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Author Jacques, Genevieve ♦ Frymiare, Jennifer L. ♦ Kounios, John ♦ Clark, Christopher ♦ Polikar, Robi
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Description IEEE Int. Conf on Acoustics Speech and Signal Processing
The diagnosis of Alzheimer’s disease at an early stage is a major concern due to growing number of the elderly population affected, as well as the lack of a standard and effective diagnosis procedure available to community healthcare providers. Recent studies have used wavelets and other signal processing methods to analyze EEG signals in an attempt to find a non-invasive biomarker for Alzheimer’s disease and had varying degrees of success. These studies have traditionally used automated classifiers such as neural networks; however the use of an ensemble of classifiers has not been previously explored and may prove to be beneficial. In this study, multiresolution wavelet analysis is performed on event related potentials of the EEG which are then used with the ensemble of classifiers based Learn++ algorithm. We describe the approach, and present our promising preliminary results. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2005-01-01