Development of EEG-based stress index

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Main Authors: Norizam, Sulaiman, Mohd Nasir, Taib, Prof. Dr., Sahrim, Lias, Zunairah, Hj Murat, Siti Armiza, Mohd Aris, Mahfuza, Mustafa, Nazre, Abdul Rashid
Other Authors: norizam@ump.edu.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2012
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Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/21406
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spelling my.unimap-214062012-10-18T07:55:16Z Development of EEG-based stress index Norizam, Sulaiman Mohd Nasir, Taib, Prof. Dr. Sahrim, Lias Zunairah, Hj Murat Siti Armiza, Mohd Aris Mahfuza, Mustafa Nazre, Abdul Rashid norizam@ump.edu.my dr.nasir@ieee.org Cognitive states Electroencephalogram (EEG) Energy Spectral Density Shannon Entropy Spectral Centroids k-Nearest Neighbor (k-NN) Stress Index Link to publisher's homepage at http://ieeexplore.ieee.org/ This paper presents a non-parametric method to produce stress index using Electroencephalogram (EEG) signals. 180 EEG datasets from healthy subjects were evaluated at two cognitive states; resting state (Eyes Closed) and working state (Eyes Open). In working cognitive state, subjects were asked to answer the Intelligence Quotient (IQ) test questions. The EEG datasets were categorized into 4 groups. Energy Spectral Density (ESD) ratios and Spectral Centroids (SC) from the two tasks were calculated and selected as input features to k-Nearest Neighbor (k-NN) classifier. Shannon’s Entropy (SE) was used to detect and quantify the distribution of ESD due to stressors (stress factors). The stress indexes were assigned based on the results of classification, ESD ratios, SC and SE. There were 3 types of stress indexes can be assigned which represent the stress level (low stress, moderate stress and high stress) at classification accuracy of 88.89%. The regression coefficient of the SC of Beta and Alpha was 77%. 2012-10-18T07:55:16Z 2012-10-18T07:55:16Z 2012-02-27 Working Paper p. 461-466 978-145771989-9 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6179059 http://hdl.handle.net/123456789/21406 en Proceedings of the International Conference on Biomedical Engineering (ICoBE 2012) Institute of Electrical and Electronics Engineers (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Cognitive states
Electroencephalogram (EEG)
Energy Spectral Density
Shannon Entropy
Spectral Centroids
k-Nearest Neighbor (k-NN)
Stress Index
spellingShingle Cognitive states
Electroencephalogram (EEG)
Energy Spectral Density
Shannon Entropy
Spectral Centroids
k-Nearest Neighbor (k-NN)
Stress Index
Norizam, Sulaiman
Mohd Nasir, Taib, Prof. Dr.
Sahrim, Lias
Zunairah, Hj Murat
Siti Armiza, Mohd Aris
Mahfuza, Mustafa
Nazre, Abdul Rashid
Development of EEG-based stress index
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 norizam@ump.edu.my
author_facet norizam@ump.edu.my
Norizam, Sulaiman
Mohd Nasir, Taib, Prof. Dr.
Sahrim, Lias
Zunairah, Hj Murat
Siti Armiza, Mohd Aris
Mahfuza, Mustafa
Nazre, Abdul Rashid
format Working Paper
author Norizam, Sulaiman
Mohd Nasir, Taib, Prof. Dr.
Sahrim, Lias
Zunairah, Hj Murat
Siti Armiza, Mohd Aris
Mahfuza, Mustafa
Nazre, Abdul Rashid
author_sort Norizam, Sulaiman
title Development of EEG-based stress index
title_short Development of EEG-based stress index
title_full Development of EEG-based stress index
title_fullStr Development of EEG-based stress index
title_full_unstemmed Development of EEG-based stress index
title_sort development of eeg-based stress index
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/21406
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score 13.222552