Analysis of correlation between body mass index (BMI) and brain wave using EEG for alpha and beta wave / Azlan Hakimi Yahaya Rashid

The research is focusing on the correlation between the body mass index (BMI) and the brain wave pattern using EEG, concentrating on Alpha and Beta wave. Using BMI as reference, all 63 samples were given a questionnaire and categorized into underweight, ideal weight and overweight, before undergoing...

Full description

Saved in:
Bibliographic Details
Main Author: Yahaya Rashid, Azlan Hakimi
Format: Thesis
Language:English
Published: 2014
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/67665/1/67665.PDF
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-uitm-ir.67665
record_format uketd_dc
spelling my-uitm-ir.676652022-10-20T08:20:31Z Analysis of correlation between body mass index (BMI) and brain wave using EEG for alpha and beta wave / Azlan Hakimi Yahaya Rashid 2014 Yahaya Rashid, Azlan Hakimi Brain Other therapies and special aspects of therapy, A-Z The research is focusing on the correlation between the body mass index (BMI) and the brain wave pattern using EEG, concentrating on Alpha and Beta wave. Using BMI as reference, all 63 samples were given a questionnaire and categorized into underweight, ideal weight and overweight, before undergoing the EEG process. The brainwaves were captured using EEG; all data needed were recorded and then analyzed using SPSS software. It was observed that there are high correlations between BMI and brainwave pattern for overweight category as compared to the others. Generally, it can also be concluded that ideal weight student have more balance brainwave pattern hence, less stress than the others. 2014 Thesis https://ir.uitm.edu.my/id/eprint/67665/ https://ir.uitm.edu.my/id/eprint/67665/1/67665.PDF text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering S. Abdul Kadir, Ros Shilawani
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor S. Abdul Kadir, Ros Shilawani
topic Brain
Brain
spellingShingle Brain
Brain
Yahaya Rashid, Azlan Hakimi
Analysis of correlation between body mass index (BMI) and brain wave using EEG for alpha and beta wave / Azlan Hakimi Yahaya Rashid
description The research is focusing on the correlation between the body mass index (BMI) and the brain wave pattern using EEG, concentrating on Alpha and Beta wave. Using BMI as reference, all 63 samples were given a questionnaire and categorized into underweight, ideal weight and overweight, before undergoing the EEG process. The brainwaves were captured using EEG; all data needed were recorded and then analyzed using SPSS software. It was observed that there are high correlations between BMI and brainwave pattern for overweight category as compared to the others. Generally, it can also be concluded that ideal weight student have more balance brainwave pattern hence, less stress than the others.
format Thesis
qualification_level Bachelor degree
author Yahaya Rashid, Azlan Hakimi
author_facet Yahaya Rashid, Azlan Hakimi
author_sort Yahaya Rashid, Azlan Hakimi
title Analysis of correlation between body mass index (BMI) and brain wave using EEG for alpha and beta wave / Azlan Hakimi Yahaya Rashid
title_short Analysis of correlation between body mass index (BMI) and brain wave using EEG for alpha and beta wave / Azlan Hakimi Yahaya Rashid
title_full Analysis of correlation between body mass index (BMI) and brain wave using EEG for alpha and beta wave / Azlan Hakimi Yahaya Rashid
title_fullStr Analysis of correlation between body mass index (BMI) and brain wave using EEG for alpha and beta wave / Azlan Hakimi Yahaya Rashid
title_full_unstemmed Analysis of correlation between body mass index (BMI) and brain wave using EEG for alpha and beta wave / Azlan Hakimi Yahaya Rashid
title_sort analysis of correlation between body mass index (bmi) and brain wave using eeg for alpha and beta wave / azlan hakimi yahaya rashid
granting_institution Universiti Teknologi MARA (UiTM)
granting_department Faculty of Electrical Engineering
publishDate 2014
url https://ir.uitm.edu.my/id/eprint/67665/1/67665.PDF
_version_ 1783735712163561472