NDLI: Human emotion modeling based on salient global features of EEG signal

Content Provider	IEEE Xplore Digital Library
Author	Ahmed, T. Islam, M. Ahmad, M.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Khulna Univ. of Eng. & Technol., Khulna, Bangladesh (Ahmed, T.; Islam, M.; Ahmad, M.)
Abstract	Feature extraction and accurate classification of the emotion-related EEG-characteristics have a key role in success of emotion recognition systems. This paper proposes an emotion modeling from EEG (Electroencephalogram) signals based on both time and frequency domain features by applying some statistical measures, Fourier and wavelet transform. After collecting the EEG signals, the various kinds of EEG features are investigated to build an emotion classification system. The main objective of this work is to compare the efficacy of the extracted features for classifying five types of emotional states relax, mental task, memory related task, pleasant, and fear. For this purpose support vector machine classifier was employed to classify the five emotional states by using salient global features. In case of statistical features the overall accuracy was obtained 54.2%, which is improved for FFT features 55.00% and the highest accuracy was obtained by DWT features 60.15%.
Sponsorship	Mutual Trust Bank Ltd.
Starting Page	246
Ending Page	251
File Size	584502
Page Count	6
File Format	PDF
DOI	10.1109/ICAEE.2013.6750341
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-19
Publisher Place	Bangladesh
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Time-frequency analysis Emotional states Accuracy Frequency and time-frequency domain features Feature extraction Brain modeling Electroencephalography Time Support vector machine EEG emotion modeling
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
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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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