Diagnosis method of mild cognitive impairment based on power variance of EEG

Mild cognitive impairment (MCI) patients and healthy people were classified by using a “power variance function (PVF)”, namely, an index of electroencephalography (EEG) proposed in a previous report. PVF is defined by calculating variance of the power variability of an EEG signal at each frequency of the signal using wavelet transform. After confirming that the distribution of PVFs of the subjects was a normal distribution at each frequency, the distributions of PVFs of 25 MCI patients and those of 57 healthy people were compared in terms of Z-score. The comparison results indicate that for the MCI patients, the PVFs in the θ band are significantly higher in left parieto-occipital area and that those in the β band are lower in the bitemporal area. Multidimensional discriminant analysis using the PVF in the θ-β band recorded only on four electrodes on the left parieto-occipital area could be used to classify MCI patients from healthy people with leave-one-out accuracy of 87.5%. This indicates the possibility of diagnosing MCI by using EEG signals recorded only on a few electrodes.