Early detection of electroencephalogram temporal events in Alzheimer's disease

Abstract

Alzheimer’s Disease (AD) is considered one of the most debilitating illness in modern societies and the leading cause of dementia. This study is a new approach to detect early AD Electroencephalogram (EEG) temporal events in order to improve early AD diagnosis. For that, Self-Organized Maps (SOM) were used, and it was found that there are sequences of EEG energy variation, characteristic of AD, that appear with high incidence in Mild Cognitive Impairment (MCI) patients. Those AD events are related to the first cognitive changes in patients that interfered with the normal EEG signal pattern. Moreover, there are significant differences concerning the propagation time of those events between the study groups(p=0.0082<0.05), meaning that, as AD progresses the brain dynamics are progressively affected, what is expected because AD causes brain atrophy.