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Title: Electroencephalogram subject identification: A review
Authors: Del Pozo-Banos, Marcos
Alonso, Jesús B. 
Ticay-Rivas, Jaime R.
Travieso, Carlos M. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Electroencephalogram, Biometrics, Genetics, Identification
Issue Date: 2014
Publisher: 0957-4174
Journal: Expert Systems with Applications 
Abstract: This is, to the best of the authors knowledge, the first complete research on the state of the art on EEG based subject identification. As well as covering the full story of this field (from 1980 to 2013), an overview of the findings made in genetic and neurophysiology areas, from which it is based, is also provided. After a comprehensive search, 109 biometric publications were found and studied, from which 88 were finally included in this document. A categorization of papers is proposed based on the recording paradigm. The most used databases, some of them public, have been identified and named to allow the comparison of results from these and future works. The findings of this work show that, although basic questions remain to be answered, the EEG, and specially its power spectrum in the range of the alpha rhythm, contains subject specific information that can be used for classification. Moreover, approaches such as a multi-day-session training, the fusion of information from different electrodes and bands, and Support Vector Machines are recommended to maximize the system’s performance. All in all, the problem of subject identification by means of their EEG is harder than initially expected, as it relies on information extracted from complex heterogeneous EEG traits which are the results of elaborated models of inheritance, which in turn makes the problem very sensitive to its variables (time, frequency, space, recording paradigm and algorithms).
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2014.05.013
Source: Expert Systems with Applications[ISSN 0957-4174],v. 41, p. 6537-6554
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