagnostic implications of EEG analysis in patients with dementia. 629-632. Paper presented at 2nd International IEEE EMBS Conference on Neural Engineering, 2005, Arlington, VA, United States. https://doi.org/10.1109/CNE.2005.1419703