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Frequency study of facial electromyography signals with respect to emotion recognition

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Main Authors: Selvaraj, Jerritta, Murugappan, Muthusamy, Dr., Wan Khairunizam, Wan Ahmad, Dr., Sazali, Yaacob, Prof. Dr.
Other Authors: khairunizam@unimap.edu.my
Format: Article
Language:English
Published: Walter de Gruyter GmbH 2014
Subjects:
Analysis of variance
Audio visual stimuli
Emotional frequency analysis
Human-computer interaction
Facial electromyogram signals
Sensitivity
Specificity
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33184
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spelling my.unimap-331842014-04-21T01:41:50Z Frequency study of facial electromyography signals with respect to emotion recognition Selvaraj, Jerritta Murugappan, Muthusamy, Dr. Wan Khairunizam, Wan Ahmad, Dr. Sazali, Yaacob, Prof. Dr. khairunizam@unimap.edu.my murugappan@unimap.edu.my s.yaacob@unimap.edu.my Analysis of variance Audio visual stimuli Emotional frequency analysis Human-computer interaction Facial electromyogram signals Sensitivity Specificity Link to publisher's homepage http://www.degruyter.com/ Emotional intelligence is one of the key research areas in human-computer interaction. This paper reports the development of an emotion recognition system using facial electromyogram (EMG) signals focusing the ambiguity on the frequency ranges used by different research works. The six emotional states (happiness, sadness, fear, surprise, disgust, and neutral) were elicited in 60 subjects using audio visual stimuli. Statistical features were extracted from the signals at high, medium, low, and very low frequency levels. They were then classified using four classifiers – naïve Bayes, regression tree, K-nearest neighbor, and fuzzy K-nearest neighbor, and the performance of the system at the different frequency levels were studied using three metrics, namely, % accuracy, sensitivity, and specificity. The post hoctests in analysis of variance (ANOVA) indicate that the features contain significant emotional information at the very low-frequency range (<0.08 Hz). Similarly, the performance metrics of the classifiers also ensure better recognition rate at very low-frequency range. Though this range of frequency has not been used by researchers, the results of this work indicate that it should not be ignored. Further investigation of the very low frequency range to identify emotional information is still in progress. 2014-03-28T02:58:40Z 2014-03-28T02:58:40Z 2014-01 Article Biomedizinische Technik/Biomedical Engineering, January 2014, pages 1–9 1862-278X (Online) 0013-5585 (Print) http://dspace.unimap.edu.my:80/dspace/handle/123456789/33184 10.1515/bmt-2013-0118 http://www.degruyter.com/ en Walter de Gruyter GmbH
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 Analysis of variance
Audio visual stimuli
Emotional frequency analysis
Human-computer interaction
Facial electromyogram signals
Sensitivity
Specificity
spellingShingle Analysis of variance
Audio visual stimuli
Emotional frequency analysis
Human-computer interaction
Facial electromyogram signals
Sensitivity
Specificity
Selvaraj, Jerritta
Murugappan, Muthusamy, Dr.
Wan Khairunizam, Wan Ahmad, Dr.
Sazali, Yaacob, Prof. Dr.
Frequency study of facial electromyography signals with respect to emotion recognition
description Link to publisher's homepage http://www.degruyter.com/
author2 khairunizam@unimap.edu.my
author_facet khairunizam@unimap.edu.my
Selvaraj, Jerritta
Murugappan, Muthusamy, Dr.
Wan Khairunizam, Wan Ahmad, Dr.
Sazali, Yaacob, Prof. Dr.
format Article
author Selvaraj, Jerritta
Murugappan, Muthusamy, Dr.
Wan Khairunizam, Wan Ahmad, Dr.
Sazali, Yaacob, Prof. Dr.
author_sort Selvaraj, Jerritta
title Frequency study of facial electromyography signals with respect to emotion recognition
title_short Frequency study of facial electromyography signals with respect to emotion recognition
title_full Frequency study of facial electromyography signals with respect to emotion recognition
title_fullStr Frequency study of facial electromyography signals with respect to emotion recognition
title_full_unstemmed Frequency study of facial electromyography signals with respect to emotion recognition
title_sort frequency study of facial electromyography signals with respect to emotion recognition
publisher Walter de Gruyter GmbH
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33184
_version_ 1643797092684005376
score 13.235362

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