Lingfeng Liu, Lijun Hao, Qian Yang, Qing Cao, Nan Jiang and Meiyun Zhang* Pages 11 - 28 ( 18 )
<P>Objective: To explore changes in the alpha rhythm wavelength of background electroencephalography in Alzheimer’s disease patients with different degrees of dementia in a resting state; examine their correlation with the degree of cognitive impairment; determine whether the alpha rhythm wavelength can distinguish mild Alzheimer’s disease patients, moderately severe Alzheimer’s disease patients, and healthy controls at the individual level; and identify a cut-off value to differentiate Alzheimer’s disease patients from healthy controls. <P> Methods: Quantitative electroencephalography signals of 42 patients with mild Alzheimer’s disease, 42 patients with moderately severe Alzheimer’s disease, and 40 healthy controls during rest state with eyes closed were analyzed using wavelet transform. Electroencephalography signals were decomposed into different scales, and their segments were superimposed according to the same length (wavelength and amplitude) and phase alignment. Phase averaging was performed to obtain average phase waveforms of the desired scales of each lead. The alpha-band wavelengths corresponding to the ninth scale of the background rhythm of different leads were compared between groups. <P> Results: The average wavelength of the alpha rhythm phase of the whole-brain electroencephalography signals in Alzheimer’s disease patients was prolonged and positively correlated with the severity of cognitive dysfunction (P < 0.01). The ninth-scale phase average wavelength of each lead had high diagnostic efficacy for Alzheimer’s disease, and the diagnostic efficacy of lead P3 (area under the receiver operating characteristic curve = 0.873) was the highest. <P> Conclusion: The average wavelength of the electroencephalography alpha rhythm phase may be used as a quantitative feature for the diagnosis of Alzheimer’s disease, and the slowing of the alpha rhythm may be an important neuro-electrophysiological index for disease evaluation.</P>
Alzheimer’s Disease, EEG, alpha rhythm, alpha-band wavelength, average phase waveform, wavelet transformation.