Analisis spektral entropi dan kompleksitas sinyal EEG pada Alzheimer’s Disease - Nita Handayani; Y Akbar; I Arif; S N Khotimah; F Haryanto; W P Taruno (Journal of Medical Physics and Biophysics, 2018)
Alzheimer's Disease (AD) is a neurodegenerative disease characterized by decreased memory function and cognitive ability. The disease is caused by damage to neurons due to the accumulation of amyloid beta plaque (Aβ) and neurofibrillary tangles (NFTs) within the neurons. This condition causes the transmission of electrical signals in the brain to be inhibited and there is a change in the level of irregularity and complexity of brain signals. The purpose of this study was to measure the degree of irregularity and complexity of EEG data in AD patients with spectral entropy and Largest Lyapunov Exponent (LLE) quantities. EEG data recording uses 14-channel Emotiv Epoc with a sampling frequency of 128 Hz. The test subjects consisted of 9 subjects with Alzheimer's Disease and 10 control subjects. The Mann-Whitney U test statistic was used to see if there were significantly differences in the values of spectral entropy and LLE between the AD group and the control group. Based on the calculation results obtained that the value of spectral entropy of AD patients lower than control subjects (p <0.05) on P8, F4 and AF4 electrodes. The chaotic level test with LLE showed significantly difference (p <0.05) on AF3, F7, FC5, P8, T8, F4, F8 and AF4 electrodes between AD group and control group. The study of EEG nonlinear dynamics can be used to determine the degree of irregularity and complexity of brain signals.