NDLI: Investigation of window size in classification of EEG-emotion signal with wavelet entropy and support vector machine

Content Provider	IEEE Xplore Digital Library
Author	Candra, H. Yuwono, M. Rifai Chai Handojoseno, A. Elamvazuthi, I. Nguyen, H.T. Su, S.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Univ. Teknol. PETRONAS, Tronoh, Malaysia (Elamvazuthi, I.) \|\| Centre for Health Technol., Univ. of Technol., Sydney, Sydney, NSW, Australia (Candra, H.; Yuwono, M.; Rifai Chai; Handojoseno, A.; Nguyen, H.T.; Su, S.)
Abstract	When dealing with patients with psychological or emotional symptoms, medical practitioners are often faced with the problem of objectively recognizing their patients' emotional state. In this paper, we approach this problem using a computer program that automatically extracts emotions from EEG signals. We extend the finding of Koelstra et. al [IEEE trans. affective comput., vol. 3, no. 1, pp. 18-31, 2012] using the same dataset (i.e. the DEAP: dataset for emotion analysis using electroencephalogram, physiological and video signals), where we observed that the accuracy can be further improved using wavelet features extracted from shorter time segments. More precisely, we achieved accuracy of 65% for both valence and arousal using the wavelet entropy of 3 to 12 seconds signal segments. This improvement in accuracy entails an important discovery that information on emotions contained in the EEG signal may be better described in term of wavelets and in shorter time segments.
Starting Page	7250
Ending Page	7253
File Size	753798
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7320065
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Electroencephalography Discrete wavelet transforms Entropy Feature extraction Support vector machines Emotion recognition
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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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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