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Human emotion recognition through short time Electroencephalogram (EEG) signals using Fast Fourier Transform (FFT)

Proceeding of The 9th International Colloquium on Signal Processing and its Applications 2013 (CSPA 2013) at Kuala Lumpur, Malaysia on 8 March 2013 through 10 March 2013

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Main Authors: Murugappan, Muthusamy, Dr., Murugappan, Subbulakshmi
Other Authors: murugappan@unimap.edu.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2014
Subjects:
Electroencephalogram (EEG)
Fast Fourier Transform (FFT)
K Nearest Neighbor (KNN)
Probabilistic Neural Network (PNN)
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/34201
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spelling my.unimap-342012014-04-30T09:19:55Z Human emotion recognition through short time Electroencephalogram (EEG) signals using Fast Fourier Transform (FFT) Murugappan, Muthusamy, Dr. Murugappan, Subbulakshmi murugappan@unimap.edu.my subbulakshmi@unimap.edu.my Electroencephalogram (EEG) Fast Fourier Transform (FFT) K Nearest Neighbor (KNN) Probabilistic Neural Network (PNN) Proceeding of The 9th International Colloquium on Signal Processing and its Applications 2013 (CSPA 2013) at Kuala Lumpur, Malaysia on 8 March 2013 through 10 March 2013 Human emotion recognition plays a vital role in psychology, psycho-physiology and human machine interface (HMI) design. Electroencephalogram (EEG) reflects the internal emotional state changes of the subject compared to other conventional methods (face recognition, gestures, speech, etc). In this work, EEG signals are collected using 62 channels from 20 subjects in the age group of 21∼39 years for determining discrete emotions. Audio-visual stimuli (video clips) is used for inducing five different emotions (happy, surprise, fear, disgust, neutral). EEG signals are preprocessed through Butterworth 4 th order filter with a cut off frequency of 0.5 Hz-60 Hz and smoothened using Surface Laplacian filter. EEG signals are framed into a short time duration of 5s and two statistical features (spectral centroid and spectral entropy) in four frequency bands namely alpha (8 Hz-16 Hz), beta (16 Hz-32 Hz), gamma (32 Hz-60 Hz) and alpha to gamma (8 Hz-60 Hz) are extracted using Fast Fourier Transform (FFT). These features are mapped into the corresponding emotions using two simple classifiers such as K Nearest Neighbor(KNN) and Probabilistic Neural Network (PNN). In this work, KNN outperforms PNN by offering the maximum mean classification accuracy of 91.33 % on beta band. This experimental results indicates the short time duration of EEG signals is highly essential for detecting the emotional state changes of the subjects. 2014-04-30T09:19:55Z 2014-04-30T09:19:55Z 2013-03 Working Paper p. 289-294 978-146735609-1 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6530058 http://dspace.unimap.edu.my:80/dspace/handle/123456789/34201 en Proceeding of The 9th International Colloquium on Signal Processing and its Applications 2013 (CSPA 2013); Institute of Electrical and Electronics Engineers (IEEE)
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)
Fast Fourier Transform (FFT)
K Nearest Neighbor (KNN)
Probabilistic Neural Network (PNN)
spellingShingle Electroencephalogram (EEG)
Fast Fourier Transform (FFT)
K Nearest Neighbor (KNN)
Probabilistic Neural Network (PNN)
Murugappan, Muthusamy, Dr.
Murugappan, Subbulakshmi
Human emotion recognition through short time Electroencephalogram (EEG) signals using Fast Fourier Transform (FFT)
description Proceeding of The 9th International Colloquium on Signal Processing and its Applications 2013 (CSPA 2013) at Kuala Lumpur, Malaysia on 8 March 2013 through 10 March 2013
author2 murugappan@unimap.edu.my
author_facet murugappan@unimap.edu.my
Murugappan, Muthusamy, Dr.
Murugappan, Subbulakshmi
format Working Paper
author Murugappan, Muthusamy, Dr.
Murugappan, Subbulakshmi
author_sort Murugappan, Muthusamy, Dr.
title Human emotion recognition through short time Electroencephalogram (EEG) signals using Fast Fourier Transform (FFT)
title_short Human emotion recognition through short time Electroencephalogram (EEG) signals using Fast Fourier Transform (FFT)
title_full Human emotion recognition through short time Electroencephalogram (EEG) signals using Fast Fourier Transform (FFT)
title_fullStr Human emotion recognition through short time Electroencephalogram (EEG) signals using Fast Fourier Transform (FFT)
title_full_unstemmed Human emotion recognition through short time Electroencephalogram (EEG) signals using Fast Fourier Transform (FFT)
title_sort human emotion recognition through short time electroencephalogram (eeg) signals using fast fourier transform (fft)
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/34201
_version_ 1643797421264732160
score 13.159267

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