NDLI: Classification of human emotions from EEG signals using filtering and ANFIS classifier

Content Provider	IEEE Xplore Digital Library
Author	Ravindran, R.M.
Copyright Year	2014
Description	Author affiliation: P.G Dept. of Comput. Applic., N.G.M Coll., Pollachi, India (Ravindran, R.M.)
Abstract	Human emotion classification has been an attractive research area in the field of data mining. Several research works have been carried out for investigating the classification system for human emotions. This research article is intended to deal with the classification of human emotions through Electroencephalogram (EEG). The essential aspects of this system are feature extraction and accurate classification of the emotion-related EEG-characteristics to attain a significant emotion recognition system. In this research work, the emotions and the patterns of EEG signals of human brain are studied. The aim of this work is to investigate the changes in the brain signals in the domain of different emotions. The study can be analyzed for its utility in the diagnosis of psychosomatic disorders like anxiety and depression in economical way with higher precision. The modified adaptive filtering for signal preprocessing is proposed in this system for removing the noise and artifacts in EEG signal. The adaptive neuro fuzzy inference system is also proposed for classifying and analyzing the emotions based on the features selected. The proposed system is compared with the existing system and the performance of the proposed system is evaluated using the metrics such as specificity and sensitivity.
Starting Page	113
Ending Page	119
File Size	4054315
Page Count	7
File Format	PDF
e-ISBN	9781479979875
DOI	10.1109/ICCTET.2014.6966272
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-08
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Emotion recognition Conferences Brain signal Adaptive filters Adaptive filtering Feature extraction Brain modeling Electroencephalography Classification algorithms Adaptive neuro fuzzy inference system
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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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