An analysis for Alzheimer’s disease using cross-correlation and averaged frequency of EEG data

Abstract

A survey by Japan’s Ministry of Health, Labour and Welfare shows that the number of people with dementia will increase to 7 million individuals by 2025. This means that about one in five people who are 65 years of age or older will develop dementia. In addition, the number of traffic accidents involving older drivers has become an issue recently. Therefore, we considered that if there were a technique that allowed individuals to determine the presence of dementia by themselves, it could be detected at an earlier stage. Our proposed method employs averaged frequency and triple correlation techniques to detect the presence of Alzheimer’s disease using only three electrodes and a short data acquisition period.