Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals

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Main Authors:	Murugappan, Nagarajan, Ramachandran, Prof. Dr., Sazali, Yaacob, Prof. Dr.
Other Authors:	murugappan@unimap.edu.my
Format:	Article
Language:	English
Published:	Biomedical Engineering Society of the R.O.C. 2011
Subjects:	Electroencephalogram (EEG) Emotion assessment Surface laplacian filtering Wavelet transform K nearest neighbor (KNN) Linear discriminant analysis (LDA)
Online Access:	http://dspace.unimap.edu.my/xmlui/handle/123456789/12189
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Institution:	Universiti Malaysia Perlis
Language:	English

id	my.unimap-12189
record_format	dspace
spelling	my.unimap-121892011-06-10T04:09:03Z Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals Murugappan Nagarajan, Ramachandran, Prof. Dr. Sazali, Yaacob, Prof. Dr. murugappan@unimap.edu.my Electroencephalogram (EEG) Emotion assessment Surface laplacian filtering Wavelet transform K nearest neighbor (KNN) Linear discriminant analysis (LDA) Link to publisher's homepage at http://www.bmes.org.tw/ In this paper, we present human emotion assessment using electroencephalogram (EEG) signals. The combination of surface Laplacian (SL) filtering, time-frequency analysis of wavelet transform (WT) and linear classifiers are used to classify discrete emotions (happy, surprise, fear, disgust, and neutral). EEG signals were collected from 20 subjects through 62 active electrodes, which were placed over the entire scalp based on the International 10-10 system. An audio-visual (video clips) induction-based protocol was designed for evoking discrete emotions. The raw EEG signals were preprocessed through surface Laplacian filtering method and decomposed into five different EEG frequency bands (delta, theta, alpha, beta and gamma) using WT. In this work, we used three different wavelet functions, namely: "db8", "sym8" and "coif5", for extracting the statistical features from EEG signal for classifying the emotions. In order to evaluate the efficacy of emotion classification under different sets of EEG channels, we compared the classification accuracy of the original set of channels (62 channels) with that of a reduced set of channels (24 channels). The validation of statistical features was performed using 5-fold cross validation. In this work, K nearest neighbor (KNN) outperformed linear discriminant analysis (LDA) by offering a maximum average classification rate of 83.04% on 62 channels and 79.17% on 24 channels, respectively. Finally, we present the average classification accuracy and individual classification accuracy of two different classifiers for justifying the performance of our emotion recognition system. 2011-06-10T04:05:26Z 2011-06-10T04:05:26Z 2011 Article Journal of Medical and Biological Engineering, vol. 31(1), 2011, pages 45-52 1609-0985 http://jmbe.bme.ncku.edu.tw/index.php/bme/article/view/455/807 http://hdl.handle.net/123456789/12189 en Biomedical Engineering Society of the R.O.C.
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	Electroencephalogram (EEG) Emotion assessment Surface laplacian filtering Wavelet transform K nearest neighbor (KNN) Linear discriminant analysis (LDA)
spellingShingle	Electroencephalogram (EEG) Emotion assessment Surface laplacian filtering Wavelet transform K nearest neighbor (KNN) Linear discriminant analysis (LDA) Murugappan Nagarajan, Ramachandran, Prof. Dr. Sazali, Yaacob, Prof. Dr. Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals
description	Link to publisher's homepage at http://www.bmes.org.tw/
author2	murugappan@unimap.edu.my
author_facet	murugappan@unimap.edu.my Murugappan Nagarajan, Ramachandran, Prof. Dr. Sazali, Yaacob, Prof. Dr.
format	Article
author	Murugappan Nagarajan, Ramachandran, Prof. Dr. Sazali, Yaacob, Prof. Dr.
author_sort	Murugappan
title	Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals
title_short	Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals
title_full	Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals
title_fullStr	Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals
title_full_unstemmed	Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals
title_sort	combining spatial filtering and wavelet transform for classifying human emotions using eeg signals
publisher	Biomedical Engineering Society of the R.O.C.
publishDate	2011
url	http://dspace.unimap.edu.my/xmlui/handle/123456789/12189
_version_	1643790618879590400

Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals

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