Why the study?
Can a classification method based on EEG power variability using 4 electrodes accurately distinguish between MCI patients and healthy people?
Can a classification method based on EEG power variability using 4 electrodes accurately distinguish between MCI patients and healthy people?
A novel EEG-based classification method using only 4 electrodes can accurately distinguish patients with mild cognitive impairment from healthy individuals.
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Should not yet alter MCI screening practice; hypothesis-generating for 4-electrode EEG and requires prospective validation.
Patients with mild cognitive impairment (MCI) and healthy people were classified by using “Power variance function (PVF)” of electroencephalography (EEG) recorded on only 4 electrodes in this study. PVF is an index of power variability of EEG proposed in a previous report. In this study, the balance of PVFs on a head of each person was analyzed. EEG signals of 25 MCI patients and those of 57 healthy people were recorded on Twenty-one electrodes in accordance with the 10-20 International System while the patients were at rest with eyes closed for 5 minutes. After noise reduction, the balance of PVFs of the MCI patients and those of the healthy people were compared. The results indicated that for MCI patients, the difference between PVFs of the frontal region and those of the occipital region was significantly smaller than that of healthy people in theta-alpha band. Moreover, it was found that the balance of PVFs were especially different between MCI patients and healthy people in theta-alpha band on 4 electrodes (O1, F3, Fz, and Cz as the reference). These electrodes were, therefore, selected for classification of MCI patients and healthy people. As the classification result, accuracy of 89.0%, sensitivity of 84.0%, and specificity of 91.2% were achieved.
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UEDA et al. (2015) studied this question.
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