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

V. Podgorelec


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.



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

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Print ISSN: 1392-1215
Online ISSN: 2029-5731