iRepository at Perpustakaan UniMAP >
Journal Articles >
School of Mechatronic Engineering (Articles) >

Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/8993

Title: Classification of human emotion from eeg using discrete wavelet transform
Authors: Murugappan, M.
Ramachandran, Nagarajan
Sazali, Yaacob, Prof. Dr.
Keywords: Discrete wavelet transform;electroencephalogram (EEG);Human emotions;K Nearest Neighbor (KNN);Linear Discriminant Analysis (LDA);Discrete Wavelet Transform (DWT)
Issue Date: Apr-2010
Publisher: Scientific Research Publishing Inc
Citation: Journal of Biomedical Science and Engineering, vol. 3(4), April 2010, pages 390-396
Abstract: In this paper, we summarize the human emotion recognition using different set of electroencephalogram (EEG) channels using discrete wavelet transform. An audio-visual induction based protocol has been designed with more dynamic emotional content for inducing discrete emotions (disgust, happy, surprise, fear and neutral). EEG signals are collected using 64 electrodes from 20 subjects and are placed over the entire scalp using International 10-10 system. The raw EEG signals are preprocessed using Surface Laplacian (SL) filtering method and decomposed into three different frequency bands (alpha, beta and gamma) using Discrete Wavelet Transform (DWT). We have used db4 wavelet function for deriving a set of conventional and modified energy based features from the EEG signals for classifying emotions. Two simple pattern classification methods, K Nearest Neighbor (KNN) and Linear Discriminant Analysis (LDA) methods are used and their performances are compared for emotional states classification. The experimental results indicate that, one of the proposed features (ALREE) gives the maximum average classification rate of 83.26% using KNN and 75.21% using LDA compared to those of conventional features. Finally, we present the average classification rate and subsets of emotions classification rate of these two different classifiers for justifying the performance of our emotion recognition system.
Description: Link to publisher's homepage at http://www.scirp.org/
URI: http://www.scirp.org/journal/jbise/
ISSN: 1937-6871
Appears in Collections:M. Murugappan, Dr.
School of Mechatronic Engineering (Articles)
Sazali Yaacob, Prof. Dr.
Ramachandran, Nagarajan, Prof. Dr.

Files in This Item:

File Description SizeFormat
Classification of human emotion from eeg using discrete wavelet transform.pdf32 kBAdobe PDFView/Open
classification of human emotionMURUGAPPAN.pdfAccess is limited to UniMAP community486.07 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! Perpustakaan Tuanku syed Faizuddin Putra, Kampus Pauh Putra, Universiti Malaysia Perlis, 02600, Arau Perlis
TEL: +604-9885420 | FAX: +604-9885405 | EMAIL: rujukan@unimap.edu.my Feedback