Output details

Approximate entropy and auto mutual information analysis of the electroencephalogram in Alzheimer's disease patients

This output shows that Alzheimer’s disease can be detected by analysing the electrical activity of the brain recorded in electroencephalograms with advanced signal processing techniques and that more information is obtained when different time scales are inspected. Furthermore, a strong correlation exists between the results of analysing the electrical activity of the brain with information based techniques, such as mutual information, and embedding entropies, like approximate entropy. This could facilitate early diagnosis of Alzheimer’s disease using the electroencephalogram, a technique with lower cost than medical imaging.