INVESTIGATING THE VARIATIONS IN THE BRAIN ACTIVITY BETWEEN HEALTHY SUBJECTS AND MILD COGNITIVE IMPAIRMENT (MCI) PATIENTS

Najmeh Pakniyat, Balamurali Ramakrishnan, V. Pallavi, Ondrej Krejcar, Robert Frischer and Hamidreza Namazi
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Najmeh Pakniyat: 30 Shore Breeze Drive, Toronto ON, Canada M8V 0J1, Canada
Balamurali Ramakrishnan: ��Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai 600069, Tamil Nadu, India
V. Pallavi: ��Computer Science and Engineering, Vemu Institute of Technology, Tirupati-Chittoor Highway, P. Kothakota, Chittoor 517112, Andhra Pradesh, India
Ondrej Krejcar: �Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czechia¶Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czechia∥Department of Biomedical Engineering and Measurement, Faculty of Mechanical Engineering Technical, University of Kosice, Slovakia
Robert Frischer: �Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czechia
Hamidreza Namazi: �Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czechia**School of Engineering, Monash University, Selangor, Malaysia

FRACTALS (fractals), 2023, vol. 31, issue 09, 1-7

Abstract: Analysis of brain activity for patients with brain disorders is an important research area. Mild cognitive impairment (MCI) is a condition in which patients have more memory or thinking problems compared to healthy people of the same age. In this work, we studied the alterations in brain activity among control subjects and patients with MCI. Three complexity techniques, namely sample entropy, approximate entropy, and fractal dimension, were employed to study electroencephalogram (EEG) signals recorded from 102 control (healthy) subjects, and seven subjects with MCI in a comfortable position, on a bed, with their eyes closed. The results showed that the EEG signals of patients with MCI show greater complexity than the EEG signals of healthy subjects. This analysis method can be applied to compare brain activity among healthy subjects and patients with other brain diseases.

Keywords: Mild Cognitive Impairment (MCI); EEG Signals; Complexity; Sample Entropy Approximate Entropy; Fractal Dimension (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0218348X23501244

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