Age-Related Changes in Brainwave Patterns

An EEG-Based Analysis

DOI

10.2991/978-94-6463-831-8_38How to use a DOI?

Keywords

EEG Signals; Brain Activity; Descriptive Statistics; Correlation Analysis

Abstract

From an age perspective, the brain changes based on thinking and processing information. The study in this case presents the EEG brainwave patterns in 109 samples, each for one thousand outcomes, ranging from 18 to 83 years old. The signals from the different regions of the brain, like frontal, central, parietal, temporal, and occipital, were analyzed and scaled using mathematical scaling techniques, descriptive statistics, correlation analysis, and data visualization in the form of the line plot and the scatter plot to help understand it all. In older adults, especially the age group: 50–59, brain activity dropped significantly in the frontal areas like FP1: r = -0.43693 and occipital areas like O2: r = -0.29864, showing reduced signal with age. The average correlation from different parts of the brain varied by age group, with the strongest value in the 50–59 group: r = 0.250971, and the lowest in the 30–39 age group: r = -0.0089, pointing to clear aging trends. This suggests that EEG can be useful to monitor brain aging. The research paper suggests that EEG could help monitor brain health because aging affects different brain regions uniquely.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Hnin Ei Hlaing
AU  - Wanus Srimaharaj
PY  - 2025
DA  - 2025/08/31
TI  - Age-Related Changes in Brainwave Patterns
BT  - Proceeding of the 1st International Conference on Lifespan Innovation (ICLI 2025)
PB  - Atlantis Press
SP  - 314
EP  - 321
SN  - 2468-5739
UR  - https://doi.org/10.2991/978-94-6463-831-8_38
DO  - 10.2991/978-94-6463-831-8_38
ID  - Hlaing2025
ER  -