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Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups

Proceeding of The 5th Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII 2013) at Geneva, Switzerland on 2 September 2013 through 5 September 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp

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Bibliographic Details
Main Authors: Selvaraj, Jerritta, Murugappan, M., Dr., Wan Khairunizam, Wan Ahmad, Dr., Sazali, Yaacob, Prof. Dr.
Other Authors: sn.jerritta@gmail.com
Format: Working Paper
Language:English
Published: IEEE Conference Publications 2014
Subjects:
Emotion
Inducement Stimuli
Physiological signals
Signal Processing Techniques
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/34629
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spelling my.unimap-346292014-05-22T04:48:12Z Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups Selvaraj, Jerritta Murugappan, M., Dr. Wan Khairunizam, Wan Ahmad, Dr. Sazali, Yaacob, Prof. Dr. sn.jerritta@gmail.com murugappan@unimap.edu.my khairunizam@unimap.edu.my s.yaacob@unimap.edu.my Emotion Inducement Stimuli Physiological signals Signal Processing Techniques Proceeding of The 5th Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII 2013) at Geneva, Switzerland on 2 September 2013 through 5 September 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp Emotion recognition using physiological signals is one of the key research areas in Human Computer Interaction (HCI). In this work, we identify the six basic emotional states (Happiness, sadness, fear, surprise, disgust and neutral) from the QRS complex of electrocardiogram (ECG) signals. We focus specifically on the nonlinear feature 'Hurst exponent' computed using two methods namely rescaled range statistics (RRS) and finite variance scaling (FVS). The study is done on emotional ECG data obtained using audio visual stimuli from sixty subjects belonging to three different age groups - children (9 to 16 years), young adults (18 to 25 years) and adults (39 to 68 years). The performance of the Hurst exponent computed using RRS and FVS for individual age groups resulted in a maximum average accuracy of 78.21%. The combined analysis of the all the age groups had a maximum average accuracy of 70.23%. In general, the results of all the six emotional states indicate better performance compared to previous research works. However, the performance needs to be further improved in order to develop a reliable and robust emotion recognition system. 2014-05-22T04:48:12Z 2014-05-22T04:48:12Z 2013-09 Working Paper p. 849-854 978-076955048-0 http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6681551 http://dspace.unimap.edu.my:80/dspace/handle/123456789/34629 http://dx.doi.org/10.1109/ACII.2013.159 en Proceeding of The 5th Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII 2013); 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 Emotion
Inducement Stimuli
Physiological signals
Signal Processing Techniques
spellingShingle Emotion
Inducement Stimuli
Physiological signals
Signal Processing Techniques
Selvaraj, Jerritta
Murugappan, M., Dr.
Wan Khairunizam, Wan Ahmad, Dr.
Sazali, Yaacob, Prof. Dr.
Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups
description Proceeding of The 5th Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII 2013) at Geneva, Switzerland on 2 September 2013 through 5 September 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp
author2 sn.jerritta@gmail.com
author_facet sn.jerritta@gmail.com
Selvaraj, Jerritta
Murugappan, M., Dr.
Wan Khairunizam, Wan Ahmad, Dr.
Sazali, Yaacob, Prof. Dr.
format Working Paper
author Selvaraj, Jerritta
Murugappan, M., Dr.
Wan Khairunizam, Wan Ahmad, Dr.
Sazali, Yaacob, Prof. Dr.
author_sort Selvaraj, Jerritta
title Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups
title_short Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups
title_full Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups
title_fullStr Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups
title_full_unstemmed Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups
title_sort emotion detection from qrs complex of ecg signals using hurst exponent for different age groups
publisher IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/34629
_version_ 1643797548624773120
score 13.214268

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