Open AccessImplementation of EEG signals and P-300 Component to estimate Mild Cognitive Impairment (MCI)
Author(s) -
Parag Puranik,
Santosh Agrahari,
Ashish Panat
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3188.078219
Subject(s) - electroencephalography , audiology , cognitive impairment , coherence (philosophical gambling strategy) , alpha (finance) , psychology , beta rhythm , cognition , beta (programming language) , medicine , developmental psychology , neuroscience , psychometrics , computer science , mathematics , statistics , construct validity , programming language
Aim: The aim is to estimate the parameters of MCI by evaluating the EEG and P-300 component of subjects. The controlled healthy and MCI patients selected for this analysis. The aim is to reveal the worsening cognition in the patients and diagnose the disease at an early stage. Method: EEG recording & P-300 measurement of 30 subjects is performed. Considering all the possibilities and artefacts 1024-point Quantitative EEG selected to perform the analysis. Results: The parameters of EEG and P-300 analysis revealed the difference between Controlled healthy and MCI group patients. Power, relative power, symmetry, coherence, phase cross spectrum, correlation were differentiated using QEEG analysis. Conclusion: The study on MCI patients discovered that the mass posterior sluggish rhythm of frequency bands dropped the alpha and beta behavior whereas the occipital movement of the alpha and beta band in the usual aging is increasing. The P-300 component used to classify MCI and Controlled healthy people.