On the use of empirical mode decomposition (EMD) for Alzheimer's disease diagnosis

Alzheimer’s Disease (AD) is considered one of the most common form of dementia; it involves a progressive decline in cognitive function because of pathological modifications or damage of the brain. One of the major challenges is to develop tools for early diagnosis and disease progression. Electroencephalogram represents potentially a noninvasive and relatively non-expensive approach for screening of dementia and AD. It provides a method to objectively quantify the cortical activation patterns but it is usually considered insensitive in the early AD. This study introduces a novel method where electroencephalographic recordings (EEG) are subjected to Empirical Mode Decomposition (EMD), which decomposes a signal into components known as Intrinsic Mode Functions (IMFs). The results, suggest that, the IMFs may be used to determine the particular frequency bandwidths in which specific phenomena occur.