Offline LabVIEW-based EEG Signals Analysis for Human Stress Monitoring

Stress is often known as a state of mental or emotional tension resulting from adverse circumstances. Consequently, people nowadays are facing stress where different people will have a different level of stress. Hence, EEG technology is invented to assist people to determine the level of stress by...

Full description

Bibliographic Details
Main Authors: Norizam, Sulaiman, Beh, See Ying, Mahfuzah, Mustafa, Mohd Shawal, Jadin
Format: Conference or Workshop Item
Language:English
Published: IEEE 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/28264/7/Offline%20LabVIEW-based%20EEG%20Signals%20Analysis.pdf
_version_ 1825813322353606656
author Norizam, Sulaiman
Beh, See Ying
Mahfuzah, Mustafa
Mohd Shawal, Jadin
author_facet Norizam, Sulaiman
Beh, See Ying
Mahfuzah, Mustafa
Mohd Shawal, Jadin
author_sort Norizam, Sulaiman
collection UMP
description Stress is often known as a state of mental or emotional tension resulting from adverse circumstances. Consequently, people nowadays are facing stress where different people will have a different level of stress. Hence, EEG technology is invented to assist people to determine the level of stress by using brain signals. This paper describes the development of a LabVIEW-based system that can determine the level of stress based on the analysis of brain signals in LabVIEW. In this study, 1-channel EEG amplifier is employed to record EEG signals from five subjects at three different cognitive states which are closed eyes (do nothing), playing game and doing IQ test. The eegID application in mobile phone is used to capture recorded EEG signals from EEG amplifier and then the captured EEG signals are analysed in LabVIEW. The result shows that the average centroid which was applied on the EEG Power Spectrum of Alpha band is higher than Beta band when the subject is at relax cognitive state meanwhile the average centroid of EEG Power Spectrum of Beta band is higher than Alpha band when the subject is at stress cognitive state. Thus, it can be concluded that the subject are in the stress cognitive state when playing game and doing IQ test. At the end of this project, the LabVIEW Graphical User Interface (GUI) is created to display the level of stress for each subject after undergoing several mental exercises. Beside LabVIEW GUI, a device is constructed to display the level of stress in offline manner.
first_indexed 2024-03-06T12:42:15Z
format Conference or Workshop Item
id UMPir28264
institution Universiti Malaysia Pahang
language English
last_indexed 2024-03-06T12:42:15Z
publishDate 2019
publisher IEEE
record_format dspace
spelling UMPir282642020-05-05T00:14:41Z http://umpir.ump.edu.my/id/eprint/28264/ Offline LabVIEW-based EEG Signals Analysis for Human Stress Monitoring Norizam, Sulaiman Beh, See Ying Mahfuzah, Mustafa Mohd Shawal, Jadin TK Electrical engineering. Electronics Nuclear engineering Stress is often known as a state of mental or emotional tension resulting from adverse circumstances. Consequently, people nowadays are facing stress where different people will have a different level of stress. Hence, EEG technology is invented to assist people to determine the level of stress by using brain signals. This paper describes the development of a LabVIEW-based system that can determine the level of stress based on the analysis of brain signals in LabVIEW. In this study, 1-channel EEG amplifier is employed to record EEG signals from five subjects at three different cognitive states which are closed eyes (do nothing), playing game and doing IQ test. The eegID application in mobile phone is used to capture recorded EEG signals from EEG amplifier and then the captured EEG signals are analysed in LabVIEW. The result shows that the average centroid which was applied on the EEG Power Spectrum of Alpha band is higher than Beta band when the subject is at relax cognitive state meanwhile the average centroid of EEG Power Spectrum of Beta band is higher than Alpha band when the subject is at stress cognitive state. Thus, it can be concluded that the subject are in the stress cognitive state when playing game and doing IQ test. At the end of this project, the LabVIEW Graphical User Interface (GUI) is created to display the level of stress for each subject after undergoing several mental exercises. Beside LabVIEW GUI, a device is constructed to display the level of stress in offline manner. IEEE 2019-03-04 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/28264/7/Offline%20LabVIEW-based%20EEG%20Signals%20Analysis.pdf Norizam, Sulaiman and Beh, See Ying and Mahfuzah, Mustafa and Mohd Shawal, Jadin (2019) Offline LabVIEW-based EEG Signals Analysis for Human Stress Monitoring. In: 9th IEEE Control And System Graduate Research Colloquium (ICSGRC 2018) , 3-4 August 2018 , Shah Alam, Selangor. pp. 126-131. (18504705). ISBN 978-1-5386-6321-9 (Published) https://doi.org/10.1109/ICSGRC.2018.8657606
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Norizam, Sulaiman
Beh, See Ying
Mahfuzah, Mustafa
Mohd Shawal, Jadin
Offline LabVIEW-based EEG Signals Analysis for Human Stress Monitoring
title Offline LabVIEW-based EEG Signals Analysis for Human Stress Monitoring
title_full Offline LabVIEW-based EEG Signals Analysis for Human Stress Monitoring
title_fullStr Offline LabVIEW-based EEG Signals Analysis for Human Stress Monitoring
title_full_unstemmed Offline LabVIEW-based EEG Signals Analysis for Human Stress Monitoring
title_short Offline LabVIEW-based EEG Signals Analysis for Human Stress Monitoring
title_sort offline labview based eeg signals analysis for human stress monitoring
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/28264/7/Offline%20LabVIEW-based%20EEG%20Signals%20Analysis.pdf
work_keys_str_mv AT norizamsulaiman offlinelabviewbasedeegsignalsanalysisforhumanstressmonitoring
AT behseeying offlinelabviewbasedeegsignalsanalysisforhumanstressmonitoring
AT mahfuzahmustafa offlinelabviewbasedeegsignalsanalysisforhumanstressmonitoring
AT mohdshawaljadin offlinelabviewbasedeegsignalsanalysisforhumanstressmonitoring