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Exploiting the P300 paradigm for cognitive biometrics

Gupta, Cota Navin, Palaniappan, Ramaswamy, Paramesran, Raveendran (2012) Exploiting the P300 paradigm for cognitive biometrics. International Journal of Cognitive Biometrics, 1 (1). pp. 26-38. ISSN 2042-6461. (doi:10.1504/IJCB.2012.046513) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
https://doi.org/10.1504/IJCB.2012.046513

Abstract

Automatic identification of a person’s individuality is an important issue today. Brain Computer Interfaces (BCI) which uses EEG as a modality is a promising area for cognitive biometrics. A BCI system could be used to recognise a sequence (say letters, colours or images) by the user. This sequence could form a ‘BrainWord’, which could be used for authentication in a multimodal environment with other technologies for high security applications. In this work, we studied several variations of the well-known P300 BCI paradigm. The influence of irrelevant stimuli during a task was studied by considering the popular Rapid Serial Visual Paradigm (RSVP) . The variation in spatial locations of the presentation stimuli during a task was studied, by designing a Spatially Varying Paradigm . Comparison of classification accuracies and bit rates for eight participants from a BCI perspective, highlights that RSVP paradigm could be exploited effectively for biometrics.

Item Type: Article
DOI/Identification number: 10.1504/IJCB.2012.046513
Additional information: Unmapped bibliographic data: JO - International Journal of Cognitive Biometrics [Field not mapped to EPrints]
Uncontrolled keywords: authentication system, bit rate, brain-computer interface, cognitive biometrics, P300 potential, RSVP, rapid serial visual paradigm, spatially varying paradigm
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 14 Dec 2018 17:15 UTC
Last Modified: 30 May 2019 08:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/71048 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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