AlzSDR - METHOD FOR OBTAINING AN INDICATOR OF PRESENCE FOR ALZHEIMER'S DISEASE USING EEG SIGNALS

The AlzSDR - METHOD FOR OBTAINING AN INDICATOR OF PRESENCE FOR ALZHEIMER'S DISEASE USING EEG SIGNALS - tool is based on a new electroencephalogram (EEG) signal processing tool - the Margolacs - to characterize the Alzheimer’s disease (AD) activity and to assist on its diagnosis and evolution prospecting for different stages: Mild Cognitive Impairment (MCI), Mild and Moderate AD (ADM) and Advanced AD (ADA). The system reached a prediction accuracy of 98% for All vs All, 99% for C vs MCI, 99% for C vs ADM, 97% for MCI vs ADM-ADA. In C vs MCI, C vs ADM and MCI vs ADM-ADA, the proposed method outperforms the state-of-art methods by 1%, 3%, and 3%, respectively. In All vs All, it outperforms the state-of-art EEG and non-EEG methods by 2% and 4%, respectively.
These results indicate that the proposed method represents an improvement in diagnosing AD. The
AlzSDR tool as an interface that provide to medical doctors some important information such as: (1) diagnosis; (2) Alzheimer Scalp-level activity prospection; (3) Power spectral density metrics; (4) recording data and the corresponding EEG conventional sub-bands plot;