Analyzing EEG Signals with Machine Learning for Diagnosing Alzheimer’s Disease

Authors

  • V. Podgorelec University of Maribor

DOI:

https://doi.org/10.5755/j01.eee.18.8.2627

Keywords:

Alzheimer’s disease, computer aided diagnosis, electroencephalography, machine learning, medical diagnosis, signal analysis

Abstract

In order to have the greatest treatment impact the early and accurate diagnose of Alzheimer’s disease (AD) is essential. In this paper we present a method for analyzing EEG signals with machine learning approach in order to diagnose AD. We show how to extract features out of EEG recordings to be used with a machine learning algorithm for the induction of AD classification model. The obtained results are very promising.

DOI: http://dx.doi.org/10.5755/j01.eee.18.8.2627

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Published

2012-10-17

How to Cite

Podgorelec, V. (2012). Analyzing EEG Signals with Machine Learning for Diagnosing Alzheimer’s Disease. Elektronika Ir Elektrotechnika, 18(8), 61-64. https://doi.org/10.5755/j01.eee.18.8.2627

Issue

Vol. 18 No. 8 (2012)

Section

SIGNAL TECHNOLOGY

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