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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5639
Title: A Novel framework of EEG-based user identification by analyzing music-listening behavior
Authors: Kaur B.
Singh D.
Pratim Roy, Partha
Published in: Multimedia Tools and Applications
Abstract: This paper introduces a novel framework for user identification by analyzing neuro-signals. Studies regarding Electroencephalography (EEG) revealed that such bio-signals are sensitive, hard to forge, confidential, and unique which the conventional biometric systems like face, speaker, signature and voice lack. Traditionally, researchers investigated the neuro-signal patterns by asking users to perform various imaginary, visual or calculative tasks. In this work, we have analyzed this neuro-signal pattern using audio as stimuli. The EEG signals are recorded simultaneously while user is listening to music. Four different genres of music are considered as users have their own preference and accordingly they respond with different emotions and interests. The users are also asked to provide music preference which acts as a personal identification mechanism. The framework offers the benefit of uniqueness in neuro-signal pattern even with the same music preference by different users. We used two different classifiers i.e. Hidden Markov Model (HMM) based temporal classifier and Support Vector Machine (SVM) for user identification system. A dataset of 2400 EEG signals while listening to music was collected from 60 users. User identification performance of 97.50 % and 93.83 % have been recorded with HMM and SVM classifiers, respectively. Finally, the performance of the system is also evaluated on various emotional states after showing different emotional videos to users. © 2016, Springer Science+Business Media New York.
Citation: Multimedia Tools and Applications (2017), 76(24): 25581-25602
URI: https://doi.org/10.1007/s11042-016-4232-2
http://repository.iitr.ac.in/handle/123456789/5639
Issue Date: 2017
Publisher: Springer New York LLC
Keywords: Electroencephalography (EEG)
Hidden Markov Model (HMM)
Savtizik-Golay filter
Support Vector Machine (SVM)
User identification
Wavelet transform
ISSN: 13807501
Author Scopus IDs: 57208659024
57209912206
56880478500
Author Affiliations: Kaur, B., Department of Computer Science and Engineering, DCRUST, Sonipat, India
Singh, D., Department of Computer Science and Engineering, DCRUST, Sonipat, India
Roy, P.P., Department of Computer Science and Engineering, IIT, Roorkee, India
Corresponding Author: Kaur, B.; Department of Computer Science and Engineering, DCRUSTIndia; email: kaur.barjinder@gmail.com
Appears in Collections:Journal Publications [CS]

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