This paper presents an EEG study for coherence and phase synchrony in mild cognitive impairment (MCI) subjects. MCI is characterized by cognitive decline, which is an early stage of Alzheimer’s disease (AD). AD is a neurodegenerative disorder with symptoms such as memory loss and cognitive impairment. EEG coherence is a statistical measure of correlation between signals from electrodes spatially separated on the scalp. The magnitude of phase synchrony is expressed in the phase locking value (PLV), a statistical measure of neuronal connectivity in the human brain. Brain signals were recorded using an Emotiv Epoc 14-channel wireless EEG at a sampling frequency of 128 Hz. In this study, we used 22 elderly subjects consisted of 10 MCI subjects and 12 healthy subjects as control group. The coherence between each electrode pair was measured for all frequency bands (delta, theta, alpha and beta). In the MCI subjects, the value of coherence and phase synchrony was generally lower than in the healthy subjects especially in the beta frequency. A decline of intrahemisphere coherence in the MCI subjects occurred in the left temporo-parietal-occipital region. The pattern of decline in MCI coherence is associated with decreased cholinergic connectivity along the path that connects the temporal, occipital, and parietal areas of the brain to the frontal area of the brain. EEG coherence and phase synchrony are able to distinguish persons who suffer AD in the early stages from healthy elderly subjects.
Brainwave is widely used as an indicator of brain activity and can be detected by electroencephalography (EEG). The development of EEG device has become more advanced along with the invention of low-cost tiny electronic modules and wireless technology. This research aimed to develop a low-cost wireless modular device for brainwave acquisition based on Arduino microcontroller. The system was designed into sensor block for brainwave receiver and conditioning, and mainboard block for data processing. Dry-active electrode was developed as the sensor, followed by preamplifier module which was also installed at the sensor block. Active filter and DRL circuits were developed on the mainboard part. Arduino UNO was used as the main processor of the device. The developed modules were then evaluated using signal generator to examine the module characteristics and consistency. As the result, the preamplifier module was detected to reach 40.34 dB on gain ability. The cutoff frequency on the active filter module was calculated on 31 Hz. Furthermore, Arduino UNO was identified to have a consistency on input and output voltage.
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