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Electromyogram signal based human emotion classification using KNN and LDA

Proceeding of The IEEE International Conference on System Engineering and Technology, (ICSET 2011) at Shah Alam, Malaysia on 27 June 2011 through 28 June 2011. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp

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Bibliographic Details
Main Author: Murugappan, M., Dr.
Other Authors: murugappan@unimap.edu.my
Format: Working Paper
Language:English
Published: IEEE Conference Publications 2014
Subjects:
Discrete wavelet transform
EMG
Emotions
K Nearest Neighbor
Linear Discriminant Analysis
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/34656
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spelling my.unimap-346562014-05-22T10:39:46Z Electromyogram signal based human emotion classification using KNN and LDA Murugappan, M., Dr. murugappan@unimap.edu.my Discrete wavelet transform EMG Emotions K Nearest Neighbor Linear Discriminant Analysis Proceeding of The IEEE International Conference on System Engineering and Technology, (ICSET 2011) at Shah Alam, Malaysia on 27 June 2011 through 28 June 2011. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp In this paper, we presents Electromyogram (EMG) signal based human emotion classification using K Nearest Neighbor (KNN) and Linear Discriminant Analysis (LDA). Five most dominating emotions such as: happy, disgust, fear, sad and neutral are considered and these emotions are induced through Audio-visual stimuli (video clips). EMG signals are obtained by using 3 electrodes over 10 trials per emotion and preprocessed by using Butterworth 6th order filter to remove noises and external interferences. EMG signals on decomposed into four different frequency ranges ((8 Hz-16 Hz), (16 Hz-31 Hz) and (16 Hz-63 Hz)) using Discrete Wavelet Transform (DWT). The ststistical features extracted from the above frequency bands are mapped into five different emotions using two simple classifiers such as KNN and LDA. The value of K in KNN is varied randomly, and maximum classification rate is achieved at K=3. KNN classifier gives the highest classification rate on four emotions (disgust, happy, fear and neutral) different emotions and LDA on sad emotion. The maximum classification rate of disgust, happy, fear neutral, and sad are 90.83%, 100%, 94.17%, and 90.28% and 43.89%, respectively are achieved using KNN and LDA. The results from the proposed methodology are promising and female are easily evoked by different emotional stimuli compared to male. 2014-05-22T10:39:46Z 2014-05-22T10:39:46Z 2011-06 Working Paper p. 106-110 http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5993430 http://dspace.unimap.edu.my:80/dspace/handle/123456789/34656 http://dx.doi.org/10.1109/ICSEngT.2011.5993430 978-1-4577-1256-2 en Proceeding of The IEEE International Conference on System Engineering and Technology (ICSET 2011); 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 Discrete wavelet transform
EMG
Emotions
K Nearest Neighbor
Linear Discriminant Analysis
spellingShingle Discrete wavelet transform
EMG
Emotions
K Nearest Neighbor
Linear Discriminant Analysis
Murugappan, M., Dr.
Electromyogram signal based human emotion classification using KNN and LDA
description Proceeding of The IEEE International Conference on System Engineering and Technology, (ICSET 2011) at Shah Alam, Malaysia on 27 June 2011 through 28 June 2011. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp
author2 murugappan@unimap.edu.my
author_facet murugappan@unimap.edu.my
Murugappan, M., Dr.
format Working Paper
author Murugappan, M., Dr.
author_sort Murugappan, M., Dr.
title Electromyogram signal based human emotion classification using KNN and LDA
title_short Electromyogram signal based human emotion classification using KNN and LDA
title_full Electromyogram signal based human emotion classification using KNN and LDA
title_fullStr Electromyogram signal based human emotion classification using KNN and LDA
title_full_unstemmed Electromyogram signal based human emotion classification using KNN and LDA
title_sort electromyogram signal based human emotion classification using knn and lda
publisher IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/34656
_version_ 1643797556829880320
score 13.159267

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