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Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT)

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Main Authors: Murugappan, Muthusamy, Dr., Murugappan, Subbulakshmi, Bong, Siao Zheng
Other Authors: murugappan@unimap.edu.my
Format: Article
Language:English
Published: Society of Physical Therapy Science 2014
Subjects:
Discrete wavelet transform
Heart rate variability
Human emotions
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/34698
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spelling my.unimap-346982014-05-23T09:10:10Z Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT) Murugappan, Muthusamy, Dr. Murugappan, Subbulakshmi Bong, Siao Zheng murugappan@unimap.edu.my subbulakshmi@unimap.edu.my wendy880806@gmail.com Discrete wavelet transform Heart rate variability Human emotions Link to publisher's homepage at https://www.jstage.jst.go.jp [Purpose] Intelligent emotion assessment systems have been highly successful in a variety of applications, such as e-learning, psychology, and psycho-physiology. This study aimed to assess five different human emotions (happiness, disgust, fear, sadness, and neutral) using heart rate variability (HRV) signals derived from an electrocardiogram (ECG). [Subjects] Twenty healthy university students (10 males and 10 females) with a mean age of 23 years participated in this experiment. [Methods] All five emotions were induced by audio-visual stimuli (video clips). ECG signals were acquired using 3 electrodes and were preprocessed using a Butterworth 3rd order filter to remove noise and baseline wander. The Pan-Tompkins algorithm was used to derive the HRV signals from ECG. Discrete wavelet transform (DWT) was used to extract statistical features from the HRV signals using four wavelet functions: Daubechies6 (db6), Daubechies7 (db7), Symmlet8 (sym8), and Coifet5 (coif5). The k-nearest neighbor (KNN) and linear discriminate analysis (LDA) were used to map the statistical features into corresponding emotions. [Results] KNN provided the maximum average emotion classification rate compared to LDA for five emotions (sadness - 50.28%; happiness - 79.03%; fear - 77.78%; disgust - 88.6%; and neutral - 78.34%). [Conclusion] The results of this study indicate that HRV may be a reliable indicator of changes in the emotional state of subjects and provides an approach to the development of a real-time emotion assessment system with a higher reliability than other systems. 2014-05-23T09:10:10Z 2014-05-23T09:10:10Z 2013-06 Article Journal of Physical Therapy Science, vol. 25(7), 2013, pages 753-759 0915-5287 https://www.jstage.jst.go.jp/article/jpts/25/7/25_jpts-2012-446/_article http://dspace.unimap.edu.my:80/dspace/handle/123456789/34698 en Society of Physical Therapy Science
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 Discrete wavelet transform
Heart rate variability
Human emotions
spellingShingle Discrete wavelet transform
Heart rate variability
Human emotions
Murugappan, Muthusamy, Dr.
Murugappan, Subbulakshmi
Bong, Siao Zheng
Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT)
description Link to publisher's homepage at https://www.jstage.jst.go.jp
author2 murugappan@unimap.edu.my
author_facet murugappan@unimap.edu.my
Murugappan, Muthusamy, Dr.
Murugappan, Subbulakshmi
Bong, Siao Zheng
format Article
author Murugappan, Muthusamy, Dr.
Murugappan, Subbulakshmi
Bong, Siao Zheng
author_sort Murugappan, Muthusamy, Dr.
title Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT)
title_short Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT)
title_full Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT)
title_fullStr Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT)
title_full_unstemmed Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT)
title_sort frequency band analysis of electrocardiogram (ecg) signals for human emotional state classification using discrete wavelet transform (dwt)
publisher Society of Physical Therapy Science
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/34698
_version_ 1643797562464927744
score 13.211869

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