NDLI: Wavelet based analysis of EEG signal for evaluating mental behavior

Content Provider	IEEE Xplore Digital Library
Author	Ahmed, T. Islam, M. Yusuf, M.S.U. Ahmad, M.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Khulna Univ. of Eng. & Technol., Khulna, Bangladesh (Ahmed, T.; Islam, M.; Yusuf, M.S.U.; Ahmad, M.)
Abstract	The purpose of the research is to evaluate the different human mental behavior through Electroencephalogram (EEG) signal with time-frequency analysis by receiving information from the internal changes of brain state. The paper presents the detection of human mental states based on some salient features of EEG signal. For this purpose seven emotional states have been specified such as relax, thought, memory related, motor action, pleasant, fear, and enjoying music. Several EEG signals have been collected for these states and analyzed using discrete wavelet transform. The discrete wavelet transform (DWT) is used to extract different significant features from the analyzed signal by computing the subband coefficients and applying statistical measures on them. Among various statistical measures maximum and minimum value, mean and standard deviation of wavelet coefficients in each subband are chosen which indicate the dispersion in different mental states and help to evaluate them. The analyzed results are compared with the spectrum analysis. It is found that wavelet analysis provides more effective way in the functioning of the brain to study of mental behavior in compare with Fourier analysis.
Sponsorship	IEEE Comput. Soc.
Starting Page	1
Ending Page	6
File Size	977561
Page Count	6
File Format	PDF
ISBN	9781479903979
e-ISBN	9781479904006
DOI	10.1109/ICIEV.2013.6572706
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-17
Publisher Place	Bangladesh
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrodes DWT Time-frequency analysis Statistical measures DFT Feature extraction Mental state Electroencephalography Discrete wavelet transforms EEG signal Wavelet coefficients
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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