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A study on mental arithmetic task based human stress level classification using discrete wavelet transform

Proceeding of The 3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT 2012) at Kuala Lumpur, Malaysia on 6 October 2012 through 9 October 2012. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp

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Bibliographic Details
Main Authors: Karthikeyan, Palanisamy, Murugappan, M., Dr., Sazali, Yaacob, Prof. Dr.
Other Authors: karthi_209170@yahoo.com
Format: Working Paper
Language:English
Published: IEEE Conference Publications 2014
Subjects:
ECG
KNN classifier
Mental arithmetic task
Stress
Wavelet transform
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/34652
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spelling my.unimap-346522014-05-22T09:01:39Z A study on mental arithmetic task based human stress level classification using discrete wavelet transform Karthikeyan, Palanisamy Murugappan, M., Dr. Sazali, Yaacob, Prof. Dr. karthi_209170@yahoo.com murugappan@unimap.edu.my s.yaacob@unimap.edu.my ECG KNN classifier Mental arithmetic task Stress Wavelet transform Proceeding of The 3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT 2012) at Kuala Lumpur, Malaysia on 6 October 2012 through 9 October 2012. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp Several studies examined human stress identification using Mental Arithmetic Task (MAT). The identification and prediction of stress levels using existing data processing methodologies are incompetent to predict the stress levels either in real time or laboratory based experiments. The main objectives of the present work is to classify the stress levels using mental arithmetic task and appropriate signal processing methodology, (ii) to analyze the characteristics of Electrocardiogram (ECG) signal for different stress levels, and (iii) to derive the optimum features from a set of statistical features over different frequency bands. Ten healthy female subjects (20 to 25) years voluntarily participated and ECG signal was acquired. In this work, High Frequency (HF) and Low Frequency (LF) frequency band of ECG signal is directly analyzed similar frequency ranges of Heart Rate Viability (HRV) signals. Discrete Wavelet Transform (DWT) have employed for identifying the stress relevant effect of ANS activity during different stress levels. Statistical features derived using DWT are mapped into four different states including three stress levels (normal, low stress, medium stress, and high stress) using K-Nearest Neighbor (KNN) classifier. Covariance feature gives the maximum mean classification rate of 96.3%, and 75.9% in LF and HF bands, respectively. In addition, the maximum average classification accuracy of 65.5% is achieved using mean feature in LF/HF+LF and HF/HF+LF ratios. 2014-05-22T09:01:39Z 2014-05-22T09:01:39Z 2012-10 Working Paper p. 77-81 978-1-4673-1649-1 (Print) 978-1-4673-1704-7 (Online) 1985-5753 http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6408369 http://dspace.unimap.edu.my:80/dspace/handle/123456789/34652 http://dx.doi.org/10.1109/STUDENT.2012.6408369 en Proceeding of The 3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT 2012); IEEE Conference Publications
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 ECG
KNN classifier
Mental arithmetic task
Stress
Wavelet transform
spellingShingle ECG
KNN classifier
Mental arithmetic task
Stress
Wavelet transform
Karthikeyan, Palanisamy
Murugappan, M., Dr.
Sazali, Yaacob, Prof. Dr.
A study on mental arithmetic task based human stress level classification using discrete wavelet transform
description Proceeding of The 3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT 2012) at Kuala Lumpur, Malaysia on 6 October 2012 through 9 October 2012. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp
author2 karthi_209170@yahoo.com
author_facet karthi_209170@yahoo.com
Karthikeyan, Palanisamy
Murugappan, M., Dr.
Sazali, Yaacob, Prof. Dr.
format Working Paper
author Karthikeyan, Palanisamy
Murugappan, M., Dr.
Sazali, Yaacob, Prof. Dr.
author_sort Karthikeyan, Palanisamy
title A study on mental arithmetic task based human stress level classification using discrete wavelet transform
title_short A study on mental arithmetic task based human stress level classification using discrete wavelet transform
title_full A study on mental arithmetic task based human stress level classification using discrete wavelet transform
title_fullStr A study on mental arithmetic task based human stress level classification using discrete wavelet transform
title_full_unstemmed A study on mental arithmetic task based human stress level classification using discrete wavelet transform
title_sort study on mental arithmetic task based human stress level classification using discrete wavelet transform
publisher IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/34652
_version_ 1643797555483508736
score 13.222552

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