Study on a quantitative electroencephalography power spectrum typical of Chinese Han Alzheimer's disease patients by using wavelet transforms.

Abstract

Our objective was to investigate the quantitative electroencephalogram (EEG) power spectrum typical of Chinese Han ethnic Alzheimer's disease (AD) patients. A study on the resting EEG was carried out on 103 local AD (NINCDS-ADRDA criteria) patients, and 124 age-matched normal elderly subjects served as controls. A novel multi-resolution decomposition algorithm based on Daubechies wavelet transform was employed for EEG spectral analysis. This algorithm decomposed recorded EEG signals into components with five frequency subbands, which especially provided more electroneural activity details in comparison with the conventional four subbands. A significant prevalence of an EEG spectrum characterized by increased slow activity with decreased fast activity was found in these patients. Moreover, the spectral power increase/decrease was mainly centralized in the below-2 Hz/over-8 Hz band, whereas the 2-8 Hz band did not show any widespread change. In conclusion, this study may provide some evidence of specific spectral changes of EEG affected by AD in China.